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- What Is a Case Study? | Definition, Examples & Methods
What Is a Case Study? | Definition, Examples & Methods
Published on May 8, 2019 by Shona McCombes . Revised on January 30, 2023.
A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.
A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem .
Table of contents
When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyze the case.
A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.
Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.
You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.
Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:
- Provide new or unexpected insights into the subject
- Challenge or complicate existing assumptions and theories
- Propose practical courses of action to resolve a problem
- Open up new directions for future research
Unlike quantitative or experimental research , a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.
However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.
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While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:
- Exemplify a theory by showing how it explains the case under investigation
- Expand on a theory by uncovering new concepts and ideas that need to be incorporated
- Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions
To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.
There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews , observations , and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data.
The aim is to gain as thorough an understanding as possible of the case and its context.
In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.
How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis , with separate sections or chapters for the methods , results and discussion .
Others are written in a more narrative style, aiming to explore the case from various angles and analyze its meanings and implications (for example, by using textual analysis or discourse analysis ).
In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.
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What is the Case Study Method?
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Overview dropdown down, celebrating 100 years of the case method at hbs.
The 2021-2022 academic year marks the 100-year anniversary of the introduction of the case method at Harvard Business School. Today, the HBS case method is employed in the HBS MBA program, in Executive Education programs, and in dozens of other business schools around the world. As Dean Srikant Datar's says, the case method has withstood the test of time.
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How Cases Unfold In the Classroom
How cases unfold in the classroom dropdown up, how cases unfold in the classroom dropdown down, preparation guidelines expand all collapse all, read the professor's assignment or discussion questions read the professor's assignment or discussion questions dropdown down, read the first few paragraphs and then skim the case read the first few paragraphs and then skim the case dropdown down, reread the case, underline text, and make margin notes reread the case, underline text, and make margin notes dropdown down, note the key problems on a pad of paper and go through the case again note the key problems on a pad of paper and go through the case again dropdown down, how to prepare for case discussions dropdown up, how to prepare for case discussions dropdown down, read the professor's assignment or discussion questions, read the first few paragraphs and then skim the case, reread the case, underline text, and make margin notes, note the key problems on a pad of paper and go through the case again, case study best practices expand all collapse all, prepare prepare dropdown down, discuss discuss dropdown down, participate participate dropdown down, relate relate dropdown down, apply apply dropdown down, note note dropdown down, understand understand dropdown down, case study best practices dropdown up, case study best practices dropdown down, participate, what can i expect on the first day dropdown down.
Most programs begin with registration, followed by an opening session and a dinner. If your travel plans necessitate late arrival, please be sure to notify us so that alternate registration arrangements can be made for you. Please note the following about registration:
HBS campus programs – Registration takes place in the Chao Center.
India programs – Registration takes place outside the classroom.
Other off-campus programs – Registration takes place in the designated facility.
What happens in class if nobody talks? Dropdown down
Professors are here to push everyone to learn, but not to embarrass anyone. If the class is quiet, they'll often ask a participant with experience in the industry in which the case is set to speak first. This is done well in advance so that person can come to class prepared to share. Trust the process. The more open you are, the more willing you’ll be to engage, and the more alive the classroom will become.
Does everyone take part in "role-playing"? Dropdown down
Professors often encourage participants to take opposing sides and then debate the issues, often taking the perspective of the case protagonists or key decision makers in the case.
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Home Blog Business Case Study: How to Write and Present It
Case Study: How to Write and Present It
Marketers, consultants, salespeople, and all other types of business managers often use case study analysis to highlight a success story, showing how an exciting problem can be or was addressed. But how do you create a compelling case study and then turn it into a memorable presentation? Get a lowdown from this post!
What is a Case Study?
Let’s start with this great case study definition by the University of South Caroline:
In the social sciences, the term case study refers to both a method of analysis and a specific research design for examining a problem, both of which can generalize findings across populations.
In simpler terms — a case study is an investigative research into a problem aimed at presenting or highlighting solution(s) to the analyzed issues.
A standard business case study provides insights into:
- General business/market conditions
- The main problem faced
- Methods applied
- The outcomes gained using a specific tool or approach
Case studies (also called case reports) are also used in clinical settings to analyze patient outcomes outside of the business realm.
But this is a topic for another time. In this post, we’ll focus on teaching you how to write and present a business case, plus share several case study PowerPoint templates and design tips!
Why Case Studies are a Popular Marketing Technique
Besides presenting a solution to an internal issue, case studies are often used as a content marketing technique . According to a 2020 Content Marketing Institute report, 69% of B2B marketers use case studies as part of their marketing mix.
A case study informs the reader about a possible solution and soft-sells the results, which can be achieved with your help (e.g., by using your software or by partnering with your specialist).
For the above purpose, case studies work like a charm. Per the same report:
- For 9% of marketers, case studies are also the best method for nurturing leads.
- 23% admit that case studies are beneficial for improving conversions.
Moreover, case studies also help improve your brand’s credibility, especially in the current fake news landscape and dubious claims made without proper credits.
Ultimately, case studies naturally help build up more compelling, relatable stories and showcase your product benefits through the prism of extra social proof, courtesy of the case study subject.
Popular Case Study Format Types
Most case studies come either as a slide deck or as a downloadable PDF document.
Typically, you have several options to distribute your case study for maximum reach:
- Case study presentations — in-person, virtual, or pre-recorded, there are many times when a case study presentation comes in handy. For example, during client workshops, sales pitches, networking events, conferences, trade shows, etc.
- Dedicated website page — highlighting case study examples on your website is a great way to convert middle on the funnel prospects. Google’s Think With Google case study section is a great example of a web case study design done right.
- Blog case studies — data-driven storytelling is a staunch way to stand apart from your competition by providing unique insights, no other brand can tell.
- Video case studies — video is a great medium for showcasing more complex business cases and celebrating customer success stories.
How to Write a Case Study: a 4-Step Framework
Once you decide on your case study format, the next step is collecting data and then translating it into a storyline. There are different case study methods and research approaches you can use to procure data.
But let’s say you already have all your facts straight and need to organize them in a clean copy for your presentation deck. Here’s how you should do it.
1. Identify the Problem
Every compelling case study research starts with a problem statement definition. While in business settings, there’s no need to explain your methodology in-depth; you should still open your presentation with a quick problem recap slide.
Be sure to mention:
- What’s the purpose of the case study? What will the audience learn?
- Set the scene. Explain the before, aka the problems someone was facing.
- Advertise the main issues and findings without highlighting specific details.
The above information should nicely fit in several paragraphs or 2-3 case study template slides
2. Explain the Solution
The bulk of your case study copy and presentation slides should focus on the provided solution(s). This is the time to speak at lengths about how the subject went from before to the glorious after.
Here are some writing prompts to help you articulate this better:
- State the subject’s main objective and goals. What outcomes were they after?
- Explain the main solution(s) provided. What was done? Why this, but not that?
- Mention if they tried any alternatives. Why did those work? Why were you better?
This part may take the longest to write. Don’t rush it and reiterate several times. Sprinkle in some powerful words and catchphrases to make your copy more compelling.
3. Collect Testimonials
Persuasive case studies feature the voice of customer (VoC) data — first-party testimonials and assessments of how well the solution work. These provide extra social proof and credibility to all the claims you are making.
So plan and schedule interviews with your subjects to collect their input and testimonials. Also, design your case study interview questions in a way that lets you obtain the quantifiable result.
4. Package The Information in a Slide Deck
Once you have a rough first draft, try different business case templates and designs to see how these help structure all the available information.
As a rule of thumb, try to keep one big idea per slide. If you are talking about a solution, first present the general bullet points. Then give each solution a separate slide where you’ll provide more context and perhaps share some quantifiable results.
For example, if you look at case study presentation examples from AWS like this one about Stripe , you’ll notice that the slide deck has few texts and really focuses on the big picture, while the speaker provides extra context.
Need some extra case study presentation design help? Download our Business Case Study PowerPoint template with 100% editable slides.
How to Do a Case Study Presentation: 3 Proven Tips
Your spoken presentation (and public speaking skills ) are equally if not more important than the case study copy and slide deck. To make a strong business case, follow these quick techniques.
Focus on Telling a Great Story
A case study is a story of overcoming a challenge, achieving something grand. Your delivery should reflect that. Step away from the standard “features => benefits” sales formula. Instead, make your customer the hero of the study. Describe the road they went through and how you’ve helped them succeed.
The premises of your story can be as simple as:
- Help with overcoming a hurdle
- Gaining major impact
- Reaching a new milestone
- Solving a persisting issue no one else code
Based on the above, create a clear story arc. Show where your hero started. Then explain what type of a journey they went through. Inject some emotions in the mix to make your narrative more relatable and memorable.
Experiment with Copywriting Formulas
Copywriting is the art and science of organizing words into compelling and persuasive combinations which help readers retain the right ideas.
To ensure that the audience retains the right takeaways from your case study presentation, you can try using some of the classic copywriting formulas to structure your delivery. These include:
- AIDCA — short for A ttention, I nterest, D esire, C onviction, and A ction. First, grab the audience’s attention by addressing the major problem. Next, pique their interest with some teaser facts. Spark their desire by showing that you know the right way out. Then, show a conviction that you know how to solve the issue—finally, prompt follow-up action such as contacting you to learn more.
- PADS — short for P roblem, A gitation, D iscredit, S olution. This is more of a salesy approach to case study narration. Again, you start with a problem, agitate about its importance, discredit why other solutions won’t cut it, and then present your option.
- 4Ps — short for P roblem, P romise, P roof, P roposal. This is a middle-ground option that prioritizes storytelling over hard pitches. Set the scene first with a problem. Then make a promise of how you can solve it. Show proof in the form of numbers, testimonials, and different scenarios. Round it up with a proposal for getting the same outcomes.
Take an Emotion-Inducing Perspectives
The key to building a strong rapport with an audience is showing that you are one of them and fully understand what they are going through.
One of the ways to build this connection is speaking from an emotion-inducing perspective. This is best illustrated with an example:
- A business owner went to the bank
- A business owner came into a bank branch
In the second case, the wording prompts listeners to paint a mental picture from the perspective of the bank employees — a role you’d like them to relate to. By placing your audience in the right visual perspective, you can make them more receptive to your pitches.
Final Tip: Use Compelling Presentation Visuals
Our brain is wired to process images much faster than text. So when you are presenting a case study, always look for an opportunity to tie in some illustrations such as:
- A product demo/preview
- Processes chart
- Call-out quotes or numbers
- Custom illustrations or graphics
- Customer or team headshots
Use icons to minimize the volume of texts. Also, opt for readable fonts which can look good in a smaller size too.
Finally, practice your case study presentation several times — solo and together with your team — to collect feedback and make last-moment refinements!
1. Business Case Study PowerPoint Template
To efficiently create a Business Case Study it’s important to ask all the right questions and document everything necessary, therefore this PowerPoint Template will provide all the sections you need.
Use This Template
2. Medical Case Study PowerPoint Template
3. Medical Infographics PowerPoint Templates
4. Success Story PowerPoint Template
5. Detective Research PowerPoint Template
6. Animated Clinical Study PowerPoint Templates
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What Is a Case Study?
An in-depth study of one person, group, or event
Kendra Cherry, MS, is the author of the "Everything Psychology Book (2nd Edition)" and has written thousands of articles on diverse psychology topics. Kendra holds a Master of Science degree in education from Boise State University with a primary research interest in educational psychology and a Bachelor of Science in psychology from Idaho State University with additional coursework in substance use and case management.
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Cara Lustik is a fact-checker and copywriter.
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Verywell / Colleen Tighe
Benefits and Limitations
Types of case studies, how to write a case study.
A case study is an in-depth study of one person, group, or event. In a case study, nearly every aspect of the subject's life and history is analyzed to seek patterns and causes of behavior. Case studies can be used in various fields, including psychology, medicine, education, anthropology, political science, and social work.
The purpose of a case study is to learn as much as possible about an individual or group so that the information can be generalized to many others. Unfortunately, case studies tend to be highly subjective, and it is sometimes difficult to generalize results to a larger population.
While case studies focus on a single individual or group, they follow a format similar to other types of psychology writing. If you are writing a case study, it is important to follow the rules of APA format .
A case study can have both strengths and weaknesses. Researchers must consider these pros and cons before deciding if this type of study is appropriate for their needs.
One of the greatest advantages of a case study is that it allows researchers to investigate things that are often difficult to impossible to replicate in a lab. Some other benefits of a case study:
- Allows researchers to collect a great deal of information
- Give researchers the chance to collect information on rare or unusual cases
- Permits researchers to develop hypotheses that can be explored in experimental research
On the negative side, a case study:
- Cannot necessarily be generalized to the larger population
- Cannot demonstrate cause and effect
- May not be scientifically rigorous
- Can lead to bias
Researchers may choose to perform a case study if they are interested in exploring a unique or recently discovered phenomenon. The insights gained from such research can help the researchers develop additional ideas and study questions that might be explored in future studies.
However, it is important to remember that the insights gained from case studies cannot be used to determine cause and effect relationships between variables. However, case studies may be used to develop hypotheses that can then be addressed in experimental research.
Case Study Examples
There have been a number of notable case studies in the history of psychology. Much of Freud's work and theories were developed through the use of individual case studies. Some great examples of case studies in psychology include:
- Anna O : Anna O. was a pseudonym of a woman named Bertha Pappenheim, a patient of a physician named Josef Breuer. While she was never a patient of Freud's, Freud and Breuer discussed her case extensively. The woman was experiencing symptoms of a condition that was then known as hysteria and found that talking about her problems helped relieve her symptoms. Her case played an important part in the development of talk therapy as an approach to mental health treatment.
- Phineas Gage : Phineas Gage was a railroad employee who experienced a terrible accident in which an explosion sent a metal rod through his skull, damaging important portions of his brain. Gage recovered from his accident but was left with serious changes in both personality and behavior.
- Genie : Genie was a young girl subjected to horrific abuse and isolation. The case study of Genie allowed researchers to study whether language could be taught even after critical periods for language development had been missed. Her case also served as an example of how scientific research may interfere with treatment and lead to further abuse of vulnerable individuals.
Such cases demonstrate how case research can be used to study things that researchers could not replicate in experimental settings. In Genie's case, her horrific abuse had denied her the opportunity to learn language at critical points in her development.
This is clearly not something that researchers could ethically replicate, but conducting a case study on Genie allowed researchers the chance to study phenomena that are otherwise impossible to reproduce.
There are a few different types of case studies that psychologists and other researchers might utilize:
- Collective case studies : These involve studying a group of individuals. Researchers might study a group of people in a certain setting or look at an entire community. For example, psychologists might explore how access to resources in a community has affected the collective mental well-being of those living there.
- Descriptive case studies : These involve starting with a descriptive theory. The subjects are then observed, and the information gathered is compared to the pre-existing theory.
- Explanatory case studies : These are often used to do causal investigations. In other words, researchers are interested in looking at factors that may have caused certain things to occur.
- Exploratory case studies : These are sometimes used as a prelude to further, more in-depth research. This allows researchers to gather more information before developing their research questions and hypotheses .
- Instrumental case studies : These occur when the individual or group allows researchers to understand more than what is initially obvious to observers.
- Intrinsic case studies : This type of case study is when the researcher has a personal interest in the case. Jean Piaget's observations of his own children are good examples of how an intrinsic cast study can contribute to the development of a psychological theory.
The three main case study types often used are intrinsic, instrumental, and collective. Intrinsic case studies are useful for learning about unique cases. Instrumental case studies help look at an individual to learn more about a broader issue. A collective case study can be useful for looking at several cases simultaneously.
The type of case study that psychology researchers utilize depends on the unique characteristics of the situation as well as the case itself.
There are also different methods that can be used to conduct a case study, including prospective and retrospective case study methods.
Prospective case study methods are those in which an individual or group of people is observed in order to determine outcomes. For example, a group of individuals might be watched over an extended period of time to observe the progression of a particular disease.
Retrospective case study methods involve looking at historical information. For example, researchers might start with an outcome, such as a disease, and then work their way backward to look at information about the individual's life to determine risk factors that may have contributed to the onset of the illness.
Where to Find Data
There are a number of different sources and methods that researchers can use to gather information about an individual or group. Six major sources that have been identified by researchers are:
- Archival records : Census records, survey records, and name lists are examples of archival records.
- Direct observation : This strategy involves observing the subject, often in a natural setting . While an individual observer is sometimes used, it is more common to utilize a group of observers.
- Documents : Letters, newspaper articles, administrative records, etc., are the types of documents often used as sources.
- Interviews : Interviews are one of the most important methods for gathering information in case studies. An interview can involve structured survey questions or more open-ended questions.
- Participant observation : When the researcher serves as a participant in events and observes the actions and outcomes, it is called participant observation.
- Physical artifacts : Tools, objects, instruments, and other artifacts are often observed during a direct observation of the subject.
Section 1: A Case History
This section will have the following structure and content:
Background information : The first section of your paper will present your client's background. Include factors such as age, gender, work, health status, family mental health history, family and social relationships, drug and alcohol history, life difficulties, goals, and coping skills and weaknesses.
Description of the presenting problem : In the next section of your case study, you will describe the problem or symptoms that the client presented with.
Describe any physical, emotional, or sensory symptoms reported by the client. Thoughts, feelings, and perceptions related to the symptoms should also be noted. Any screening or diagnostic assessments that are used should also be described in detail and all scores reported.
Your diagnosis : Provide your diagnosis and give the appropriate Diagnostic and Statistical Manual code. Explain how you reached your diagnosis, how the client's symptoms fit the diagnostic criteria for the disorder(s), or any possible difficulties in reaching a diagnosis.
Section 2: Treatment Plan
This portion of the paper will address the chosen treatment for the condition. This might also include the theoretical basis for the chosen treatment or any other evidence that might exist to support why this approach was chosen.
- Cognitive behavioral approach : Explain how a cognitive behavioral therapist would approach treatment. Offer background information on cognitive behavioral therapy and describe the treatment sessions, client response, and outcome of this type of treatment. Make note of any difficulties or successes encountered by your client during treatment.
- Humanistic approach : Describe a humanistic approach that could be used to treat your client, such as client-centered therapy . Provide information on the type of treatment you chose, the client's reaction to the treatment, and the end result of this approach. Explain why the treatment was successful or unsuccessful.
- Psychoanalytic approach : Describe how a psychoanalytic therapist would view the client's problem. Provide some background on the psychoanalytic approach and cite relevant references. Explain how psychoanalytic therapy would be used to treat the client, how the client would respond to therapy, and the effectiveness of this treatment approach.
- Pharmacological approach : If treatment primarily involves the use of medications, explain which medications were used and why. Provide background on the effectiveness of these medications and how monotherapy may compare with an approach that combines medications with therapy or other treatments.
This section of a case study should also include information about the treatment goals, process, and outcomes.
When you are writing a case study, you should also include a section where you discuss the case study itself, including the strengths and limitiations of the study. You should note how the findings of your case study might support previous research.
In your discussion section, you should also describe some of the implications of your case study. What ideas or findings might require further exploration? How might researchers go about exploring some of these questions in additional studies?
Here are a few additional pointers to keep in mind when formatting your case study:
- Never refer to the subject of your case study as "the client." Instead, their name or a pseudonym.
- Read examples of case studies to gain an idea about the style and format.
- Remember to use APA format when citing references .
A Word From Verywell
Case studies can be a useful research tool, but they need to be used wisely. In many cases, they are best utilized in situations where conducting an experiment would be difficult or impossible. They are helpful for looking at unique situations and allow researchers to gather a great deal of information about a specific individual or group of people.
If you have been directed to write a case study for a psychology course, be sure to check with your instructor for any specific guidelines that you are required to follow. If you are writing your case study for professional publication, be sure to check with the publisher for their specific guidelines for submitting a case study.
Simply Psychology. Case Study Method .
Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach . BMC Med Res Methodol . 2011 Jun 27;11:100. doi:10.1186/1471-2288-11-100
Gagnon, Yves-Chantal. The Case Study as Research Method: A Practical Handbook . Canada, Chicago Review Press Incorporated DBA Independent Pub Group, 2010.
Yin, Robert K. Case Study Research and Applications: Design and Methods . United States, SAGE Publications, 2017.
By Kendra Cherry Kendra Cherry, MS, is the author of the "Everything Psychology Book (2nd Edition)" and has written thousands of articles on diverse psychology topics. Kendra holds a Master of Science degree in education from Boise State University with a primary research interest in educational psychology and a Bachelor of Science in psychology from Idaho State University with additional coursework in substance use and case management.
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Towards Data Science
Case Study: Applying a Data Science Process Model to a Real-World Scenario
Development of a machine learning model for materials planning in the supply chain.
In today’s rapidly changing environment, one of the most critical challenges facing companies is the ability to predict future demand accurately. This is especially true for supply chain teams, where accurate demand planning is vital for maintaining customer satisfaction and keeping costs under control.
In this case study , we will explore how a data science process model can help companies tackle this challenge hands-on by leveraging statistical forecasting methods. The goal of the fictitious company was to develop a more accurate demand planning process that reduced stock-outs, increased inventory turnover, and improve overall supply chain performance.
This project is a powerful example of how data science can transform a business by unlocking new insights, increasing efficiency, and improving decision-making. I hope that this case study will help you to think about the potential applications in your organization and showcase how you can apply the process model DASC-PM successfully.
Please note that the entire article has also been published in the below publication and was written by Daniel Badura and Jonas Dieckmann : Chapter 3: “ Development of a Machine Learning Model for Materials Planning in the Supply Chain” in: Schulz et al. (2023): DASC-PM v1.1 Case Studies . Available from: https://www.researchgate.net/publication/368661660_DASC-PM_v11_Case_Studies
1. Domain and project description
SCHRAMME AG is a leading provider of dressings, band-aids, and bandages. The management thinks that there are qualitative optimization potential and savings opportunities in materials planning and the resulting production processes. Management assigns an internal project manager the task of developing a model based on machine learning to plan the materials and requirements in the supply chain. Due to negative experiences in previous data science projects, it is proposed that this project should initially be developed by using a process model.
The DASC-PM is chosen to ensure a structured and scientific process for project management. To gain an overview of the project assignment, the project manager initially works out various use cases that are then checked for suitability and feasibility. The suitable use cases then serve as the basis for figuring out the specific problems and the design of the project. This design is then checked again for suitability and feasibility.
Starting point and use case development
The company manually plans and then produces over 2,500 different products at present. In the last few quarters, they increasingly had inventory shortages for some product series, while for individual products inventories exceeded storage capacities. While the controlling department complains about rising storage costs due to imprecise planning, the demand planners lament the insufficient amount of time for the planning. For some time, the head of the supply chain has criticized the fact that the planning is done solely manually, and the opportunities of digitalization appear not to be taken advantage of.
Project goals One goal of the project is the development of a machine learning model where a large part of the product requirements should be planned automatically in the future, based on various influential factors. The demand planners should increasingly address the planning of important product groups and advertising. The system should take account of seasonality, trends, and market developments, and achieve planning accuracy of 75%. This means that the forecasts for quantities of each product should deviate from actual requirements by no more than 25%. Order histories, inventory and sales figures for customers, and internal advertising plans should be used as potential data sources.
Current team set-up Along with the inclusion of the Supply Chain department, close collaboration with Sales and IT is also expected. The planning team in the Supply Chain department now consists of a global market demand planning team that deals with long-term planning (6–18 months) based on market developments, product life cycles, and strategic focus. In individual markets, there are local customer demand planning teams that implement short-term materials and advertising planning (0–6 months) for retail through the corresponding sales channels.
The data science model to be developed should support the monthly planning cycles and quantify the need for short-term and long-term materials. The projection is then loaded into the internal planning software and should be analyzed and, if need be, supplemented or corrected. The final planning quantity will ultimately be used by the factories for production planning. To take account of the customer- and product-specific expertise, seasonality, and experiences from the past, individual team members of the planning team should be included in the project, allocating up to 20% of their working hours to it.
Suitability Check An important partial aspect during the use case selection is the suitability test. The project manager tries to examine whether the project can fundamentally be classified as feasible and whether the requirements can be carried out with the available resources. Expert interviews have shown that the problem in general is very well suited for the deployment of data science and corresponding projects have already been undertaken externally and also published. The data science team confirmed that there are a sufficient number of potentially suitable methods for this project and the required data sources are available.
Finally, the project manager analyzes feasibility. It is necessary to coordinate with the IT department to check the available infrastructure and the expertise of the involved employees. The available cloud infrastructure from Microsoft and the experience of the data science team withDatabricks software make the project appear fundamentally achievable. The project risk is classified as moderate in general since the planers assume a major role as controllers in the implementation phase and the results are checked.
Project design
Based on the problem and specific aspects of the domains, the project manager, the head of the supply chain, and a data scientist are now responsible for formally designing the project.
The project objective is assumed to be an improvement in planning accuracy and a reduction in the manual processes and is tied to the aim of developing an appropriate model for the project. According to an initial estimate, the cost framework totals EUR 650,000. A period of six months is proposed as the timeframe for the development, with an additional six months planned for process integration.
Since full planning and a description of the course of projects in the data science context are usually not possible in contrast to many other projects, the project manager solely prepares a project outline for this process with the basic cornerstones that were already indicated in the previous sections. The budget includes financial resources for 1 full-time project manager, 2 full-time data scientists, and 0.5 full-time data engineers. As already mentioned, the demand planners should allocate roughly 20% of the working hours to share their expertise and experience.
The project as a whole should be handled with an agile working method and based on the DASC-PM phases according to the Scrum methodology. The work is done iteratively in the areas of data procurement, analysis, utilization, and use, with the preceding and following phase moving into focus in each phase. The back-steps are especially important if gaps or problems are found in key areas and can only be solved by returning to the previous phase. The project outline is prepared visually and placed in a very visible area of the SCHRAMME AG office for all participants. Then the entire project description is checked for suitability and feasibility once again until the process moves on to the next phase.
2. Data provision
Data preparation.
SCHRAMME AG has several data sources that can be included in automatic planning. Besides the historical sales data from the ERP system, order histories and customer data from the CRM system are options, along with inventories and marketing measures. Azure Data Factory is used to prepare a cloud-based pipeline that loads, transforms, and integrates the data from various source systems. The primary basis for the automatic forecasts should be the order histories: The remaining data is used either as background information for the planning teams or to carry out cluster analyses in advance if need be. In the initial phase of the project, the individual data sources still exhibit big differences regarding quality and structure. That is why adjustments are made together with the IT and technical departments to prepare the forecasts later on a solid basis.
Data management
The data management process is automated by data engineers and done according to a daily schedule to always remain up to date. To keep the complexity reasonable, the most promising data sources are initially processed and the pipeline is then incrementally expanded with Continuous Integration / Continuous Deployment (CI/CD). After deployment, the processed data are stored in Azure Data Lake Storage where they can be used for future analysis with Azure Databricks. DataLake also stores the backups of the prepared data and analysis results as well as other data such as protocols, quality metrics, and credential structures. Writing and reading authorizations as well as plan versions also ensure that only the latest planning period can be processed so that the values from the past no longer change.
Exploratory data analysis
An important step in data preparation is the exploratory data analysis (EDA) where various statistics and visualizations are produced to start with. This results in an overview of the distributions, outliers, and correlations in the data. The results of the EDA provide insights into characteristics to be considered for the next phase of the analysis. In the second step, Feature Selection and Feature Engineering are used to select the relevant characteristics or produce new features. A dimension reduction method such as a principal component analysis is applied for data with high dimensionality. The EDA provides information about the existing demand histories of SCHRAMMEAG.
3. Analysis
Identification of suitable analysis methods.
The feasibility test at the beginning of the project made it clear that this project can and should be solved with data science methods. The two data science employees involved initially provide an overview of the existing methods that are well suited for the existing problem. This existing problem is part of the regression problem class in the supervised learning algorithms. Fundamentally, this is a type of time series analysis that can be expanded by additional factors or multiple regression.
In connection with the key area of scientificity, the latest developments in research on comparable problems were examined. This showed that XGBoost, ARIMA, FacebookProphet, and LightGBM are frequently named methods for the problem class. A data scientist documents the corresponding advantages and disadvantages of each method and sorts them according to the complexity and computational intensity. To receive the first indications on the model ability for products from SCHRAMME AG, simpler models are initially selected by the project team, which then adopts the classical exponential smoothing and ARIMA model family.
Application of analysis methods
Since multiple users are involved in the analysis process for this project, the team initially relies on a suitable notebook-based development environment in Databricks. Along the typical machine learning workflow, the code for the import and data cleaning is initially implemented. To ensure validity, the underlying dataset is ultimately divided into training, validation, and test data by cross-validation. The selected methods are then applied to training and validation datasets to optimize the model. In this context, attempts are also repeatedly made to optimize the parameters of processes and sensibly reduce the number of available dimensions, if need be. The data scientists at SCHRAMME AG document the execution and validation results of the individual runs. The ARIMA family models fundamentally exhibit a better performance relative to the exponential smoothing, even if the target accuracy of 75% still cannot be achieved with a currently resulting value of 62.4%. The RMSE and MAPE metrics also show potential for optimization.
The parameter configurations and the basis for selecting the final model after the first application iteration are documented and prepared for the project manager and the head of the supply chain in a technically understandable way. What is seen in particular, is that some product groups have very unusual seasonality and certain products are generally very difficult to predict. Even if the product portfolio of SCHRAMME AG is affected somewhat less due to temporary closures (lockdowns) during the corona pandemic, a slight decline in demand for dressing products has been observed. It is assumed that less activity and transport, as well as fewer accidents and injuries, account for this drop.
The trend can be modeled quite well in the analysis method used. To improve the target accuracy, technically more complex methods are used in another experiment, with these methods proving to be relevant and applicable in the context of identifying suitable methods. After some iterations to optimize parameters and cross-validate, the Prophet and XGBoost methods demonstrated the highest validation results at 73.4% and 65.8%, respectively.
The data scientists consider Prophet to be the most suitable method among the applied processes and determine the planning accuracy relative to the test time series. Even if the accuracy is slightly below the target value of 73.4%, a significant improvement in planning accuracy is achieved. The MAPE is at 16.64% and the RMSE at 8,130, which implies a less absolute deviation in comparison to the RMSE in the XGBoost method (10,134). Similar to the first experiment, however, there are product groups that are very difficult to predict overall (37.2%) and negatively impact the cumulative accuracy.
The results of the analyses are used as the basis for a logical evaluation and classification by the head of the supply chain and the analysts, which is organized and moderated by the project manager. The adopted metrics for evaluation are the cumulative planning accuracy of all products defined in advance together with the common RMSE and MAPE metrics. The department needs to have a realistic, trackable, and reliable basis for determining requirements on the product level.
The benchmark for planning accuracy is assumed to be the current (manually planned) median accuracy of 58% over the last two years. The evaluation of results shows that many product groups overall can be planned with a high degree of accuracy by using the data science model and vastly exceed the benchmark. However, there are also product groups that reflect similar accuracy concerning manual planning. It is necessary to discuss above all the product area of drainage, which sees much worse results with the model than in the manual planning and appears to be unsuitable for a statistical calculation of requirements with the methods used to date.
From a technical perspective, the head of the supply chain believes that it makes little sense to plan such product groups statistically since only limited planning accuracy is possible due to their specific seasonal and trend-based characteristics. She recommends the introduction of an error threshold value on a product basis to determine which products should be predicted with the model and which product groups will be removed from the modeling and still planned manually. A range slightly below the current benchmark seems to be a suitable threshold value since nearly as good accuracy with a less manual effort from the perspective of the department is always an improvement on the way to achieving the project objective. The project leader documents the results of the evaluation with the decisions and measures adopted.
The required quantities of all selected products for the next 18 months can be documented as the analysis result after the first real modeling. This can now be utilized and integrated into the planning process of the teams.
4. Deployment
The team now enters the utilization phase of the DASC-PM for integration.
Technical-methodological preparation
It is possible to rely on the existing infrastructure for utilization. The forecasts are loaded in the planning software IBM Planning Analytics where they are tested and reprocessed. The so-called TurboIntegrator is used to automate the loading process that represents a central component of IBM Planning Analytics. The OLAP structure of Planning Analytics allows for the creation of flexible views where the users can personally choose their context (time reference, product groups, etc.)and adjust calculations in real-time. Furthermore, the reporting software QlikSense is also integrated for more in-depth analyses. Here, the components of the time series (trends, seasonality, noise) can be visualized on the one hand and additional information such as outliers and median values can be displayed on the other hand. The final plans are loaded into the Data Lake after processing by the planning teams so they can be referenced in the future.
Ensuring technical feasibility
The forecasts themselves are automatically regenerated at the beginning of the month. The planners can make their corrections during the first four working days of the month and view the results in the planning system in real-time. Since the algorithms work in a cloud environment, the computing power can be scaled, if need be. To get all processes to run automatically, changes in the data sources should be minimized. If there is a need for adjustment, the data engineer will be informed, and the interface document will be updated by recording all the information on data sources and connections. The planning and forecasting system is a mixture of the cloud (Microsoft Azure) and an on-premise system (Planning Analytics), with the planners only having active access to the on-premise structures. Credentials are awarded here so the local planners only have access to their areas, while the global planners can view all topics. After the end of the development phase, the support services are mainly handled by the IT department. In the case of complex problems, data scientists or data engineers are also consulted.
Ensuring applicability
Users of the solution are the local and global planning teams. Since members of the teams have less of a technical orientation, training sessions are held to help them interpret the forecasts and classify their quality. The user interface is also designed with a focus on clarity and understandability. Simple line and bar charts for processes and benchmarks are used, along with tables reduced to what is most important. The users are included in the development from the beginning to ensure technical correctness and relevance and to ensure familiarity with the solution before the end of the development phase. In addition, complete documentation is drafted. The technical part of the documentation mostly builds on the interface document by demonstrating the data structures and connections, while the content part is jointly prepared with the users.
Technical preparation
To ensure that the new solution does not lose relevance or quality after a few months, work continues to be done on improvements after the completion of the first development phase, even if substantially less time is spent on it. The most important aspect of the ongoing improvement is the constant automated adjustment of the prediction model to new data. Other parts of the system still requiring manual work at the beginning are also automated over time. A change in various parameters such as the forecast horizon or threshold values for the accuracy of the prediction can be made by the planners themselves in Planning Analytics, with the model remaining flexible. Problems occurring after the release of the first version are entered via the IT ticket system and assigned to the data science area. At regular intervals, it is also checked whether the model still satisfies the expectations of the company or whether changes are necessary.
5. (Application) Use and summary
The transition to the use of the developed model means that the Data Science Process Model(DASC-PM) enters its last phase. As a whole, SCHRAMME AG was able to achieve the objectives it had set in the supply chain area by using a structured and holistic approach. Additional or new projects can now be derived from here. The planning processes were largely automated and supported by machine learning algorithms. The relevant stakeholders in management, finance, and the supply chain were highly satisfied. After initial skepticism, the planning team itself is now also convinced by the reduction in workload and possible prioritization. However, it is also conceivable that weak points will surface during use and more iterations will be required in later phases.
The case study as a whole showed that non-linear process models in particular are advantageous for the area of data science. The DASC-PM is a suitable novel process that can be transferred to numerous other domains and problems.
In conclusion, data science plays an integral role in solving complex business problems by identifying hidden patterns and extracting actionable insights from data. Through this case study, we demonstrated how data science techniques can be used to develop predictive models to help businesses make informed decisions e.g., in the supply chain.
While this case study focuses on demand planning, the process model can be used in various ways, such as for building personalized recommendations on e-commerce websites, identifying fraud in financial transactions, or predicting customer churn in telecom or subscription-based businesses.
However, it’s essential to note that real-world data science projects pose several challenges, such as data quality issues, lack of domain expertise, and inadequate communication between stakeholders. In comparison, fictitious case studies provide an idealized environment with clean, well-labeled data and well-defined problem statements. Thus, real-world projects require a pragmatic approach that takes into account various factors such as business objectives, data quality, computational resources, and ethical considerations. I am pretty sure you know this from your own experience. Do not underestimate reality!
In summary, data science has immense potential to transform industries, and society and create new opportunities for businesses. The DASC-DM (or any) process model can help to structure the approach logically to ensure clear guidance for both, business stakeholders as well as the project team itself.
Please let me know about your experience with data science projects. How do you structure them & what are the biggest challenges? Feel free to leave a comment!
I hope you find it useful. Let me know your thoughts! And feel free to connect on LinkedIn at https://www.linkedin.com/in/jonas-dieckmann/ and/or to follow me here on medium.
The whole case study has been published in:
[1] Schulz et al. (2023): “ DASC-PM v1.1 Case Studies” Available from: https://www.researchgate.net/publication/368661660_DASC-PM_v11_Case_Studies
Process images have been taken from:
[2] Schulz et al. (2022): “ DASC-PM v1.1 — A Process Model for Data Science Projects ” (2022), Publisher: NORDAKADEMIE gAG Hochschule der Wirtschaft, ISBN: 978–3–00–064898–4, DOI: 10.25673/32872.2
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All You Wanted to Know About How to Write a Case Study
What do you study in your college? If you are a psychology, sociology, or anthropology student, we bet you might be familiar with what a case study is. This research method is used to study a certain person, group, or situation. In this guide from our dissertation writing service , you will learn how to write a case study professionally, from researching to citing sources properly. Also, we will explore different types of case studies and show you examples — so that you won’t have any other questions left.
What Is a Case Study?
A case study is a subcategory of research design which investigates problems and offers solutions. Case studies can range from academic research studies to corporate promotional tools trying to sell an idea—their scope is quite vast.
What Is the Difference Between a Research Paper and a Case Study?
While research papers turn the reader’s attention to a certain problem, case studies go even further. Case study guidelines require students to pay attention to details, examining issues closely and in-depth using different research methods. For example, case studies may be used to examine court cases if you study Law, or a patient's health history if you study Medicine. Case studies are also used in Marketing, which are thorough, empirically supported analysis of a good or service's performance. Well-designed case studies can be valuable for prospective customers as they can identify and solve the potential customers pain point.
Case studies involve a lot of storytelling – they usually examine particular cases for a person or a group of people. This method of research is very helpful, as it is very practical and can give a lot of hands-on information. Most commonly, the length of the case study is about 500-900 words, which is much less than the length of an average research paper.
The structure of a case study is very similar to storytelling. It has a protagonist or main character, which in your case is actually a problem you are trying to solve. You can use the system of 3 Acts to make it a compelling story. It should have an introduction, rising action, a climax where transformation occurs, falling action, and a solution.
Here is a rough formula for you to use in your case study:
Problem (Act I): > Solution (Act II) > Result (Act III) > Conclusion.
Types of Case Studies
The purpose of a case study is to provide detailed reports on an event, an institution, a place, future customers, or pretty much anything. There are a few common types of case study, but the type depends on the topic. The following are the most common domains where case studies are needed:
- Historical case studies are great to learn from. Historical events have a multitude of source info offering different perspectives. There are always modern parallels where these perspectives can be applied, compared, and thoroughly analyzed.
- Problem-oriented case studies are usually used for solving problems. These are often assigned as theoretical situations where you need to immerse yourself in the situation to examine it. Imagine you’re working for a startup and you’ve just noticed a significant flaw in your product’s design. Before taking it to the senior manager, you want to do a comprehensive study on the issue and provide solutions. On a greater scale, problem-oriented case studies are a vital part of relevant socio-economic discussions.
- Cumulative case studies collect information and offer comparisons. In business, case studies are often used to tell people about the value of a product.
- Critical case studies explore the causes and effects of a certain case.
- Illustrative case studies describe certain events, investigating outcomes and lessons learned.
Case Study Format
The case study format is typically made up of eight parts:
- Executive Summary. Explain what you will examine in the case study. Write an overview of the field you’re researching. Make a thesis statement and sum up the results of your observation in a maximum of 2 sentences.
- Background. Provide background information and the most relevant facts. Isolate the issues.
- Case Evaluation. Isolate the sections of the study you want to focus on. In it, explain why something is working or is not working.
- Proposed Solutions. Offer realistic ways to solve what isn’t working or how to improve its current condition. Explain why these solutions work by offering testable evidence.
- Conclusion. Summarize the main points from the case evaluations and proposed solutions. 6. Recommendations. Talk about the strategy that you should choose. Explain why this choice is the most appropriate.
- Implementation. Explain how to put the specific strategies into action.
- References. Provide all the citations.
How to Write a Case Study
Let's discover how to write a case study.
Setting Up the Research
When writing a case study, remember that research should always come first. Reading many different sources and analyzing other points of view will help you come up with more creative solutions. You can also conduct an actual interview to thoroughly investigate the customer story that you'll need for your case study. Including all of the necessary research, writing a case study may take some time. The research process involves doing the following:
- Define your objective. Explain the reason why you’re presenting your subject. Figure out where you will feature your case study; whether it is written, on video, shown as an infographic, streamed as a podcast, etc.
- Determine who will be the right candidate for your case study. Get permission, quotes, and other features that will make your case study effective. Get in touch with your candidate to see if they approve of being part of your work. Study that candidate’s situation and note down what caused it.
- Identify which various consequences could result from the situation. Follow these guidelines on how to start a case study: surf the net to find some general information you might find useful.
- Make a list of credible sources and examine them. Seek out important facts and highlight problems. Always write down your ideas and make sure to brainstorm.
- Focus on several key issues – why they exist, and how they impact your research subject. Think of several unique solutions. Draw from class discussions, readings, and personal experience. When writing a case study, focus on the best solution and explore it in depth. After having all your research in place, writing a case study will be easy. You may first want to check the rubric and criteria of your assignment for the correct case study structure.
Read Also: 'CREDIBLE SOURCES: WHAT ARE THEY?'
Although your instructor might be looking at slightly different criteria, every case study rubric essentially has the same standards. Your professor will want you to exhibit 8 different outcomes:
- Correctly identify the concepts, theories, and practices in the discipline.
- Identify the relevant theories and principles associated with the particular study.
- Evaluate legal and ethical principles and apply them to your decision-making.
- Recognize the global importance and contribution of your case.
- Construct a coherent summary and explanation of the study.
- Demonstrate analytical and critical-thinking skills.
- Explain the interrelationships between the environment and nature.
- Integrate theory and practice of the discipline within the analysis.
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Case Study Outline
Let's look at the structure of an outline based on the issue of the alcoholic addiction of 30 people.
Introduction
- Statement of the issue: Alcoholism is a disease rather than a weakness of character.
- Presentation of the problem: Alcoholism is affecting more than 14 million people in the USA, which makes it the third most common mental illness there.
- Explanation of the terms: In the past, alcoholism was commonly referred to as alcohol dependence or alcohol addiction. Alcoholism is now the more severe stage of this addiction in the disorder spectrum.
- Hypotheses: Drinking in excess can lead to the use of other drugs.
- Importance of your story: How the information you present can help people with their addictions.
- Background of the story: Include an explanation of why you chose this topic.
- Presentation of analysis and data: Describe the criteria for choosing 30 candidates, the structure of the interview, and the outcomes.
- Strong argument 1: ex. X% of candidates dealing with anxiety and depression...
- Strong argument 2: ex. X amount of people started drinking by their mid-teens.
- Strong argument 3: ex. X% of respondents’ parents had issues with alcohol.
- Concluding statement: I have researched if alcoholism is a disease and found out that…
- Recommendations: Ways and actions for preventing alcohol use.
Writing a Case Study Draft
After you’ve done your case study research and written the outline, it’s time to focus on the draft. In a draft, you have to develop and write your case study by using: the data which you collected throughout the research, interviews, and the analysis processes that were undertaken. Follow these rules for the draft:
- Your draft should contain at least 4 sections: an introduction; a body where you should include background information, an explanation of why you decided to do this case study, and a presentation of your main findings; a conclusion where you present data; and references.
- In the introduction, you should set the pace very clearly. You can even raise a question or quote someone you interviewed in the research phase. It must provide adequate background information on the topic. The background may include analyses of previous studies on your topic. Include the aim of your case here as well. Think of it as a thesis statement. The aim must describe the purpose of your work—presenting the issues that you want to tackle. Include background information, such as photos or videos you used when doing the research.
- Describe your unique research process, whether it was through interviews, observations, academic journals, etc. The next point includes providing the results of your research. Tell the audience what you found out. Why is this important, and what could be learned from it? Discuss the real implications of the problem and its significance in the world.
- Include quotes and data (such as findings, percentages, and awards). This will add a personal touch and better credibility to the case you present. Explain what results you find during your interviews in regards to the problem and how it developed. Also, write about solutions which have already been proposed by other people who have already written about this case.
- At the end of your case study, you should offer possible solutions, but don’t worry about solving them yourself.
Use Data to Illustrate Key Points in Your Case Study
Even though your case study is a story, it should be based on evidence. Use as much data as possible to illustrate your point. Without the right data, your case study may appear weak and the readers may not be able to relate to your issue as much as they should. Let's see the examples from essay writing service :
With data: Alcoholism is affecting more than 14 million people in the USA, which makes it the third most common mental illness there. Without data: A lot of people suffer from alcoholism in the United States.
Try to include as many credible sources as possible. You may have terms or sources that could be hard for other cultures to understand. If this is the case, you should include them in the appendix or Notes for the Instructor or Professor.
Finalizing the Draft: Checklist
After you finish drafting your case study, polish it up by answering these ‘ask yourself’ questions and think about how to end your case study:
- Check that you follow the correct case study format, also in regards to text formatting.
- Check that your work is consistent with its referencing and citation style.
- Micro-editing — check for grammar and spelling issues.
- Macro-editing — does ‘the big picture’ come across to the reader? Is there enough raw data, such as real-life examples or personal experiences? Have you made your data collection process completely transparent? Does your analysis provide a clear conclusion, allowing for further research and practice?
Problems to avoid:
- Overgeneralization – Do not go into further research that deviates from the main problem.
- Failure to Document Limitations – Just as you have to clearly state the limitations of a general research study, you must describe the specific limitations inherent in the subject of analysis.
- Failure to Extrapolate All Possible Implications – Just as you don't want to over-generalize from your case study findings, you also have to be thorough in the consideration of all possible outcomes or recommendations derived from your findings.
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How to Create a Title Page and Cite a Case Study
Let's see how to create an awesome title page.
Your title page depends on the prescribed citation format. The title page should include:
- A title that attracts some attention and describes your study
- The title should have the words “case study” in it
- The title should range between 5-9 words in length
- Your name and contact information
- Your finished paper should be only 500 to 1,500 words in length. With this type of assignment, write effectively and avoid fluff.
Here is a template for the APA and MLA format title page:
There are some cases when you need to cite someone else's study in your own one – therefore, you need to master how to cite a case study. A case study is like a research paper when it comes to citations. You can cite it like you cite a book, depending on what style you need.
Citation Example in MLA Hill, Linda, Tarun Khanna, and Emily A. Stecker. HCL Technologies. Boston: Harvard Business Publishing, 2008. Print.
Citation Example in APA Hill, L., Khanna, T., & Stecker, E. A. (2008). HCL Technologies. Boston: Harvard Business Publishing.
Citation Example in Chicago Hill, Linda, Tarun Khanna, and Emily A. Stecker. HCL Technologies.
Case Study Examples
To give you an idea of a professional case study example, we gathered and linked some below.
Eastman Kodak Case Study
Case Study Example: Audi Trains Mexican Autoworkers in Germany
To conclude, a case study is one of the best methods of getting an overview of what happened to a person, a group, or a situation in practice. It allows you to have an in-depth glance at the real-life problems that businesses, healthcare industry, criminal justice, etc. may face. This insight helps us look at such situations in a different light. This is because we see scenarios that we otherwise would not, without necessarily being there. If you need custom essays , try our research paper writing services .
Get Help Form Qualified Writers
Crafting a case study is not easy. You might want to write one of high quality, but you don’t have the time or expertise. If you’re having trouble with your case study, help with essay request - we'll help. EssayPro writers have read and written countless case studies and are experts in endless disciplines. Request essay writing, editing, or proofreading assistance from our writing service, and all of your worries will be gone.
Don't Know Where to Start?
Crafting a case study is not easy. You might want to write one of high quality, but you don’t have the time or expertise. Request essay writing, editing, or proofreading assistance from our writing service.
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15+ Professional Case Study Examples [Design Tips + Templates]
By Alice Corner , Jan 12, 2023
Let me ask you a question: Have you ever bought something — within the last 10 years or so — without reading its reviews or without a recommendation or prior experience of using it?
If the answer is no — or at least, rarely — you get my point.
For businesses selling consumer goods, having raving reviews is a good way to get more customers. The same thing applies to B2B and/or SaaS businesses — but for this type of business, besides regular, short reviews, having a detailed case study can help tremendously.
Case studies are an incredibly effective form of marketing that you can use to help promote your product and plan your marketing strategy effectively. You can also use it as a form of customer analysis or as a sales tool to inspire potential customers.
So what does a case study look like and how can you create one? In this article, I’m going to list over 15 marketing case study examples, case study tips, and case study templates to help you create a case study that converts.
Click to jump ahead:
- What is a Case Study?
- Marketing Case Study Examples
Sales Case Study Examples
Simple case study examples, business case study examples.
- Case Study FAQs
What is a case study?
A case study is a research method to gain a better understanding of a subject or process. Case studies involve in-depth research into a given subject, in order to understand its functionality and successes.
In the context of a business, however, case studies take customer success stories and explore how they use your product to help them achieve their business goals.
As well as being valuable marketing tools, case studies are a good way to evaluate your product as it allows you to objectively examine how others are using it.
It’s also a good way to interview your customers about why they work with you.
Related: What is a Case Study? [+6 Types of Case Studies]
What is a marketing case study?
A marketing case study is a type of marketing where you use your existing customers as an example of what your product or services can achieve. You can also create case studies of internal, successful marketing projects.
Here’s an example of a marketing case study template:
Return to Table of Contents
Marketing case study examples
Marketing case studies are incredibly useful for showing your marketing successes. Every successful marketing campaign relies on influencing a consumer’s behavior, and a great case study can be a great way to spotlight your biggest wins.
In the marketing case study examples below, a variety of designs and techniques to create impactful and effective case studies.
Show off impressive results with a bold marketing case study
Case studies are meant to show off your successes, so make sure you feature your positive results prominently. Using bold and bright colors as well as contrasting shapes, large bold fonts, and simple icons is a great way to highlight your wins.
In well-written case study examples like the one below, the big wins are highlighted on the second page with a bright orange color and are highlighted in circles.
Making the important data stand out is especially important when attracting a prospective customer with marketing case studies.
Use a simple but clear layout in your case study
Using a simple layout in your case study can be incredibly effective, like in the example of a case study below.
Keeping a clean white background, and using slim lines to help separate the sections is an easy way to format your case study.
Making the information clear helps draw attention to the important results, and it helps improve the accessibility of the design .
Business case study examples like this would sit nicely within a larger report, with a consistent layout throughout.
Use visuals and icons to create an engaging and branded business case study
Nobody wants to read pages and pages of text — and that’s why Venngage wants to help you communicate your ideas visually.
Using icons, graphics, photos, or patterns helps create a much more engaging design.
With this Blue Cap case study icons, colors, and impactful pattern designs have been used to create an engaging design that catches your eye.
Use a monochromatic color palette to create a professional and clean case study
Let your research shine by using a monochromatic and minimalistic color palette.
By sticking to one color, and leaving lots of blank space you can ensure your design doesn’t distract a potential customer from your case study content.
In this case study on Polygon Media, the design is simple and professional, and the layout allows the prospective customer to follow the flow of information.
The gradient effect on the left-hand column helps break up the white background and adds an interesting visual effect.
Did you know you can generate an accessible color palette with Venngage? Try our free accessible color palette generator today and create a case study that delivers and looks pleasant to the eye:
Add long term goals in your case study
When creating a case study it’s a great idea to look at both the short term and the long term goals of the company to gain the best understanding possible of the insights they provide.
Short-term goals will be what the company or person hopes to achieve in the next few months, and long-term goals are what the company hopes to achieve in the next few years.
Check out this modern pattern design example of a case study below:
In this case study example, the short and long-term goals are clearly distinguished by light blue boxes and placed side by side so that they are easy to compare.
Use a strong introductory paragraph to outline the overall strategy and goals before outlining the specific short-term and long-term goals to help with clarity.
This strategy can also be handy when creating a consulting case study.
Use data to make concrete points about your sales and successes
When conducting any sort of research stats, facts, and figures are like gold dust (aka, really valuable).
Being able to quantify your findings is important to help understand the information fully. Saying sales increased 10% is much more effective than saying sales increased.
In sales case study examples, like this one, the key data and findings can be presented with icons. This contributes to the potential customer’s better understanding of the report.
They can clearly comprehend the information and it shows that the case study has been well researched.
Use emotive, persuasive, or action based language in your marketing case study
Create a compelling case study by using emotive, persuasive and action-based language when customizing your case study template.
In this well-written case study example, we can see that phrases such as “Results that Speak Volumes” and “Drive Sales” have been used.
Using persuasive language like you would in a blog post. It helps inspire potential customers to take action now.
Keep your potential customers in mind when creating a customer case study for marketing
82% of marketers use case studies in their marketing because it’s such an effective tool to help quickly gain customers’ trust and to showcase the potential of your product.
Why are case studies such an important tool in content marketing?
By writing a case study you’re telling potential customers that they can trust you because you’re showing them that other people do.
Not only that, but if you have a SaaS product, business case studies are a great way to show how other people are effectively using your product in their company.
In this case study, Network is demonstrating how their product has been used by Vortex Co. with great success; instantly showing other potential customers that their tool works and is worth using.
Related: 10+ Case Study Infographic Templates That Convert
Case studies are particularly effective as a sales technique.
A sales case study is like an extended customer testimonial, not only sharing opinions of your product – but showcasing the results you helped your customer achieve.
Make impactful statistics pop in your sales case study
Writing a case study doesn’t mean using text as the only medium for sharing results.
You should use icons to highlight areas of your research that are particularly interesting or relevant, like in this example of a case study:
Icons are a great way to help summarize information quickly and can act as visual cues to help draw the customer’s attention to certain areas of the page.
In some of the business case study examples above, icons are used to represent the impressive areas of growth and are presented in a way that grabs your attention.
Use high contrast shapes and colors to draw attention to key information in your sales case study
Help the key information stand out within your case study by using high contrast shapes and colors.
Use a complementary or contrasting color, or use a shape such as a rectangle or a circle for maximum impact.
This design has used dark blue rectangles to help separate the information and make it easier to read.
Coupled with icons and strong statistics, this information stands out on the page and is easily digestible and retainable for a potential customer.
Less is often more, and this is especially true when it comes to creating designs. Whilst you want to create a professional-looking, well-written and design case study – there’s no need to overcomplicate things.
These simple case study examples show that smart clean designs and informative content can be an effective way to showcase your successes.
Use colors and fonts to create a professional-looking case study
Business case studies shouldn’t be boring. In fact, they should be beautifully and professionally designed.
This means the normal rules of design apply. Use fonts, colors, and icons to create an interesting and visually appealing case study.
In this case study example, we can see how multiple fonts have been used to help differentiate between the headers and content, as well as complementary colors and eye-catching icons.
Whether you’re a B2B or B2C company, business case studies can be a powerful resource to help with your sales, marketing, and even internal departmental awareness.
Business and business management case studies should encompass strategic insights alongside anecdotal and qualitative findings, like in the business case study examples below.
Conduct a B2B case study by researching the company holistically
When it comes to writing a case study, make sure you approach the company holistically and analyze everything from their social media to their sales.
Think about every avenue your product or service has been of use to your case study company, and ask them about the impact this has had on their wider company goals.
In business case study examples like the one above, we can see that the company has been thought about holistically simply by the use of icons.
By combining social media icons with icons that show in-person communication we know that this is a well-researched and thorough case study.
This case study report example could also be used within an annual or end-of-year report.
Highlight the key takeaway from your marketing case study
To create a compelling case study, identify the key takeaways from your research. Use catchy language to sum up this information in a sentence, and present this sentence at the top of your page.
This is “at a glance” information and it allows people to gain a top-level understanding of the content immediately.
You can use a large, bold, contrasting font to help this information stand out from the page and provide interest.
Learn how to choose fonts effectively with our Venngage guide and once you’ve done that.
Upload your fonts and brand colors to Venngage using the My Brand Kit tool and see them automatically applied to your designs.
The heading is the ideal place to put the most impactful information, as this is the first thing that people will read.
In this example, the stat of “Increase[d] lead quality by 90%” is used as the header. It makes customers want to read more to find out how exactly lead quality was increased by such a massive amount.
If you’re conducting an in-person interview, you could highlight a direct quote or insight provided by your interview subject.
Pick out a catchy sentence or phrase, or the key piece of information your interview subject provided and use that as a way to draw a potential customer in.
Use charts to visualize data in your business case studies
Charts are an excellent way to visualize data and to bring statistics and information to life. Charts make information easier to understand and to illustrate trends or patterns.
Making charts is even easier with Venngage.
In this consulting case study example, we can see that a chart has been used to demonstrate the difference in lead value within the Lead Elves case study.
Adding a chart here helps break up the information and add visual value to the case study.
Using charts in your case study can also be useful if you’re creating a project management case study.
You could use a Gantt chart or a project timeline to show how you have managed the project successfully.
Use direct quotes to build trust in your marketing case study
To add an extra layer of authenticity you can include a direct quote from your customer within your case study.
According to research from Nielsen , 92% of people will trust a recommendation from a peer and 70% trust recommendations even if they’re from somebody they don’t know.
So if you have a customer or client who can’t stop singing your praises, make sure you get a direct quote from them and include it in your case study.
You can either lift part of the conversation or interview, or you can specifically request a quote. Make sure to ask for permission before using the quote.
This design uses a bright contrasting speech bubble to show that it includes a direct quote, and helps the quote stand out from the rest of the text.
This will help draw the customer’s attention directly to the quote, in turn influencing them to use your product or service.
Case Study Examples Summary
Once you have created your case study, it’s best practice to update your examples on a regular basis to include up-to-date statistics, data, and information.
You should update your business case study examples often if you are sharing them on your website.
It’s also important that your case study sits within your brand guidelines – find out how Venngage’s My Brand Kit tool can help you create consistently branded case study templates.
Case studies are important marketing tools – but they shouldn’t be the only tool in your toolbox. Content marketing is also a valuable way to earn consumer trust.
Case Study FAQ
Why should you write a case study.
Case studies are an effective marketing technique to engage potential customers and help build trust.
By producing case studies featuring your current clients or customers, you are showcasing how your tool or product can be used. You’re also showing that other people endorse your product.
In addition to being a good way to gather positive testimonials from existing customers, business case studies are good educational resources and can be shared amongst your company or team, and used as a reference for future projects.
How should you write a case study?
To create a great case study, you should think strategically. The first step, before starting your case study research, is to think about what you aim to learn or what you aim to prove.
You might be aiming to learn how a company makes sales or develops a new product. If this is the case, base your questions around this.
You can learn more about writing a case study from our extensive guide.
Some good questions you could ask would be:
- Why do you use our tool or service?
- How often do you use our tool or service?
- What does the process of using our product look like to you?
- If our product didn’t exist, what would you be doing instead?
- What is the number one benefit you’ve found from using our tool?
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Process Modeling in ’23: Top 5 Use Cases & Case Studies
What is business process modeling?
1. increase process transparency , 2. ensure process standardization and optimization , 3. facilitate employee collaboration, 4. discover process automation opportunities, 5. allocating process resources, further reading.
Process management allows companies to improve their processes so that they can enhance their process efficiency and customer satisfaction while decreasing cost. Yet, business analysts often do not know every activity and steps involved in processes despite interviewing with employees who directly involved in the processes. Business process modeling which is a data-driven method used under business process management can help overcome this challenge. Process modeling enables analysts to discover, visualize, analyze, and improve business processes while estimating the success of a modification to a business strategy.
This article explains process modeling and its top five business use cases.
Process modeling is the practice of visualizing business processes and workflows. By including every individual step, process models provide an end-to-end overview of the tasks and activities in business processes. Process modeling reveals insights about:
- Events and activities in a workflow
- The people involved in these activities and events
- Decision points together with the paths and outcomes
- Systems and devices used in the process
- Success and failure rates
The graphical representation of the processes facilitates business leaders and analysts to inspect and improve process efficiency accordingly.
The advantages process modeling offers to include:
Process modeling helps understand how processes function with all steps and identify the factors that bring loops, repetitive works or errors, and the elements that bring efficiency and success.
HSA Bank 1 benefited from process modeling to understand and analyze their processes. The bank detected several tasks to simplify and clarify during the modelling, which improved their case resolution by 75%.
Process modeling helps organizations understand internal procedures, rules and standards to align other processes that do not follow the required structure. Business leaders can optimize and standardize these processes based on their insights.
Cofco International 1 , one of China’s largest food and agriculture companies, applied process modeling to visualize and understand their compliance with the country-based laws and grain standards across different countries. The company traced and updated its processes with process modelling to ensure compliance and optimization.
Since process modeling allows businesses to visualize and understand actual processes, business leaders develop more accurate business strategies and communicate with employees based on the process graphs. As a result, process modeling streamlines the coordination of systems, people and information in the organization.
Westpac New Zealand Ltd. leveraged a process management solution to model and document their processes. The bank had a task document repository, into which staff members had to email the documents for storage. Therefore, they stored the documented processes in three months and created more than 2000 reusable artefacts. Over 130 employees use these documents and collaborate through them in new projects.
IBM allows their customers to combine IBM BlueWorks Live (BWL) and Process Management solutions with IBM Process Mining . Users can upload a process model they generate with these tools to process mining and compare it with the process discovered by the process mining tool or vice versa.
Process modeling facilitates process automation as it enables business leaders and analysts to view and discover points and tasks that can benefit from automation.
The multinational printer and copier manufacturer Kyocera 1 captured their pricing approval processes with process modeling. By better understanding their processes, they detected several processes that can benefit from automation. That reduced the approval time by 85%. As employees allocate only 20 minutes per approval, they focus on other tasks, which improves overall efficiency.
Process modeling indicates the involvement of people in certain tasks or the usage of tools, devices and systems within a workflow. Therefore, businesses can leverage the modeling to determine if their resource and monetary investments generate expected returns.
One example would be that the manufacturers can understand their machinery usage in their production processes. Process modeling can show which machinery is utilized less and is utilized more frequently. Based on the insight, manufacturers can decide to re-allocate the work across the tools or disinvest in the machinery that is not helpful for their business to save money.
If you are interested in process improvement and process discovery, you can check out our relevant articles:
- Process Improvement in 2022: In-depth guide for businesses
- Process Discovery in 2021: What it is & How it works
If you are interested in process mining solutions for process improvement but want to know more, download our comprehensive guide and learn it all at once:
If you want to use business modeling tools for your business processes, feel free to check out our data-driven list .
And if you need guidance to find the right vendor, let us talk to you:
1 case studies
Hazal is an industry analyst in AIMultiple. She is experienced in market research, quantitative research and data analytics. She received her master’s degree in Social Sciences from the University of Carlos III of Madrid and her bachelor’s degree in International Relations from Bilkent University.
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How to Write a Case Study: A Step-by-Step Guide (+ Examples)
by Todd Brehe
on Aug 23, 2022
If you want to learn how to write a case study that engages prospective clients, demonstrates that you can solve real business problems, and showcases the results you deliver, this guide will help.
We’ll give you a proven template to follow, show you how to conduct an engaging interview, and give you several examples and tips for best practices.
Let’s start with the basics.
What is a Case Study?
A business case study is simply a story about how you successfully delivered a solution to your client.
Case studies start with background information about the customer, describe problems they were facing, present the solutions you developed, and explain how those solutions positively impacted the customer’s business.
Do Marketing Case Studies Really Work?
Absolutely. A well-written case study puts prospective clients into the shoes of your paying clients, encouraging them to engage with you. Plus, they:
- Get shared “behind the lines” with decision makers you may not know;
- Leverage the power of “social proof” to encourage a prospective client to take a chance with your company;
- Build trust and foster likeability;
- Lessen the perceived risk of doing business with you and offer proof that your business can deliver results;
- Help prospects become aware of unrecognized problems;
- Show prospects experiencing similar problems that possible solutions are available (and you can provide said solutions);
- Make it easier for your target audience to find you when using Google and other search engines.
Case studies serve your clients too. For example, they can generate positive publicity and highlight the accomplishments of line staff to the management team. Your company might even throw in a new product/service discount, or a gift as an added bonus.
But don’t just take my word for it. Let’s look at a few statistics and success stories:
5 Winning Case Study Examples to Model
Before we get into the nuts and bolts of how to write a case study, let’s go over a few examples of what an excellent one looks like.
The five case studies listed below are well-written, well-designed, and incorporate a time-tested structure.
1. Lane Terralever and Pinnacle at Promontory
This case study example from Lane Terralever incorporates images to support the content and effectively uses subheadings to make the piece scannable.
2. WalkMe Mobile and Hulyo
This case study from WalkMe Mobile leads with an engaging headline and the three most important results the client was able to generate.
In the first paragraph, the writer expands the list of accomplishments encouraging readers to learn more.
3. CurationSuite Listening Engine
This is an example of a well-designed printable case study . The client, specific problem, and solution are called out in the left column and summarized succinctly.
4. Brain Traffic and ASAE
This long format case study (6 pages) from Brain Traffic summarizes the challenges, solutions, and results prominently in the left column. It uses testimonials and headshots of the case study participants very effectively.
5. Adobe and Home Depot
This case study from Adobe and Home Depot is a great example of combining video, attention-getting graphics, and long form writing. It also uses testimonials and headshots well.
Now that we’ve gone over the basics and showed a few great case study examples you can use as inspiration, let’s roll up our sleeves and get to work.
A Case Study Structure That Pros Use
Let’s break down the structure of a compelling case study:
Choose Your Case Study Format
In this guide, we focus on written case studies. They’re affordable to create, and they have a proven track record. However, written case studies are just one of four case study formats to consider:
- Infographic
If you have the resources, video (like the Adobe and Home Depot example above) and podcast case studies can be very compelling. Hearing a client discuss in his or her own words how your company helped is an effective content marketing strategy
Infographic case studies are usually one-page images that summarize the challenge, proposed solution, and results. They tend to work well on social media.
Follow a Tried-and-True Case Study Template
The success story structure we’re using incorporates a “narrative” or “story arc” designed to suck readers in and captivate their interest.
Note: I recommend creating a blog post or landing page on your website that includes the text from your case study, along with a downloadable PDF. Doing so helps people find your content when they perform Google and other web searches.
There are a few simple SEO strategies that you can apply to your blog post that will optimize your chances of being found. I’ll include those tips below.
Craft a Compelling Headline
The headline should capture your audience’s attention quickly. Include the most important result you achieved, the client’s name, and your company’s name. Create several examples, mull them over a bit, then pick the best one. And, yes, this means writing the headline is done at the very end.
SEO Tip: Let’s say your firm provided “video editing services” and you want to target this primary keyword. Include it, your company name, and your client’s name in the case study title.
Write the Executive Summary
This is a mini-narrative using an abbreviated version of the Challenge + Solution + Results model (3-4 short paragraphs). Write this after you complete the case study.
SEO Tip: Include your primary keyword in the first paragraph of the Executive Summary.
Provide the Client’s Background
Introduce your client to the reader and create context for the story.
List the Customer’s Challenges and Problems
Vividly describe the situation and problems the customer was dealing with, before working with you.
SEO Tip: To rank on page one of Google for our target keyword, review the questions listed in the “People also ask” section at the top of Google’s search results. If you can include some of these questions and their answers into your case study, do so. Just make sure they fit with the flow of your narrative.
Detail Your Solutions
Explain the product or service your company provided, and spell out how it alleviated the client’s problems. Recap how the solution was delivered and implemented. Describe any training needed and the customer’s work effort.
Show Your Results
Detail what you accomplished for the customer and the impact your product/service made. Objective, measurable results that resonate with your target audience are best.
List Future Plans
Share how your client might work with your company in the future.
Give a Call-to-Action
Clearly detail what you want the reader to do at the end of your case study.
Talk About You
Include a “press release-like” description of your client’s organization, with a link to their website. For your printable document, add an “About” section with your contact information.
And that’s it. That’s the basic structure of any good case study.
Now, let’s go over how to get the information you’ll use in your case study.
How to Conduct an Engaging Case Study Interview
One of the best parts of creating a case study is talking with your client about the experience. This is a fun and productive way to learn what your company did well, and what it can improve on, directly from your customer’s perspective.
Here are some suggestions for conducting great case study interviews:
When Choosing a Case Study Subject, Pick a Raving Fan
Your sales and marketing team should know which clients are vocal advocates willing to talk about their experiences. Your customer service and technical support teams should be able to contribute suggestions.
Clients who are experts with your product/service make solid case study candidates. If you sponsor an online community, look for product champions who post consistently and help others.
When selecting a candidate, think about customer stories that would appeal to your target audience. For example, let’s say your sales team is consistently bumping into prospects who are excited about your solution, but are slow to pull the trigger and do business with you.
In this instance, finding a client who felt the same way, but overcame their reluctance and contracted with you anyway, would be a compelling story to capture and share.
Prepping for the Interview
If you’ve ever seen an Oprah interview, you’ve seen a master who can get almost anyone to open up and talk. Part of the reason is that she and her team are disciplined about planning.
Before conducting a case study interview, talk to your own team about the following:
- What’s unique about the client (location, size, industry, etc.) that will resonate with our prospects?
- Why did the customer select us?
- How did we help the client?
- What’s unique about this customer’s experience?
- What problems did we solve?
- Were any measurable, objective results generated?
- What do we want readers to do after reading this case study analysis?
Pro Tip: Tee up your client. Send them the questions in advance.
Providing questions to clients before the interview helps them prepare, gather input from other colleagues if needed, and feel more comfortable because they know what to expect.
In a moment, I’ll give you an exhaustive list of interview questions. But don’t send them all. Instead, pare the list down to one or two questions in each section and personalize them for your customer.
Nailing the Client Interview
Decide how you’ll conduct the interview. Will you call the client, use Skype or Facetime, or meet in person? Whatever mode you choose, plan the process in advance.
Make sure you record the conversation. It’s tough to lead an interview, listen to your contact’s responses, keep the conversation flowing, write notes, and capture all that the person is saying.
A recording will make it easier to write the client’s story later. It’s also useful for other departments in your company (management, sales, development, etc.) to hear real customer feedback.
Use open-ended questions that spur your contact to talk and share. Here are some real-life examples:
Introduction
- Recap the purpose of the call. Confirm how much time your contact has to talk (30-45 minutes is preferable).
- Confirm the company’s location, number of employees, years in business, industry, etc.
- What’s the contact’s background, title, time with the company, primary responsibilities, and so on?
Initial Challenges
- Describe the situation at your company before engaging with us?
- What were the initial problems you wanted to solve?
- What was the impact of those problems?
- When did you realize you had to take some action?
- What solutions did you try?
- What solutions did you implement?
- What process did you go through to make a purchase?
- How did the implementation go?
- How would you describe the work effort required of your team?
- If training was involved, how did that go?
Results, Improvements, Progress
- When did you start seeing improvements?
- What were the most valuable results?
- What did your team like best about working with us?
- Would you recommend our solution/company? Why?
Future Plans
- How do you see our companies working together in the future?
Honest Feedback
- Our company is very focused on continual improvement. What could we have done differently to make this an even better experience?
- What would you like us to add or change in our product/service?
During the interview, use your contact’s responses to guide the conversation.
Once the interview is complete, it’s time to write your case study.
How to Write a Case Study… Effortlessly
Case study writing is not nearly as difficult as many people make it out to be. And you don’t have to be Stephen King to do professional work. Here are a few tips:
- Use the case study structure that we outlined earlier, but write these sections first: company background, challenges, solutions, and results.
- Write the headline, executive summary, future plans, and call-to-action (CTA) last.
- In each section, include as much content from your interview as you can. Don’t worry about editing at this point
- Tell the story by discussing their trials and tribulations.
- Stay focused on the client and the results they achieved.
- Make their organization and employees shine.
- When including information about your company, frame your efforts in a supporting role.
Also, make sure to do the following:
Add Testimonials, Quotes, and Visuals
The more you can use your contact’s words to describe the engagement, the better. Weave direct quotes throughout your narrative.
Strive to be conversational when you’re writing case studies, as if you’re talking to a peer.
Include images in your case study that visually represent the content and break up the text. Photos of the company, your contact, and other employees are ideal.
If you need to incorporate stock photos, here are three resources:
- Deposit p hotos
And if you need more, check out Smart Blogger’s excellent resource: 17 Sites with High-Quality, Royalty-Free Stock Photos .
Proofread and Tighten Your Writing
Make sure there are no grammar, spelling, or punctuation errors. If you need help, consider using a grammar checker tool like Grammarly .
My high school English teacher’s mantra was “tighten your writing.” She taught that impactful writing is concise and free of weak, unnecessary words . This takes effort and discipline, but will make your writing stronger.
Also, keep in mind that we live in an attention-diverted society. Before your audience will dive in and read each paragraph, they’ll first scan your work. Use subheadings to summarize information, convey meaning quickly, and pull the reader in.
Be Sure to Use Best Practices
Consider applying the following best practices to your case study:
- Stay laser-focused on your client and the results they were able to achieve.
- Even if your audience is technical, minimize the use of industry jargon. If you use acronyms, explain them.
- Leave out the selling and advertising.
- Don’t write like a Shakespearean wannabe. Write how people speak. Write to be understood.
- Clear and concise writing is not only more understandable, it inspires trust. Don’t ramble.
- Weave your paragraphs together so that each sentence is dependent on the one before and after it.
- Include a specific case study call-to-action (CTA).
- A recommended case study length is 2-4 pages.
- Commit to building a library of case studies.
Get Client Approval
After you have a final draft, send it to the client for review and approval. Incorporate any edits they suggest.
Use or modify the following “Consent to Publish” form to get the client’s written sign-off:
Consent to Publish
Case Study Title:
I hereby confirm that I have reviewed the case study listed above and on behalf of the [Company Name], I provide full permission for the work to be published, in whole or in part, for the life of the work, in all languages and all formats by [Company publishing the case study].
By signing this form, I affirm that I am authorized to grant full permission.
Company Name:
E-mail Address:
Common Case Study Questions (& Answers)
We’ll wrap things up with a quick Q&A. If you have a question I didn’t answer, be sure to leave it in a blog comment below.
Should I worry about print versions of my case studies?
Absolutely.
As we saw in the CurationSuite and Brain Traffic examples earlier, case studies get downloaded, printed, and shared. Prospects can and will judge your book by its cover.
So, make sure your printed case study is eye-catching and professionally designed. Hire a designer if necessary.
Why are good case studies so effective?
Case studies work because people trust them.
They’re not ads, they’re not press releases, and they’re not about how stellar your company is.
Plus, everyone likes spellbinding stories with a hero [your client], a conflict [challenges], and a riveting resolution [best solution and results].
How do I promote my case study?
After you’ve written your case study and received the client’s approval to use it, you’ll want to get it in front of as many eyes as possible.
Try the following:
- Make sure your case studies can be easily found on your company’s homepage.
- Tweet and share the case study on your various social media accounts.
- Have your sales team use the case study as a reason to call on potential customers. For example: “Hi [prospect], we just published a case study on Company A. They were facing some of the same challenges I believe your firm is dealing with. I’m going to e-mail you a copy. Let me know what you think.”
- Distribute printed copies at trade shows, seminars, or during sales presentations.
- If you’re bidding on a job and have to submit a quote or a Request for Proposal (RFP), include relevant case studies as supporting documents.
Ready to Write a Case Study That Converts?
If you want to stand out and you want to win business, case studies should be an integral part of your sales and marketing efforts.
Hopefully, this guide answered some of your questions and laid out a path that will make it faster and easier for your team to create professional, sales-generating content.
Now it’s time to take action and get started. Gather your staff, select a client, and ask a contact to participate. Plan your interview and lead an engaging conversation. Write up your client’s story, make them shine, and then share it.
Get better at the case study process by doing it more frequently. Challenge yourself to write at least one case study every two months.
As you do, you’ll be building a valuable repository of meaningful, powerful content. These success stories will serve your business in countless ways, and for years to come.
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Written by Todd Brehe
6 thoughts on “how to write a case study: a step-by-step guide (+ examples)”.
Just the guide I needed for case studies! Great job with this one!
Hey Todd, great post here. I liked that you listed some prompting questions. Really demonstrates you know what you’re talking about. There are a bunch of Ultimate Guides out there who list the theories such as interview your customer, talk about results, etc. but really don’t help you much.
Thanks, Todd. I’ve planned a case study and this will really come in handy. Bookmarked.
Very good read. Thanks, Todd. Are there any differences between a case study and a use case, by the way?
Hi Todd, Very well-written article. This is the ultimate guide I have read till date. It has actionable points rather than some high-level gyan. Creating a new case study always works better when (1) you know the structure to follow and (2) you work in a group of 3-4 members rather than individually. Thanks for sharing this guide.
Hi Todd. Very useful guide. I learn step by step. Looking forward to continually learning from you and your team. Thanks
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This is the 8th article in our case study series on auditing with process mining . The series is written by Jasmine Handler and Andreas Preslmayr from the City of Vienna. You can find an overview of all the articles in the series here .
Once we had access to our transformed data sets, we loaded the data into the process mining software Disco and got a first impression of the complexity of the process.
Although we had worked with simplification methods from the beginning and focused on the activities from the high-level reference process to identify relevant data tables , the process map was still very complex. Figure 10 shows the discovered process model from an order perspective.
Due to the high complexity, we applied further simplification strategies to enable an explorative analysis and a should-be comparison of the real process paths and the reference process.
Firstly, by including most of the timestamp fields that we could find, we had derived a high number of activities from the raw data files. Among these activities were administrative process steps that were outside our reference process. We reduced the number of activities by only keeping those process steps that we could directly map to the high-level reference process ( Milestone simplification method ). This reduced the number of activities from more than 100 to approximately 50. Note that the data in the IT system was still more detailed than the high-level process. For example, a purchase order could be checked, rejected, and released on different levels (see Figure 11).
Secondly, there was still a high variation regarding the process paths. Therefore, we decided to cluster the data into four groups ( Semantic variant simplification method ). These four groups were:
canceled cases,
cases without an invoice,
cases with one invoice, and
cases with multiple invoices.
By looking at each data segment separately, the number of process variants was further reduced.
Finally, we also decided to focus on the most common process paths to get an overview of the mainstream behavior ( Variant simplification method ). Figure 12 shows the discovered model based on only the ten most frequent process variants. This helped us to get an overview of the main process before going into detail and analyzing the less frequent paths and how they deviate from mainstream behavior.
Due to the complexity reduction, we could now perform an explorative analysis, searching for inconsistencies and analyzing unexpected process paths in more detail.
New parts in this auditing series will appear on this blog every week. Simply come back or sign up to be notified about new blog entries here .
Anne Rozinat
Market, customers, and everything else.
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Anne knows how to mine a process like no other. She has conducted a large number of process mining projects with companies such as Philips Healthcare, Océ, ASML, Philips Consumer Lifestyle, and many others.
You may also like:
- Case Study: Auditing With Process Mining — Part VII: Data Sets
- Case Study: Auditing With Process Mining — Part VI: Data Transformation
- Case Study: Auditing With Process Mining — Part V: Raw Data
- Case Study: Auditing With Process Mining — Part IV: Process and Data Model
- Case Study: Auditing With Process Mining — Part III: Analysis Questions
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You are reading Flux Capacitor , the company weblog of Fluxicon . Here, we write mainly about Process Mining , the things we're up to, and anything really.
We make Disco , the most powerful, user-friendly, and popular process mining software in the world. You should check it out and download your free demo version here !
Every year, we organize Process Mining Camp , the only conference exclusively focused on the practical application of process mining. Join hundreds of Process Miners from all over the world for two days of practice talks, workshops, and hanging out in Eindhoven!
Whether you are a beginner, or an experienced process mining practitioner — you may want to join one of our popular Process Mining Trainings , given every few weeks by experienced guides. We hear they're pretty great.
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What Is Case Management? Definition, Process, and Models
Case management is all about connecting patients with health care providers, designing treatment plans, and making sure it all gets done on time. Learn more about this project-oriented health care profession.
![[Featured Image]: A case manager, wearing a blue uniform and a blue head covering, is sitting in front of three computer screens, looking at charts.](https://d3njjcbhbojbot.cloudfront.net/api/utilities/v1/imageproxy/https://images.ctfassets.net/wp1lcwdav1p1/74UCNQZ7eoX2IiTXBfxqlm/22e01be84083d62ce5b73fd342e8c6a1/GettyImages-108436364__1_.jpg?w=1500&h=680&q=60&fit=fill&f=faces&fm=jpg&fl=progressive&auto=format%2Ccompress&dpr=1&w=1000&h= "case study model process")
In health care, case management is a process that connects patients with health care providers, resources, and services. Directed toward ensuring that patients receive the best possible care, case management requires case managers to maneuver different health care systems and collaborate with stakeholders, including patients, medical professionals, and health insurers.
In this article, you will learn more about case management, its process, and explore some different case management models. At the end, you will find more articles and courses you can take to gain a fuller understanding of case management.
What is a case manager?
A case manager is a certified medical professional who connects patients with health care providers, coordinates appointments and treatment plans, and helps patients meet their optimum level of health.
Nurse case managers , for example, are registered nurses (RN) who use their medical expertise to help patients maneuver the health care system and health insurance to receive appropriate care.
What is case management?
Case management is a process that involves numerous stages and requires a unique intersection of health care knowledge and interpersonal skills. In this section, you’ll learn more about what you can expect from the case management process, the skills you’ll need to do it, and find an example of case management in action.
The case management process
Case management is a collaborative process in which a case manager works with clients to ensure they obtain the proper health care in the most cost-effective manner. This is what the process typically looks like:
1. Screening: The case manager reviews a client’s medical records, medical history, and current financial, living, and social support situation to understand client’s needs and current circumstances.
2. Assessment: The case manager conducts more in-depth research and meets with the client to assess their medical condition and circumstances. They might assess the client's health insurance, support systems, and treatment response history.
3. Risk evaluation: In this stage, the case manager evaluates the client's risk for particular ailments. Common factors that are evaluated include existing medical conditions, blood pressure, mental health, and finances.
4. Planning: The planning stage is when a case manager creates a plan of care for their client, which outlines their health objectives, self-care goals, health care options and services, care schedule, and any relevant resources.
5. Implementation: Once a plan has been devised, the case manager now helps the client implement it by guiding them in making sure they attend appointments and educating them about health care-related issues.
6. Follow-up: During the follow-up stage, the case manager sees how the client is progressing through their treatment plan by speaking with them, their health care providers, and their personal support network. If needed, the case manager might advise changing the treatment plan.
7. Evaluating outcomes: Finally, the case manager reviews the entire case and evaluates its outcomes, such as the client's well-being, finances, and whether they received appropriate care.
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Case management skills
Being a case manager requires both technical health care knowledge and strong interpersonal skills. Common skills that case managers should possess include:
Medical knowledge of a wide variety of ailments
Knowledge of the health care system, including different medical professionals, medical organizational structures, and health insurance providers
Project management and coordination
Communication
The ability to collaborate with others
Case management example
An elderly patient who recently suffered a stroke might be assigned a case manager at their hospital to ensure they get the ongoing care they need. In this situation, the case manager would act as a liaison between the patient and their health insurer. They would assess the patient’s current support network, suggest rehabilitation centers, and direct them toward additional resources. Over time, they would monitor the patient’s progress and make sure they attend their medical appointments and take any prescribed medication.
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Case management models
There are three primary case management models used in health care. While they are all oriented toward getting clients the care they need, each has its own unique emphasis. A case manager might use a combination of these models depending on their client’s needs.
Brokerage case management model
The brokerage case management model involves a case manager assessing a client’s need and then acting as a broker that connects them with the relevant resources, services, and medical professionals. Typically, case managers in this system have little personal contact with the client, acting instead as a liaison to ensure they receive the care they need. This model places less emphasis on monitoring outcomes and more on connecting clients with the medical professionals who will.
Clinical case management model
The clinical case management model involves a case manager (often a therapist or counselor ) assigned by a clinical care provider. The case manager works directly with the client in a clinical capacity, providing care as well as coordinating and developing treatment plans. Such direct collaboration can increase the client’s health outcomes and encourage them to follow their care plan more directly.
Strengths-based clinical case management model
The strengths-based clinical case management model is oriented around empowering clients and their support networks so they can meet their health goals. In effect, this model encourages psychological and emotional empowerment by reframing internal narratives and social empowerment by changing environmental factors that could be holding clients back. Though initially developed for those with severe mental health problems, this model can be used for a variety of clients with unique needs.
Learn more about case management
As you plan your future career as a case manager, you might consider taking a flexible, cost-effective online course to gain critical job skills and deeper insight into the patient experience. The University of Houston’s Value-Based Care Specialization introduces course takers to the fundamentals of value-based care, such as the role of case management and the power of effective communication to improve health outcomes for both patients and health care professionals.
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Learn About Value-Based Care. Learn the fundamentals and real-world application of value-based care that has become integral to improving outcomes in health care. Explore the power of effective communication between healthcare professionals and patients that leads to a partnership focused on quality care.
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This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.
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Case-based learning.
Case-based learning (CBL) is an established approach used across disciplines where students apply their knowledge to real-world scenarios, promoting higher levels of cognition (see Bloom’s Taxonomy ). In CBL classrooms, students typically work in groups on case studies, stories involving one or more characters and/or scenarios. The cases present a disciplinary problem or problems for which students devise solutions under the guidance of the instructor. CBL has a strong history of successful implementation in medical, law, and business schools, and is increasingly used within undergraduate education, particularly within pre-professional majors and the sciences (Herreid, 1994). This method involves guided inquiry and is grounded in constructivism whereby students form new meanings by interacting with their knowledge and the environment (Lee, 2012).
There are a number of benefits to using CBL in the classroom. In a review of the literature, Williams (2005) describes how CBL: utilizes collaborative learning, facilitates the integration of learning, develops students’ intrinsic and extrinsic motivation to learn, encourages learner self-reflection and critical reflection, allows for scientific inquiry, integrates knowledge and practice, and supports the development of a variety of learning skills.
CBL has several defining characteristics, including versatility, storytelling power, and efficient self-guided learning. In a systematic analysis of 104 articles in health professions education, CBL was found to be utilized in courses with less than 50 to over 1000 students (Thistlethwaite et al., 2012). In these classrooms, group sizes ranged from 1 to 30, with most consisting of 2 to 15 students. Instructors varied in the proportion of time they implemented CBL in the classroom, ranging from one case spanning two hours of classroom time, to year-long case-based courses. These findings demonstrate that instructors use CBL in a variety of ways in their classrooms.
The stories that comprise the framework of case studies are also a key component to CBL’s effectiveness. Jonassen and Hernandez-Serrano (2002, p.66) describe how storytelling:
Is a method of negotiating and renegotiating meanings that allows us to enter into other’s realms of meaning through messages they utter in their stories,
Helps us find our place in a culture,
Allows us to explicate and to interpret, and
Facilitates the attainment of vicarious experience by helping us to distinguish the positive models to emulate from the negative model.
Neurochemically, listening to stories can activate oxytocin, a hormone that increases one’s sensitivity to social cues, resulting in more empathy, generosity, compassion and trustworthiness (Zak, 2013; Kosfeld et al., 2005). The stories within case studies serve as a means by which learners form new understandings through characters and/or scenarios.
CBL is often described in conjunction or in comparison with problem-based learning (PBL). While the lines are often confusingly blurred within the literature, in the most conservative of definitions, the features distinguishing the two approaches include that PBL involves open rather than guided inquiry, is less structured, and the instructor plays a more passive role. In PBL multiple solutions to the problem may exit, but the problem is often initially not well-defined. PBL also has a stronger emphasis on developing self-directed learning. The choice between implementing CBL versus PBL is highly dependent on the goals and context of the instruction. For example, in a comparison of PBL and CBL approaches during a curricular shift at two medical schools, students and faculty preferred CBL to PBL (Srinivasan et al., 2007). Students perceived CBL to be a more efficient process and more clinically applicable. However, in another context, PBL might be the favored approach.
In a review of the effectiveness of CBL in health profession education, Thistlethwaite et al. (2012), found several benefits:
Students enjoyed the method and thought it enhanced their learning,
Instructors liked how CBL engaged students in learning,
CBL seemed to facilitate small group learning, but the authors could not distinguish between whether it was the case itself or the small group learning that occurred as facilitated by the case.
Other studies have also reported on the effectiveness of CBL in achieving learning outcomes (Bonney, 2015; Breslin, 2008; Herreid, 2013; Krain, 2016). These findings suggest that CBL is a vehicle of engagement for instruction, and facilitates an environment whereby students can construct knowledge.
Science – Students are given a scenario to which they apply their basic science knowledge and problem-solving skills to help them solve the case. One example within the biological sciences is two brothers who have a family history of a genetic illness. They each have mutations within a particular sequence in their DNA. Students work through the case and draw conclusions about the biological impacts of these mutations using basic science. Sample cases: You are Not the Mother of Your Children ; Organic Chemisty and Your Cellphone: Organic Light-Emitting Diodes ; A Light on Physics: F-Number and Exposure Time
Medicine – Medical or pre-health students read about a patient presenting with specific symptoms. Students decide which questions are important to ask the patient in their medical history, how long they have experienced such symptoms, etc. The case unfolds and students use clinical reasoning, propose relevant tests, develop a differential diagnoses and a plan of treatment. Sample cases: The Case of the Crying Baby: Surgical vs. Medical Management ; The Plan: Ethics and Physician Assisted Suicide ; The Haemophilus Vaccine: A Victory for Immunologic Engineering
Public Health – A case study describes a pandemic of a deadly infectious disease. Students work through the case to identify Patient Zero, the person who was the first to spread the disease, and how that individual became infected. Sample cases: The Protective Parent ; The Elusive Tuberculosis Case: The CDC and Andrew Speaker ; Credible Voice: WHO-Beijing and the SARS Crisis
Law – A case study presents a legal dilemma for which students use problem solving to decide the best way to advise and defend a client. Students are presented information that changes during the case. Sample cases: Mortgage Crisis Call (abstract) ; The Case of the Unpaid Interns (abstract) ; Police-Community Dialogue (abstract)
Business – Students work on a case study that presents the history of a business success or failure. They apply business principles learned in the classroom and assess why the venture was successful or not. Sample cases: SELCO-Determining a path forward ; Project Masiluleke: Texting and Testing to Fight HIV/AIDS in South Africa ; Mayo Clinic: Design Thinking in Healthcare
Humanities - Students consider a case that presents a theater facing financial and management difficulties. They apply business and theater principles learned in the classroom to the case, working together to create solutions for the theater. Sample cases: https://yaletmknowledgebase.org/category/case-studies/ .
Recommendations
Finding and Writing Cases
Consider utilizing or adapting open access cases - The availability of open resources and databases containing cases that instructors can download makes this approach even more accessible in the classroom. Instructors can consider in particular the National Center for Case Study Teaching in Science , a database featuring hundreds of accessible STEM- and social science - based case studies.
- Consider writing original cases - In the event that an instructor is unable to find open access cases relevant to their course learning objectives, they may choose to write their own. See the following resources on case writing: Cooking with Betty Crocker: A Recipe for Case Writing ; The Way of Flesch: The Art of Writing Readable Cases ; Twixt Fact and Fiction: A Case Writer’s Dilemma ; And All That Jazz: An Essay Extolling the Virtues of Writing Case Teaching Notes .
Implementing Cases
Take baby steps if new to CBL - While entire courses and curricula may involve case-based learning, instructors who desire to implement on a smaller-scale can integrate a single case into their class, and increase the number of cases utilized over time as desired.
Use cases in classes that are small, medium or large - Cases can be scaled to any course size. In large classes with stadium seating, students can work with peers nearby, while in small classes with more flexible seating arrangements, teams can move their chairs closer together. CBL can introduce more noise (and energy) in the classroom to which an instructor often quickly becomes accustomed. Further, students can be asked to work on cases outside of class, and wrap up discussion during the next class meeting.
Encourage collaborative work - Cases present an opportunity for students to work together to solve cases which the historical literature supports as beneficial to student learning (Bruffee, 1993). Allow students to work in groups to answer case questions.
Form diverse teams as feasible - When students work within diverse teams they can be exposed to a variety of perspectives that can help them solve the case. Depending on the context of the course, priorities, and the background information gathered about the students enrolled in the class, instructors may choose to organize student groups to allow for diversity in factors such as current course grades, gender, race/ethnicity, personality, among other items.
Use stable teams as appropriate - If CBL is a large component of the course, a research-supported practice is to keep teams together long enough to go through the stages of group development: forming, storming, norming, performing and adjourning (Tuckman, 1965).
Walk around to guide groups - In CBL instructors serve as facilitators of student learning. Walking around allows the instructor to monitor student progress as well as identify and support any groups that may be struggling. Teaching assistants can also play a valuable role in supporting groups.
Interrupt strategically - Only every so often, for conversation in large group discussion of the case, especially when students appear confused on key concepts. An effective practice to help students meet case learning goals is to guide them as a whole group when the class is ready. This may include selecting a few student groups to present answers to discussion questions to the entire class, asking the class a question relevant to the case using polling software, and/or performing a mini-lesson on an area that appears to be confusing among students.
Assess student learning in multiple ways - Students can be assessed informally by asking groups to report back answers to various case questions. This practice also helps students stay on task, and keeps them accountable. Cases can also be included on exams using related scenarios where students are asked to apply their knowledge.
Barrows HS. (1996). Problem-based learning in medicine and beyond: a brief overview. New Directions for Teaching and Learning, 68, 3-12.
Bonney KM. (2015). Case Study Teaching Method Improves Student Performance and Perceptions of Learning Gains. Journal of Microbiology and Biology Education, 16(1): 21-28.
Breslin M, Buchanan, R. (2008) On the Case Study Method of Research and Teaching in Design. Design Issues, 24(1), 36-40.
Bruffee KS. (1993). Collaborative learning: Higher education, interdependence, and authority of knowledge. Johns Hopkins University Press, Baltimore, MD.
Herreid CF. (2013). Start with a Story: The Case Study Method of Teaching College Science, edited by Clyde Freeman Herreid. Originally published in 2006 by the National Science Teachers Association (NSTA); reprinted by the National Center for Case Study Teaching in Science (NCCSTS) in 2013.
Herreid CH. (1994). Case studies in science: A novel method of science education. Journal of Research in Science Teaching, 23(4), 221–229.
Jonassen DH and Hernandez-Serrano J. (2002). Case-based reasoning and instructional design: Using stories to support problem solving. Educational Technology, Research and Development, 50(2), 65-77.
Kosfeld M, Heinrichs M, Zak PJ, Fischbacher U, Fehr E. (2005). Oxytocin increases trust in humans. Nature, 435, 673-676.
Krain M. (2016) Putting the learning in case learning? The effects of case-based approaches on student knowledge, attitudes, and engagement. Journal on Excellence in College Teaching, 27(2), 131-153.
Lee V. (2012). What is Inquiry-Guided Learning? New Directions for Learning, 129:5-14.
Nkhoma M, Sriratanaviriyakul N. (2017). Using case method to enrich students’ learning outcomes. Active Learning in Higher Education, 18(1):37-50.
Srinivasan et al. (2007). Comparing problem-based learning with case-based learning: Effects of a major curricular shift at two institutions. Academic Medicine, 82(1): 74-82.
Thistlethwaite JE et al. (2012). The effectiveness of case-based learning in health professional education. A BEME systematic review: BEME Guide No. 23. Medical Teacher, 34, e421-e444.
Tuckman B. (1965). Development sequence in small groups. Psychological Bulletin, 63(6), 384-99.
Williams B. (2005). Case-based learning - a review of the literature: is there scope for this educational paradigm in prehospital education? Emerg Med, 22, 577-581.
Zak, PJ (2013). How Stories Change the Brain. Retrieved from: https://greatergood.berkeley.edu/article/item/how_stories_change_brain
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Five Case Studies of Transformation Excellence
November 03, 2014 By Lars Fæste , Jim Hemerling , Perry Keenan , and Martin Reeves
In a business environment characterized by greater volatility and more frequent disruptions, companies face a clear imperative: they must transform or fall behind. Yet most transformation efforts are highly complex initiatives that take years to implement. As a result, most fall short of their intended targets—in value, timing, or both. Based on client experience, The Boston Consulting Group has developed an approach to transformation that flips the odds in a company’s favor. What does that look like in the real world? Here are five company examples that show successful transformations, across a range of industries and locations.
VF’s Growth Transformation Creates Strong Value for Investors
Value creation is a powerful lens for identifying the initiatives that will have the greatest impact on a company’s transformation agenda and for understanding the potential value of the overall program for shareholders.
VF offers a compelling example of a company using a sharp focus on value creation to chart its transformation course. In the early 2000s, VF was a good company with strong management but limited organic growth. Its “jeanswear” and intimate-apparel businesses, although responsible for 80 percent of the company’s revenues, were mature, low-gross-margin segments. And the company’s cost-cutting initiatives were delivering diminishing returns. VF’s top line was essentially flat, at about $5 billion in annual revenues, with an unclear path to future growth. VF’s value creation had been driven by cost discipline and manufacturing efficiency, yet, to the frustration of management, VF had a lower valuation multiple than most of its peers.
With BCG’s help, VF assessed its options and identified key levers to drive stronger and more-sustainable value creation. The result was a multiyear transformation comprising four components:
- A Strong Commitment to Value Creation as the Company’s Focus. Initially, VF cut back its growth guidance to signal to investors that it would not pursue growth opportunities at the expense of profitability. And as a sign of management’s commitment to balanced value creation, the company increased its dividend by 90 percent.
- Relentless Cost Management. VF built on its long-known operational excellence to develop an operating model focused on leveraging scale and synergies across its businesses through initiatives in sourcing, supply chain processes, and offshoring.
- A Major Transformation of the Portfolio. To help fund its journey, VF divested product lines worth about $1 billion in revenues, including its namesake intimate-apparel business. It used those resources to acquire nearly $2 billion worth of higher-growth, higher-margin brands, such as Vans, Nautica, and Reef. Overall, this shifted the balance of its portfolio from 70 percent low-growth heritage brands to 65 percent higher-growth lifestyle brands.
- The Creation of a High-Performance Culture. VF has created an ownership mind-set in its management ranks. More than 200 managers across all key businesses and regions received training in the underlying principles of value creation, and the performance of every brand and business is assessed in terms of its value contribution. In addition, VF strengthened its management bench through a dedicated talent-management program and selective high-profile hires. (For an illustration of VF’s transformation roadmap, see the exhibit.)
The results of VF’s TSR-led transformation are apparent. 1 1 For a detailed description of the VF journey, see the 2013 Value Creators Report, Unlocking New Sources of Value Creation , BCG report, September 2013. Notes: 1 For a detailed description of the VF journey, see the 2013 Value Creators Report, Unlocking New Sources of Value Creation , BCG report, September 2013. The company’s revenues have grown from $7 billion in 2008 to more than $11 billion in 2013 (and revenues are projected to top $17 billion by 2017). At the same time, profitability has improved substantially, highlighted by a gross margin of 48 percent as of mid-2014. The company’s stock price quadrupled from $15 per share in 2005 to more than $65 per share in September 2014, while paying about 2 percent a year in dividends. As a result, the company has ranked in the top quintile of the S&P 500 in terms of TSR over the past ten years.
A Consumer-Packaged-Goods Company Uses Several Levers to Fund Its Transformation Journey
A leading consumer-packaged-goods (CPG) player was struggling to respond to challenging market dynamics, particularly in the value-based segments and at the price points where it was strongest. The near- and medium-term forecasts looked even worse, with likely contractions in sales volume and potentially even in revenues. A comprehensive transformation effort was needed.
To fund the journey, the company looked at several cost-reduction initiatives, including logistics. Previously, the company had worked with a large number of logistics providers, causing it to miss out on scale efficiencies.
To improve, it bundled all transportation spending, across the entire network (both inbound to production facilities and out-bound to its various distribution channels), and opened it to bidding through a request-for-proposal process. As a result, the company was able to save 10 percent on logistics in the first 12 months—a very fast gain for what is essentially a commodity service.
Similarly, the company addressed its marketing-agency spending. A benchmark analysis revealed that the company had been paying rates well above the market average and getting fewer hours per full-time equivalent each year than the market standard. By getting both rates and hours in line, the company managed to save more than 10 percent on its agency spending—and those savings were immediately reinvested to enable the launch of what became a highly successful brand.
Next, the company pivoted to growth mode in order to win in the medium term. The measure with the biggest impact was pricing. The company operates in a category that is highly segmented across product lines and highly localized. Products that sell well in one region often do poorly in a neighboring state. Accordingly, it sought to de-average its pricing approach across locations, brands, and pack sizes, driving a 2 percent increase in EBIT.
Similarly, it analyzed trade promotion effectiveness by gathering and compiling data on the roughly 150,000 promotions that the company had run across channels, locations, brands, and pack sizes. The result was a 2 terabyte database tracking the historical performance of all promotions.
Using that information, the company could make smarter decisions about which promotions should be scrapped, which should be tweaked, and which should merit a greater push. The result was another 2 percent increase in EBIT. Critically, this was a clear capability that the company built up internally, with the objective of continually strengthening its trade-promotion performance over time, and that has continued to pay annual dividends.
Finally, the company launched a significant initiative in targeted distribution. Before the transformation, the company’s distributors made decisions regarding product stocking in independent retail locations that were largely intuitive. To improve its distribution, the company leveraged big data to analyze historical sales performance for segments, brands, and individual SKUs within a roughly ten-mile radius of that retail location. On the basis of that analysis, the company was able to identify the five SKUs likely to sell best that were currently not in a particular store. The company put this tool on a mobile platform and is in the process of rolling it out to the distributor base. (Currently, approximately 60 percent of distributors, representing about 80 percent of sales volume, are rolling it out.) Without any changes to the product lineup, that measure has driven a 4 percent jump in gross sales.
Throughout the process, management had a strong change-management effort in place. For example, senior leaders communicated the goals of the transformation to employees through town hall meetings. Cognizant of how stressful transformations can be for employees—particularly during the early efforts to fund the journey, which often emphasize cost reductions—the company aggressively talked about how those savings were being reinvested into the business to drive growth (for example, investments into the most effective trade promotions and the brands that showed the greatest sales-growth potential).
In the aggregate, the transformation led to a much stronger EBIT performance, with increases of nearly $100 million in fiscal 2013 and far more anticipated in 2014 and 2015. The company’s premium products now make up a much bigger part of the portfolio. And the company is better positioned to compete in its market.
A Leading Bank Uses a Lean Approach to Transform Its Target Operating Model
A leading bank in Europe is in the process of a multiyear transformation of its operating model. Prior to this effort, a benchmarking analysis found that the bank was lagging behind its peers in several aspects. Branch employees handled fewer customers and sold fewer new products, and back-office processing times for new products were slow. Customer feedback was poor, and rework rates were high, especially at the interface between the front and back offices. Activities that could have been managed centrally were handled at local levels, increasing complexity and cost. Harmonization across borders—albeit a challenge given that the bank operates in many countries—was limited. However, the benchmark also highlighted many strengths that provided a basis for further improvement, such as common platforms and efficient product-administration processes.
To address the gaps, the company set the design principles for a target operating model for its operations and launched a lean program to get there. Using an end-to-end process approach, all the bank’s activities were broken down into roughly 250 processes, covering everything that a customer could potentially experience. Each process was then optimized from end to end using lean tools. This approach breaks down silos and increases collaboration and transparency across both functions and organization layers.
Employees from different functions took an active role in the process improvements, participating in employee workshops in which they analyzed processes from the perspective of the customer. For a mortgage, the process was broken down into discrete steps, from the moment the customer walks into a branch or goes to the company website, until the house has changed owners. In the front office, the system was improved to strengthen management, including clear performance targets, preparation of branch managers for coaching roles, and training in root-cause problem solving. This new way of working and approaching problems has directly boosted both productivity and morale.
The bank is making sizable gains in performance as the program rolls through the organization. For example, front-office processing time for a mortgage has decreased by 33 percent and the bank can get a final answer to customers 36 percent faster. The call centers had a significant increase in first-call resolution. Even more important, customer satisfaction scores are increasing, and rework rates have been halved. For each process the bank revamps, it achieves a consistent 15 to 25 percent increase in productivity.
And the bank isn’t done yet. It is focusing on permanently embedding a change mind-set into the organization so that continuous improvement becomes the norm. This change capability will be essential as the bank continues on its transformation journey.
A German Health Insurer Transforms Itself to Better Serve Customers
Barmer GEK, Germany’s largest public health insurer, has a successful history spanning 130 years and has been named one of the top 100 brands in Germany. When its new CEO, Dr. Christoph Straub, took office in 2011, he quickly realized the need for action despite the company’s relatively good financial health. The company was still dealing with the postmerger integration of Barmer and GEK in 2010 and needed to adapt to a fast-changing and increasingly competitive market. It was losing ground to competitors in both market share and key financial benchmarks. Barmer GEK was suffering from overhead structures that kept it from delivering market-leading customer service and being cost efficient, even as competitors were improving their service offerings in a market where prices are fixed. Facing this fundamental challenge, Barmer GEK decided to launch a major transformation effort.
The goal of the transformation was to fundamentally improve the customer experience, with customer satisfaction as a benchmark of success. At the same time, Barmer GEK needed to improve its cost position and make tough choices to align its operations to better meet customer needs. As part of the first step in the transformation, the company launched a delayering program that streamlined management layers, leading to significant savings and notable side benefits including enhanced accountability, better decision making, and an increased customer focus. Delayering laid the path to win in the medium term through fundamental changes to the company’s business and operating model in order to set up the company for long-term success.
The company launched ambitious efforts to change the way things were traditionally done:
- A Better Client-Service Model. Barmer GEK is reducing the number of its branches by 50 percent, while transitioning to larger and more attractive service centers throughout Germany. More than 90 percent of customers will still be able to reach a service center within 20 minutes. To reach rural areas, mobile branches that can visit homes were created.
- Improved Customer Access. Because Barmer GEK wanted to make it easier for customers to access the company, it invested significantly in online services and full-service call centers. This led to a direct reduction in the number of customers who need to visit branches while maintaining high levels of customer satisfaction.
- Organization Simplification. A pillar of Barmer GEK’s transformation is the centralization and specialization of claim processing. By moving from 80 regional hubs to 40 specialized processing centers, the company is now using specialized administrators—who are more effective and efficient than under the old staffing model—and increased sharing of best practices.
Although Barmer GEK has strategically reduced its workforce in some areas—through proven concepts such as specialization and centralization of core processes—it has invested heavily in areas that are aligned with delivering value to the customer, increasing the number of customer-facing employees across the board. These changes have made Barmer GEK competitive on cost, with expected annual savings exceeding €300 million, as the company continues on its journey to deliver exceptional value to customers. Beyond being described in the German press as a “bold move,” the transformation has laid the groundwork for the successful future of the company.
Nokia’s Leader-Driven Transformation Reinvents the Company (Again)
We all remember Nokia as the company that once dominated the mobile-phone industry but subsequently had to exit that business. What is easily forgotten is that Nokia has radically and successfully reinvented itself several times in its 150-year history. This makes Nokia a prime example of a “serial transformer.”
In 2014, Nokia embarked on perhaps the most radical transformation in its history. During that year, Nokia had to make a radical choice: continue massively investing in its mobile-device business (its largest) or reinvent itself. The device business had been moving toward a difficult stalemate, generating dissatisfactory results and requiring increasing amounts of capital, which Nokia no longer had. At the same time, the company was in a 50-50 joint venture with Siemens—called Nokia Siemens Networks (NSN)—that sold networking equipment. NSN had been undergoing a massive turnaround and cost-reduction program, steadily improving its results.
When Microsoft expressed interest in taking over Nokia’s device business, Nokia chairman Risto Siilasmaa took the initiative. Over the course of six months, he and the executive team evaluated several alternatives and shaped a deal that would radically change Nokia’s trajectory: selling the mobile business to Microsoft. In parallel, Nokia CFO Timo Ihamuotila orchestrated another deal to buy out Siemens from the NSN joint venture, giving Nokia 100 percent control over the unit and forming the cash-generating core of the new Nokia. These deals have proved essential for Nokia to fund the journey. They were well-timed, well-executed moves at the right terms.
Right after these radical announcements, Nokia embarked on a strategy-led design period to win in the medium term with new people and a new organization, with Risto Siilasmaa as chairman and interim CEO. Nokia set up a new portfolio strategy, corporate structure, capital structure, robust business plans, and management team with president and CEO Rajeev Suri in charge. Nokia focused on delivering excellent operational results across its portfolio of three businesses while planning its next move: a leading position in technologies for a world in which everyone and everything will be connected.
Nokia’s share price has steadily climbed. Its enterprise value has grown 12-fold since bottoming out in July 2012. The company has returned billions of dollars of cash to its shareholders and is once again the most valuable company in Finland. The next few years will demonstrate how this chapter in Nokia’s 150-year history of serial transformation will again reinvent the company.
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A dynamic model to uphold rice self-sufficiency policies, case study; karawang regency, west java province.
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Paddy field conversions (PFCs) in Indonesia have become a major threat facing agricultural lands on the local, province, and national levels causing a reduction in rice production and leading to food insecurity. Hence, information on the impacts of PFCs on rice supply is crucial for future policy planning and management. This paper aimed to simulate four policy scenarios to view the impact of paddy fields' conversion on rice production to enhance the planning of future food security-related policies. Based on system dynamics modelling (SDM), the study used primary and secondary data to develop a quantitative Stock Flow Diagram from the qualitative Causal Loop Diagram. Available historical data; paddy cultivated area, population, and harvested areas have been used to test and validate the SDM. The study indicated that the overall maximum relative errors, coefficient of determination, and mean absolute error of tested variables were 1.33%, 0.760, and 1.49, respectively. Under the Business-as-usual scenario, it was found that the population of Karawang will reach 6.1 million people, and the paddy fields will be reduced to only 169 thousand ha by the end of the century. Thus, Karawang rice Availability Per Person, Surplus, and Self-sufficiency will be reduced by 66.20, 50.55, and 359%, respectively. Consequently, the obligation of 1.5 million tons a year cannot be met. Besides that, the Rice demand scenario indicated the Regency will be out of rice surplus in 2094 and 2085 when the demand for rice increases by 80% (SNO#3.3) and 100% (SNO#3.4), respectively. It's been concluded that paddy field conversion is the main threat that may undermine future rice production for Regency. The study recommended that proposed possible interventions should be considered along with formulating and implementing upcoming Regional Short, Medium, and long-term Development Plans.
paddy fields conversion, food security, policy scenarios, food self-sufficiency, system dynamics modelling
Across the world, food security is a significant goal for governments and communities for poverty eradication and development [1]. Indonesia has considerable resources to achieve food security, including abundant water resources and arable land to produce sufficient food. Recently, substantial attention has been paid to Indonesia's food security level and how the related resources are not being managed optimally, leading to a food insecurity situation in some parts of the territory [2]. The high dependence on rice production on Java Island is one of Indonesia's leading food security challenges. The area of Java Island only covers 7% of Indonesia's land area, yet it has 6.1 million hectares or 46.69% of total country paddy fields. It produces up to 52.32% of the national rice production [3]. Yet, 152.8 million out of 272.7 million people, or 56.03% of the country's population live in Java with a population density of 1127.5 people/Km 2 , 7.9 times higher than the national average [4]. West Java Province has the highest productivity among island provinces. Where Indramayu, and Karawang are regencies with the highest productivity in the province.
Karawang (KWR) Regency is Known as National Rice Barn "Lumbung Padi Nasional". It is the second-largest rice production centre in the province due to the paddy fields (PFs) area that the Regency possesses and the productivity of its lands. The Regency area represents only 4.6% of the province area, but it has 12% of the paddy fields of West Java, and approximately 15% of West Java rice production emanates from it [5]. It has experienced massive land-use change over the last three decades. However, up 25% of regency agricultural land use has been converted to residential, commercial, or industrial use to meet the increasing land demand due to massive urbanization [6]. Karawang lost 18,460.8 ha of its PFs between 1994 and 2015 [7]. On the other hand, the Regency population has increased by 10.76% between 2010 -2019, representing an average growth of 1.19% per year [8-10].
To minimize paddy field conversion impacts, the government of Indonesia has adopted law No 41, 2009, concerning the protection of agricultural land. Later, Presidential Decree No. 59 of 2019 was adopted to emphasize that action is needed to control paddy field conversation. In 2013, the local government of Karawang (Pemda) allocated 94,380.49 ha in the Regional Spatial Planning (RTRW) as exclusive food production lands. Moreover, in line with national government efforts to achieve national food security and food sovereignty, Pemda allocated 103,093.78 ha in 2018 as protected sustainable agricultural land (LP2B) to be exclusively designated for food production, mainly rice. According to the report of BPS-Statistics of Karawang Regency [11], the performance of these regulations/laws is not effective enough in reducing the rate of conversion.
Today numerous researchers have investigated the land use change pattern in Karawang and highlighted its impacts on the paddy fields and their ability to produce/ supply rice. Ambarwulan and Munibah [3] has used remote sensing (RS) and Geographical Information System (GIS) techniques to assess paddy field conversion from 2000 to 2011 using the Landsat 5 TM image dataset. The study stated that the paddy fields decreased from 120,865 ha to an area of 95,926 ha, with a conversion rate of 1.88 %/year, mainly due to the expansion of built-up areas. The decrease in PFs has led to a reduction in regency contribution to national food security by 10%. However, the reduction in paddy fields has decreased the Karawang rice surplus from 822,332.16 tons in 2000 to only 681,538.06 tons in 2011. Another report discussed the means and strategies to maintain national food security based on Karawang rice production [12]. The study utilized the RS, GIS, and SWOT methods to visualize the impact of floods on paddy fields and to recommend a suitable strategy. It stated that the Regency has an area of 7,489 ha (7.6%) as a high flood hazard, 19,188 ha (19.49%) as medium flood hazard, and 1.689 ha (1.72%) identified as a low flood hazard area. The Regency was losing 219.84 ha/year due to floods, equivalent to 1.5 tons of rice production loss. The study concluded that regency PFs are still able to meet local rice demands. Yet, it cannot support national food security as an obligation to provide 1.5 million tons of paddy stock per year. The loss is expected to increase due to continuing reduction in paddy fields of Karawang, which is projected to cover only 45.81% of the total regency area around 2031 [13, 14].
Furthermore, Franjaya et al. [7] has examined the dynamics change of Karawang PFs during 1994 – 2015. The study indicated that 10,326.6 ha of Karawang PFs had been converted into physical infrastructure, representing 56% of total PFs, putting the nation's food production at stake. While from 2009 to 2019, the Regency lost 16,346.77 ha or 8.54% of its PFs with an average conversion rate of 1.83 %/year. 57.98% of the conversion was converted into build-up infrastructures, highlighting the trends of land use change impacting the nation's food security negatively [15]. Few studies have analysed the factors driving the land use change in the Regency, particularly PFs conversions. Riadi et al. [16] argued that four factors significantly drove the Regency PFs conversion; slope, CBD area, build-up area, local irrigation, and road networks. Not only is the conversion impacting the rice production in the Regency, but also the reduction in workers in farming due to the industrial development. Changing land from paddy to industrial activities entails a change in the profession of local farmers due to high wages [6, 17, 18]. Therefore, the present study was undertaken with the objective of analysing 1) Karawang rice availability per person, 2) rice surplus and 3) rice self-sufficiency level via simulating different scenarios of System Dynamic Modelling.
Rapid economic growth is usually correlated with shifts in land use. The continued increase in economic and population growth, especially in the developing world, leads to an increase in the demand for land as input in the production process or consumption goods. Considering that the land extent is fixed, continuing economic growth and population pressure indicate that land use change is inevitable [19, 20]. Land conversion emerges as the result of the interaction between human activities and biophysical processes. It can be defined as the change in land use from a particular function to another function [20, 21]. Irene et al. [22] stated that the crucial land use drivers are population size, the density of regional land, economic conditions, values, and applied land use strategy. Cakranegara and Zhou et al. [20, 23] argued that land with strategic location, e.g., its proximity to road infrastructure and irrigation network prime cropland, becomes the typical victim of land conversion.
The history of land conversion in Indonesia is back to 1980 when the central government intended to open new avenues for investment and attract investors' capital [20, 24]. Specifically, in Karawang, it started in early 1990 when the local government of Karawang Regency adopted a new Regional Development Plan, placing the industrial sectors as a complementary economic driver to the agricultural sector. Consequently, land demand for non-agricultural economic activities, e.g., industrial, has increased due to new reforms, impacting the forest and agricultural lands and putting the nation's food security at stake. The impact of land conversion on paddy fields in Karawang is more significant than in other sectors. However, PFs conversion and its impacts on rice supply and self-sufficiency represent a complex problem involving more than one bioeconomic subsystem (i.e., rice demand system, rice production system).
A holistic approach such as System Dynamics Modelling (SDM) is needed to address such a problem and deal with the complexity of a whole system and visualise the impacts of PFs conversions. SDM is a feedback concept methodology that handles complex dynamic systems' non-linearity, multi-loop, and time-lag characteristics. It can be applied to model and simulate such complex dynamic systems to understand the dynamics of systems and design management policy for sustainable development [25]. According to Purwanto et al. and Borras Jr et al. [2, 25] the development of SD modelling starts with problem identification, crafting conceptual models, and qualitative Causal Loop Diagrams (CLDs), which are later translated into a quantitative model using Stocks Flow Diagrams (SFDs). CLDs and SFDs are believed to be complementary in the Analysis of SDM. CLD help identifies the system's most important, secondary, and tertiary elements. It defines the primary connection of the system components via cause-effect relationships. This gives a qualitative understanding of the system's structure. Thus, very useful in understanding the system behaviours and the potential impact of imposed policy. SFD is quantitatively underlying the system's physical structure in terms of Stock and flow [25]. It is the process in which the element identified in CLDs will be quantified and simulated, where it represents integral finite difference equations variables of the feedback loop structure of the system and simulates the dynamics behaviours.
Numerous researchers have used the SD Modelling for food production-related issues; Bala et al. [26] have used the system approach to simulate different scenarios for rice supply in South Sulawesi Provence. Sofyang et al. [27] used system dynamics to simulate scenarios and formulate policy recommendations for developing management to achieve self-sufficiency in rice in Indonesia. Fristovana et al. [28] developed system dynamics to evaluate the effects of biofuel production on food security in Colombia by analysing agro-food, livestock, and biofuel production. Furthermore, Martínez-Jaramillo et al. [29] used system dynamics to set up policy scenarios by adjusting the parameters and variables to model the economy nitrogen resource environment of the typical agricultural and pastoral area. Wang et al. [30] built CLD and SFD to investigate the influential factors in the Wheat production system and analyse them via a systematic approach to develop a food sustainability framework. Amiri et al. [31] used SD modelling to examine the interaction and drivers of the economic environment and social sustainability of the agricultural production system.
Based on the available sources, no published research has used system dynamics modelling to visualize and project the impact of paddy field conversion and population growth on Karawang rice production, i.e., Walters et al. [32] used SDM to develop causal loop mapping of Water Energy Food (WEF) security nexus. Purwanto et al. [2] converted the modelled causal loop into a quantitative simulation of WEF security. These studies focused on WEF sectors as whole not food sectors separately. The food sector did not focus on rice alone yet included other crops. Since rice is a staple food in the country and the Regency is obligated to supply 1.5 million tons of rice surplus to support national food security, the impacts of conversion and population need to be examined. In order to address this gap, this study aimed to use SDM to discuss the effect of rice PFs conversion on the Karawang rice supply, surplus, and availability per person.
3.1 Stock-flow diagrams (SFD)
SFD representing the feedback structure of the system captures the hypothesis about the cause of dynamics and the essential feedback [2]. It consists of Stock, flows, and convertors (auxiliaries) as well as defining the system boundaries. Generally, materials used to be represented as stocks, and changes occur due to the flow of the materials into or out of Stock. The movement of material into or out of Stock is a function of the flows. On the other hand, convertors act to influence flow rates. Such objects are linked by connectors, which transfer information from the feedback to the model. Thus, due to its dynamic and complex structures, non-linearity, delays, and feedback emerge. Positive feedback generating growth, negative feedback goal-seeking, and dynamic equilibrium (oscillation) are the most basic behaviours of the observed system [2, 25]. SFD represents the Karawang rice self-sufficiency model (KRS2M) in this study, developed in Powersim Studio 10 Express (www.powersim.com).
3.2 Study area
The study was conducted in Karawang Regency, West Java Province. It covers an area of 1,753.27 km 2 (Figure 1).
It's known as a regional industrial activities area and an economic centre. It is surrounded by cities such as Jakarta, Bogor, Depok, Tangerang Bekasi, and Bandung. The Regency is populated by 2,44 million and consists of thirty sub-districts comprised of 297 villages and 12 special villages. Regionally, Karawang used to be divided into two major landscapes, namely lowland and coastal areas in the northern part with elevations ranging from 0 to 50 m and a hilly area in the southern part with elevations from 50 to 1,291 m above mean sea level [34].
Figure 1. The study area map
3.3 Study tools, materials, and data
The tools used in this study are; a laptop equipped with Microsoft Office packed 2019 and Powersim Studio10.
Table 1. The main data types and descriptions
While the materials/data used are paddy fields conversion figures published by Suliman and Setiawan [15], population and rice production data published by Karawang and west Java Province statistical bureau (BPS) between 2009 -2019 were used (see Table 1).
3.4 Model development steps/ procedures
Vlachos et al. [35] stated that to demonstrate how a system dynamics model is constructed, it is necessary to identify the stakeholders, their needs, and problem formulation, delineate the system, model, verify and validate the outputs of the designed system and policy simulation (see Figure 3).
a. Problem Formulation
Population growth and development entail increased land need for settlements and other non-agricultural economic activities. In turn, the increased needs for land contribute to increasing the rate of agricultural land, including paddy fields. While the increased population growth will increase the total food demand as well as food per capita. Such conditions jeopardize the efforts of the government and communities to secure food. The government adopted Law No 41, 2009, to delineate Paddy fields and protect the agricultural land. The report BPS-Statistics of Karawang Regency [11] stated that such efforts are ineffective in reducing the conversion rate of paddy fields and their impact on future food security.
b. Identification of Stakeholders and Needs Analysis
Based on the problem that the system will address, stakeholders' opinions and needs should be considered via focus group discussions/interviews to justify their views on the existing problems, observations of the data collected, and proposed solutions [24]. The information regarding this step was obtained from the literature and official reports.
c. System Identification
System identification aims to describe the system being studied in diagrammatic form (CLD and SFD).
POP : Population, TB : Total Birth, TD : Total Death, TFC : Total Food Consumption, TRC : Total Rice Consumption: LRP : Local Rice Production, TRP : Total Rice Production, TLD : Total Land Demand, NDCC : Natural Disaster & Climate Change, LULCC : Land Use Land Cover Change, V-RTRW : Violation of RTRW, AWF : Agriculture Work Force, TCA : Total Cultivated Area, THA : Total harvested Area, IP : Increased Productivity, EGR : Effective government Regulations, SGS : Sufficient Government Subsides,
Figure 2 . CLD of model. The green arrows represent positive causalities (i.e., a change in variable X causes a change in variable Y in the same direction), while the red arrows indicate negative
Major subsystems and their relationships within and between the subsystems of the system as a whole are clearly described in Figure 2 as the Causal Loop Diagram (CLD).
d. Model Testing and Validation
Model testing is a critical part of the modelling process that helps build confidence in the model and its insights. The model output validation was conducted based on the available data, i.e., population, by using equations in Table 2.
a. Policy simulation /Model sensitivity and scenario analysis
The study chooses two variables, the birth rate of Karawang and the paddy fields conversion rate, to examine the model sensitivity against the analysed indexes; rice available per person (APP), rice surpuls (SPs) and Self-sufficiency level (SSL), as illustrated in Table 3. Additionally, the study proposed four policy scenarios to analyse (Table 4), comprising of; (1) business as usual (BAU#); (2) assuming TCA are designated by RTRW and using the conversion rate within RTRW (SNO#2); (3) increase in rice demand due to increasing in per capita per month average expenditure on rice and using a predicted conversion rate (SNO#3); and (4) assuming TCA are designated by LP2B and predicted conversion rates.
Table 2. summary of statistical measures to test the model behaviour
Table 3. Index analysed in the stock flow diagram
F igure 3. Model development steps modified from [2]
Table 4. Model sensitivity and policy scenario analysis
4.1 Model structure
The model's Stock Flow Diagram (SFD) has been developed using PowerSim studio 10. The SFD consisted of four subsystems. Two are endogenous; Rice Production (dark green) and Rice demand (orange) (Figure 4). This quantified SFD is based on the qualitative CLD. The exogenous factors drive the change of this model, and it comprises population (red) and Total land demand (TLD) (dark brown) sub-models. Structurally, models include; 2 stocks, two inflows with rate, three outflows with rate, 15 constant tools, and 14 auxiliaries. Not all qualitative variables of CLD are covered in quantitative SFD due to data limitations of data availability/accessibility.
4.2 Model behaviours
The study tested model behaviours by comparing the simulated data with actual data (2009-2019) to assess how well the model outputs replicate observed system behaviour. Based on the available data, Population data, Paddy cultivated area and rice production were chosen to be tested. The test shows satisfactory agreement between the model simulation and the actual data in terms of percentage, absolute numbers, and trends in all test variables (Table 5 and Figure 5) except harvested area data (Figure 5b), which shows lower agreement due to a various data sources used. The overall results indicated that the model demonstrated adequacy in capturing the actual system behaviours that support further scenario analysis.
POP_KRW ; Population of Karawang, Fr ; fraction, Adults ; people aged 4+ years old, TDL ; Total Land Demand, TRD ; Total Rice Demand, LULCC ; Land use Land Cover Change, CI ; Cropping Index, TCA ; Total Cultivated Area, THA ; Total Harvested Area, TRP ; Total Rice Production, SPs ; Surplus, SSL ; Self-sufficiency Level, APP ; Availability Per Person.
Figure 4. SFD model. Square boxes indicate stocks, thick arrows with ‘clouds’ indicate flows, and circles indicate connectors (auxiliary variables). Thin connecting arrows transmit information between model elements
Table 5. Testing Model behaviours of selected variable (2009-2019)
Figure 5. Model validation: a) Karawang population; b) harvested area; and c) Rice production
4.3 Model limitations
The tailored model is based on the ten years' assessment of paddy fields conversion data and prediction to 2031 in line with current Regional Spatial Planning (RTRW). The model sets to run from 2019 (baseline) to the end of the century (2100) with a setting report every three years. Since it is based on the ten years of assessment data, the projection figures might only be reliable up to 2031. The projection data might also be reliable over the next RTRW period (2031-2051) if there is no significant change in the Regency paddy fields area, conversion rate, population growth, and rice consumption.
4.4 Sensitivity analysis
Figure 6 shows the sensitivity analysis results. Such analysis aimed to build confidence in the system dynamic model by testing the model output on how it reflects reality. However, changes in population sub-system components e.g., an increase in birth should be reflected in form of an increase in the total rice demand. Also changes in the rice production sub-system components e.g., an increase or decrease in the local rice supply should be a direct response to a reduction in the paddy cultivated area due to paddy fields conversion, cropping index, or productivity. Such analysis chooses birth rate (TSNY#1) and conversion rate (TSNY#3) variables to examine the sensitivity of the system. As shown in Table 4 it assumes that the values of the variables will increase by 30% and 50% and decrease by the same percentages.
Hence, based on the simulations (TSNY#1a to TSNY#1d), changes in birth rate have significantly altered Availability Per Person (APP). Meaning that increase in birth by 50% has resulted in an increase of the rice demand by the same percentage and consequently reduced the rice APP and vice versa. While changes in conversion rate (TSNY#3a to TSNY#3a) will impact the cultivated/harvested area and rice production, thus rice supply. The results indicated that the model captured the reality of system components interacting in the real world. Hence, supporting policy scenarios.
Figure 6. Sensitivity analysis: a) availability per person; b) total cultivated/ harvested area; c) rice supply
4.5 Analysis of policies scenarios
4.5.1 Business as usual (BAU#1)
The model sits to run from 2019 to 2100 with a report setting of every three years. Under the business-as-usual scenario (Figure 7), the model shows the inversion proportionality of rice demand and supply. It shows that the population of the Karawang regency increased from 2,354,000 million in 2019 to 6,150,266 million by end of the century, representing an increase of 161.269% from the baseline (2019). This increase in the population represents an average of 1.4 per cent/year growth of population during the first thirty years (2019-2049) mainly due to the increase of birth and immigration into the regency as its industrial area attracts a workforce.
Figure 7. BAU#1 scenario: a) APP; b) surplus (SPs), Total Rice Supply (TRS), and Total Rice Demand (TRD); c) SSL
Due to this increase, the Total Rice Remand (TRD) of the Karawang population will increase from 356.8 thousand (K) in 2019 to roughly 0.9 million tons by the end of the century. On the other hand, the paddy fields area of Regency will be reduced from 191.5K ha in 2019 to 169.4K ha in 2100. This represents a reduction of 22.1K ha or 161%; as a result, the rice production/ Total Rice Supply (TRS) will drop from 1.9 million tons in 2019 to 1.7 million tons at the end of the century, as shown in Figure 7 b. The main driver of reducing production/supply is the paddy fields conversion. Consequently, the Availability Per Person (APP), rice surplus (SPs), and Self-sufficiency level (SSL) will be reduced by 66.20, 50.55, and 359%, respectively, between 2019-2100, as shown in Figure 7.
4.5.2 RTRW scenario (SNO#2)
Based on the previous study conducted by [15] show that the paddy field conversion rate is lower within the paddy fields area designated by the 2013 Karawang regional spatial planning (RTRW) and much higher outside that area. Hence, in this scenario, the study assumes the total paddy fields are those within RTRW and uses different conversion rates within the same area. This scenario highlighted that if the PFs conversion rate within the RTRW area increases by 30% (SNO#2.1) then paddy fields will be reduced from 89.2K ha in 2019 to just 60K ha by the end of the century, approximately 29K ha of paddy fields will be converted. While increasing the conversion rate within the same area by 50% (SNO#2.2) will reduce paddy fields of the area from 89.2K ha in 2019 to just 54K ha by the end of the century, a reduction of 32.9K ha. On the other hand, reducing the conversion rate by 30% (SNO#2.3) will reduce PFs from 89.2K ha to 71 thousand ha in the end, only 18K ha of PFs will be converted. Whereas a reduction of conversion rate by 50% (SNO#2.4) will reduce the PFs from 89.2K ha to 74.8K ha or a conversion of 14.4K ha by end of the century.
The SNO# scenario shows that SNO#2.1 will reduce KRW APP, SPs, and SSL by 7.96, 28.84, and 12.10%, respectively, from baseline. SNO#2.2 scenario showed APP (Figure 8 a), SPs (Figure 8 b), and (Figure 8 c) SSL would reduce by 14.16, 47.20, and 20.10%, respectively, from baseline. In comparison, SNO#2.3 will increase APP, SPs, and SSL of Regency by 8.85, 28.48, and 12.10%, respectively, from baseline. While the SNO#2.4 scenario will increase APP, SPs, and SSL of KRW by 14.16, 47.20, and 20.10%, respectively, from baseline.
Figure 8. SNO#2: a) APP; b) Surplus (SPs); c) SSL
4.5.3 Increased rice demand scenario (SNO#3)
In this scenario, the model aimed to assess the impact of change in rice consumption/demand relative to APP, SPs, and SSL, assuming that the rice demand will increase by 30% to 100%. The 100% increase would represent an upper limit of increase. There are two logical reasons behind this assumption; I) the BPS report shows an increase in per capita per year income, and II) the reports also show that per capita expenditure has increased by 50.82 % between 2009-2019.
Thus, when income increases, disposable income rises, and people consume more goods & services.
The simulation revealed that increasing per capita monthly rice average expenditure (PRE) by 30% (SNO#3.1) would increase the Total Rice Demand (TRD) from 231.9K tons in 2019 to 605.8K tons, in the end, an increment of 373.9K ton. Increasing PRE by 50% (SNO#3.2) will increase the TRD from 267.5K to 699.1K tons or an increase of 431.5K tons. Increasing PRE by 80% (SNO#3.3) would increase TRD from 321K to 838.9K tons, an increment equivalent to 517.8K tons. Whereas an increase in PRE by 100% (SNO#3.4) will increase the regency TRD from 356.7K to 932.1K tons. Therefore, SNO#3.1 would increase KRW SPs (Figure 9 b) and SSL (Figure 9 c) by 49.80 and 36.90%, respectively, from baseline. Whereas SNO#3.2 will increase SPs, and SSL by 88.99, and 53.40%, respectively, from baseline. Conversely, SNO#3.3 will increase SPs and SSL by 132.79 and 71.20%, respectively, from baseline. SNO#3.4 will increase SPs and SSL by 165.99 and 80.10%, respectively, from baseline. Because the change in population growth and reduction of paddy fields remained the same, the scenario did not show any change/significant trends in APP measure shown in Figure 9 a. the model also showed that the Regency will be out of rice surplus when in 2094 and 2085 when the consumption/ demand of rice increases by 80 and 100% respectively.
Figure 9. a) APP; b) Surplus (SPs); c) SSL
4.5.4 LP2B scenario (SNO#4)
This scenario used the area of LP2B paddy fields and future conversion rate within the production sub-models. It aims to project the possible scenario of APP, SSL, and SPs based on the LP2B paddy area. It assumes that the future paddy fields conversion rate within such area will increase by 30% (0.0168) SNO#4.1, and 50% (0.0194) SNO#4.2, and also decrease by 30% (0.0090) SNO#4.3, and 50% (0.00645) SNO#4.4. An increase in conversion rate means reducing the available paddy field, less cultivated area, and thus less rice production, and vice versa.
Therefore, the simulation revealed that SNO#4.1 will reduce KRW PFs by 13.3K ha by end of the simulation or an increase of 3.1K ha from the baseline. Thus, such a scenario would increase KRW rice SSL, APP, and SPs by 1.24, 1.14, and 3.92%, respectively (Figure 10), from the baseline. SNO#4.2 will reduce the PFs of KRW by 15.4K or will increase the PFs converted area by 5.1K ha from the baseline. Hence, it will increase rice SSL, APP, and SPs by 2.06, 2.06, and 6.54%. In contrast, SSL will decline by 1.22 and 2.02% (Figure 10 c) due to the reduction of PFs by 3.1K and 5.1K ha induced by scenario SNO#4.3 and SNO#4.4 respectively. And they will reduce APP (Figure 10 a) by 1.37 and 2.06%, (Figure 10 b), and also will reduce the Regency rice surplus by 3.92 and 6.49 respectively. Scenarios SNO#4.2 and SNO#4.2 have significant impacts, especially on the rice surplus. It means an increase in conversion rate by 50% within the LP2B area will reduce the rice surplus by 443,880.44 tons and 52,329.00 from the baseline by the end of the century. Conversely, a reduction in the conversion rate by 50% will increase the KRW rice surplus by 339,624.96 tons and 51,926.48 tons from the baseline. The change in the surplus due to Scenarios SNO#4.2 and SNO#4.2 is almost equal to 30% of Karawang rice demand. In other words, the change in surplus is enough to meet the demand of 657 thousand people, which is equivalent to the demand of six sub-districts (kacamatan) complained, namely, Tegalwaru, Ciampel, Telukjambe Timur, Klari, Cikampek, and Kotabaru.
Figure 10. SNO#4: a) APP; b) Surplus (SPs); c) SSL
4.6 Policy implication and possible interventions
Table 6 summarizes the policies and their main implications and possible practical action to be taken regarding paddy field conversion and how food production can be sustained. It highlighted two main concerns; I) the implications of various simulated policies on the different sub-models. II) possible practical actions. Where all the indicated implications are based on the simulation of the model, whereas the proposed measures in "possible practical actions" are based on the simulated scenarios and other sources such as previous studies, experts, and modellers' opinions. Hence, there are various implications of simulated scenarios/policies towards APP, SPs, and SSL. Generally, an increase in land conversion and population growth rate led to a decrease (↓) of measured parameters. In contrast, increased demand decreased SPs and SSL with no significant effect on APP (Table 6). To deal with the undesirable implication of the land sub-model, means of optimizing/controlling paddy field conversion should be considered. This means reducing the conversion rate to a level that does not significantly impact the APP, SLL, and SPs. The conversion rate must be kept at least 50% less than the current conversion rate (1% per year) and less than 0.5% per year within the RTRW area to achieve the target of sustainable protected agricultural land (LP2B). Paddy field conversion due to the horizontal expansion of settlements within the farmland can be optimized by adopting the vertical settlement plan. However, densification of the rural non-farm settlements will play an important role in controlling the horizontal expansion of non-farm occupations (i.e., construction of industry, housing, brickfield etc.), which is impacting the conversion of agricultural land, particularly paddy fields, and this is in line with what Alam et al. [36] argued about the 2011 Bangladesh Agricultural Land Protection & Land Use Bill. Paddy field conversions within the designated areas indicate that there is a violation of regulations (RTRW) via land use permit. Therefore, further measures such as linking the land use permit with the regional spatial planning (RTRW) should be taken into account to enforce the law, stop the RTRW violation, and thus, control paddy fields conversion within such area.
According to Chofyan et al. [37], a good functioning irrigation network is a supportive factor in obtaining optimal production and productivity. Its absence may become a conversion driver. The study stated that in 2015 almost 82% of Regency irrigation networks were identified as damaged; out of that, 55% of them were severely damaged, 27% were moderately damaged, and only 18% were slightly damaged.
Paddy fields located near damaged irrigation canals are characterized by low production. Thus, they have the potential to be converted because farmers/ landowners seeking high income from their land and low-productive paddy fields take more input but bring low income compared to other non-farm investments. Hence, maintaining and keeping the irrigation canals in good condition will ensure adequate irrigation water delivery to meet the production/productivity targets and reduce the odds of conversions.
Although there is no deficiency of rice supply in Karawang Regency due to the paddy fields conversion, measures such as family planning and food diversification will help reduce pressure on the rice surplus from Karawang. Since the Regency is known as the second-largest rice producer in the province and is called "lumbung padi nasional" its rice supply is not only for Karawang but for the whole of West Java Province. Hence, a family planning policy will not only control the growth of the population, which impacts the conversion process but also help reduce the pressure on the demand for rice alongside food diversification plans.
Table 6. Police implication and possible interventions
Notes: ↑ (increasing trend), ↓ (decreasing trend), → (less or no influence), LP2B (sustainable food crop agriculture land policy), RTRW (Regional Spatial Planning), ∗ (model-based), ∗∗ (other evidence-based).
The study has aimed to develop a dynamic model and analyse possible future scenarios to support the formulation of recommendations/policies to uphold the rice self-sufficiency of the Regency. This has been done by visualizing the threats and challenges. Based on the model simulations, the study can successfully build a model reflecting the real system. The results illustrated the current and future status of rice self-sufficiency in the Karawang Regency. It has been emphasised that paddy field conversion is the main threat that may undermine the future rice supply for Regency. On the other hand, population growth and /or change in consumption patterns will also alter the rice demand, thus impacting APP, SPs, and SSL on the Regency level.
Based on the above conclusions, the study recommended that proposed possible interventions should be considered along with formulating and implementing upcoming Regional Short, Medium, and long-term Development Plans. Development practitioners, policy, and decision-makers can use this model, including the generated information in evaluating and planning future food security policies with particular attention to the threat imposed by scenarios SNO#3.3 and SNO#3.4. Further research should consider enough historical data e.g., +20 years for more accurate simulation to overcome the limitation of this model. They also should take into account the increased cultivated area which increases due to the conversion from forests and bare land into paddy fields. Thus more reasonable projections and policy scenarios.
The authors would like to acknowledge the financial assistance provided by the government of Indonesia through the Ministry of Education and Culture and IPB University. They also would like to thank the University Consortium of SEARCA for their financial support. This work would not be accomplished without such aid.
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The case study approach
- Sarah Crowe 1 ,
- Kathrin Cresswell 2 ,
- Ann Robertson 2 ,
- Guro Huby 3 ,
- Anthony Avery 1 &
- Aziz Sheikh 2
BMC Medical Research Methodology volume 11 , Article number: 100 ( 2011 ) Cite this article
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The case study approach allows in-depth, multi-faceted explorations of complex issues in their real-life settings. The value of the case study approach is well recognised in the fields of business, law and policy, but somewhat less so in health services research. Based on our experiences of conducting several health-related case studies, we reflect on the different types of case study design, the specific research questions this approach can help answer, the data sources that tend to be used, and the particular advantages and disadvantages of employing this methodological approach. The paper concludes with key pointers to aid those designing and appraising proposals for conducting case study research, and a checklist to help readers assess the quality of case study reports.
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Introduction
The case study approach is particularly useful to employ when there is a need to obtain an in-depth appreciation of an issue, event or phenomenon of interest, in its natural real-life context. Our aim in writing this piece is to provide insights into when to consider employing this approach and an overview of key methodological considerations in relation to the design, planning, analysis, interpretation and reporting of case studies.
The illustrative 'grand round', 'case report' and 'case series' have a long tradition in clinical practice and research. Presenting detailed critiques, typically of one or more patients, aims to provide insights into aspects of the clinical case and, in doing so, illustrate broader lessons that may be learnt. In research, the conceptually-related case study approach can be used, for example, to describe in detail a patient's episode of care, explore professional attitudes to and experiences of a new policy initiative or service development or more generally to 'investigate contemporary phenomena within its real-life context' [ 1 ]. Based on our experiences of conducting a range of case studies, we reflect on when to consider using this approach, discuss the key steps involved and illustrate, with examples, some of the practical challenges of attaining an in-depth understanding of a 'case' as an integrated whole. In keeping with previously published work, we acknowledge the importance of theory to underpin the design, selection, conduct and interpretation of case studies[ 2 ]. In so doing, we make passing reference to the different epistemological approaches used in case study research by key theoreticians and methodologists in this field of enquiry.
This paper is structured around the following main questions: What is a case study? What are case studies used for? How are case studies conducted? What are the potential pitfalls and how can these be avoided? We draw in particular on four of our own recently published examples of case studies (see Tables 1 , 2 , 3 and 4 ) and those of others to illustrate our discussion[ 3 – 7 ].
What is a case study?
A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table 5 ), the central tenet being the need to explore an event or phenomenon in depth and in its natural context. It is for this reason sometimes referred to as a "naturalistic" design; this is in contrast to an "experimental" design (such as a randomised controlled trial) in which the investigator seeks to exert control over and manipulate the variable(s) of interest.
Stake's work has been particularly influential in defining the case study approach to scientific enquiry. He has helpfully characterised three main types of case study: intrinsic , instrumental and collective [ 8 ]. An intrinsic case study is typically undertaken to learn about a unique phenomenon. The researcher should define the uniqueness of the phenomenon, which distinguishes it from all others. In contrast, the instrumental case study uses a particular case (some of which may be better than others) to gain a broader appreciation of an issue or phenomenon. The collective case study involves studying multiple cases simultaneously or sequentially in an attempt to generate a still broader appreciation of a particular issue.
These are however not necessarily mutually exclusive categories. In the first of our examples (Table 1 ), we undertook an intrinsic case study to investigate the issue of recruitment of minority ethnic people into the specific context of asthma research studies, but it developed into a instrumental case study through seeking to understand the issue of recruitment of these marginalised populations more generally, generating a number of the findings that are potentially transferable to other disease contexts[ 3 ]. In contrast, the other three examples (see Tables 2 , 3 and 4 ) employed collective case study designs to study the introduction of workforce reconfiguration in primary care, the implementation of electronic health records into hospitals, and to understand the ways in which healthcare students learn about patient safety considerations[ 4 – 6 ]. Although our study focusing on the introduction of General Practitioners with Specialist Interests (Table 2 ) was explicitly collective in design (four contrasting primary care organisations were studied), is was also instrumental in that this particular professional group was studied as an exemplar of the more general phenomenon of workforce redesign[ 4 ].
What are case studies used for?
According to Yin, case studies can be used to explain, describe or explore events or phenomena in the everyday contexts in which they occur[ 1 ]. These can, for example, help to understand and explain causal links and pathways resulting from a new policy initiative or service development (see Tables 2 and 3 , for example)[ 1 ]. In contrast to experimental designs, which seek to test a specific hypothesis through deliberately manipulating the environment (like, for example, in a randomised controlled trial giving a new drug to randomly selected individuals and then comparing outcomes with controls),[ 9 ] the case study approach lends itself well to capturing information on more explanatory ' how ', 'what' and ' why ' questions, such as ' how is the intervention being implemented and received on the ground?'. The case study approach can offer additional insights into what gaps exist in its delivery or why one implementation strategy might be chosen over another. This in turn can help develop or refine theory, as shown in our study of the teaching of patient safety in undergraduate curricula (Table 4 )[ 6 , 10 ]. Key questions to consider when selecting the most appropriate study design are whether it is desirable or indeed possible to undertake a formal experimental investigation in which individuals and/or organisations are allocated to an intervention or control arm? Or whether the wish is to obtain a more naturalistic understanding of an issue? The former is ideally studied using a controlled experimental design, whereas the latter is more appropriately studied using a case study design.
Case studies may be approached in different ways depending on the epistemological standpoint of the researcher, that is, whether they take a critical (questioning one's own and others' assumptions), interpretivist (trying to understand individual and shared social meanings) or positivist approach (orientating towards the criteria of natural sciences, such as focusing on generalisability considerations) (Table 6 ). Whilst such a schema can be conceptually helpful, it may be appropriate to draw on more than one approach in any case study, particularly in the context of conducting health services research. Doolin has, for example, noted that in the context of undertaking interpretative case studies, researchers can usefully draw on a critical, reflective perspective which seeks to take into account the wider social and political environment that has shaped the case[ 11 ].
How are case studies conducted?
Here, we focus on the main stages of research activity when planning and undertaking a case study; the crucial stages are: defining the case; selecting the case(s); collecting and analysing the data; interpreting data; and reporting the findings.
Defining the case
Carefully formulated research question(s), informed by the existing literature and a prior appreciation of the theoretical issues and setting(s), are all important in appropriately and succinctly defining the case[ 8 , 12 ]. Crucially, each case should have a pre-defined boundary which clarifies the nature and time period covered by the case study (i.e. its scope, beginning and end), the relevant social group, organisation or geographical area of interest to the investigator, the types of evidence to be collected, and the priorities for data collection and analysis (see Table 7 )[ 1 ]. A theory driven approach to defining the case may help generate knowledge that is potentially transferable to a range of clinical contexts and behaviours; using theory is also likely to result in a more informed appreciation of, for example, how and why interventions have succeeded or failed[ 13 ].
For example, in our evaluation of the introduction of electronic health records in English hospitals (Table 3 ), we defined our cases as the NHS Trusts that were receiving the new technology[ 5 ]. Our focus was on how the technology was being implemented. However, if the primary research interest had been on the social and organisational dimensions of implementation, we might have defined our case differently as a grouping of healthcare professionals (e.g. doctors and/or nurses). The precise beginning and end of the case may however prove difficult to define. Pursuing this same example, when does the process of implementation and adoption of an electronic health record system really begin or end? Such judgements will inevitably be influenced by a range of factors, including the research question, theory of interest, the scope and richness of the gathered data and the resources available to the research team.
Selecting the case(s)
The decision on how to select the case(s) to study is a very important one that merits some reflection. In an intrinsic case study, the case is selected on its own merits[ 8 ]. The case is selected not because it is representative of other cases, but because of its uniqueness, which is of genuine interest to the researchers. This was, for example, the case in our study of the recruitment of minority ethnic participants into asthma research (Table 1 ) as our earlier work had demonstrated the marginalisation of minority ethnic people with asthma, despite evidence of disproportionate asthma morbidity[ 14 , 15 ]. In another example of an intrinsic case study, Hellstrom et al.[ 16 ] studied an elderly married couple living with dementia to explore how dementia had impacted on their understanding of home, their everyday life and their relationships.
For an instrumental case study, selecting a "typical" case can work well[ 8 ]. In contrast to the intrinsic case study, the particular case which is chosen is of less importance than selecting a case that allows the researcher to investigate an issue or phenomenon. For example, in order to gain an understanding of doctors' responses to health policy initiatives, Som undertook an instrumental case study interviewing clinicians who had a range of responsibilities for clinical governance in one NHS acute hospital trust[ 17 ]. Sampling a "deviant" or "atypical" case may however prove even more informative, potentially enabling the researcher to identify causal processes, generate hypotheses and develop theory.
In collective or multiple case studies, a number of cases are carefully selected. This offers the advantage of allowing comparisons to be made across several cases and/or replication. Choosing a "typical" case may enable the findings to be generalised to theory (i.e. analytical generalisation) or to test theory by replicating the findings in a second or even a third case (i.e. replication logic)[ 1 ]. Yin suggests two or three literal replications (i.e. predicting similar results) if the theory is straightforward and five or more if the theory is more subtle. However, critics might argue that selecting 'cases' in this way is insufficiently reflexive and ill-suited to the complexities of contemporary healthcare organisations.
The selected case study site(s) should allow the research team access to the group of individuals, the organisation, the processes or whatever else constitutes the chosen unit of analysis for the study. Access is therefore a central consideration; the researcher needs to come to know the case study site(s) well and to work cooperatively with them. Selected cases need to be not only interesting but also hospitable to the inquiry [ 8 ] if they are to be informative and answer the research question(s). Case study sites may also be pre-selected for the researcher, with decisions being influenced by key stakeholders. For example, our selection of case study sites in the evaluation of the implementation and adoption of electronic health record systems (see Table 3 ) was heavily influenced by NHS Connecting for Health, the government agency that was responsible for overseeing the National Programme for Information Technology (NPfIT)[ 5 ]. This prominent stakeholder had already selected the NHS sites (through a competitive bidding process) to be early adopters of the electronic health record systems and had negotiated contracts that detailed the deployment timelines.
It is also important to consider in advance the likely burden and risks associated with participation for those who (or the site(s) which) comprise the case study. Of particular importance is the obligation for the researcher to think through the ethical implications of the study (e.g. the risk of inadvertently breaching anonymity or confidentiality) and to ensure that potential participants/participating sites are provided with sufficient information to make an informed choice about joining the study. The outcome of providing this information might be that the emotive burden associated with participation, or the organisational disruption associated with supporting the fieldwork, is considered so high that the individuals or sites decide against participation.
In our example of evaluating implementations of electronic health record systems, given the restricted number of early adopter sites available to us, we sought purposively to select a diverse range of implementation cases among those that were available[ 5 ]. We chose a mixture of teaching, non-teaching and Foundation Trust hospitals, and examples of each of the three electronic health record systems procured centrally by the NPfIT. At one recruited site, it quickly became apparent that access was problematic because of competing demands on that organisation. Recognising the importance of full access and co-operative working for generating rich data, the research team decided not to pursue work at that site and instead to focus on other recruited sites.
Collecting the data
In order to develop a thorough understanding of the case, the case study approach usually involves the collection of multiple sources of evidence, using a range of quantitative (e.g. questionnaires, audits and analysis of routinely collected healthcare data) and more commonly qualitative techniques (e.g. interviews, focus groups and observations). The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[ 8 , 18 – 21 ]. An underlying assumption is that data collected in different ways should lead to similar conclusions, and approaching the same issue from different angles can help develop a holistic picture of the phenomenon (Table 2 )[ 4 ].
Brazier and colleagues used a mixed-methods case study approach to investigate the impact of a cancer care programme[ 22 ]. Here, quantitative measures were collected with questionnaires before, and five months after, the start of the intervention which did not yield any statistically significant results. Qualitative interviews with patients however helped provide an insight into potentially beneficial process-related aspects of the programme, such as greater, perceived patient involvement in care. The authors reported how this case study approach provided a number of contextual factors likely to influence the effectiveness of the intervention and which were not likely to have been obtained from quantitative methods alone.
In collective or multiple case studies, data collection needs to be flexible enough to allow a detailed description of each individual case to be developed (e.g. the nature of different cancer care programmes), before considering the emerging similarities and differences in cross-case comparisons (e.g. to explore why one programme is more effective than another). It is important that data sources from different cases are, where possible, broadly comparable for this purpose even though they may vary in nature and depth.
Analysing, interpreting and reporting case studies
Making sense and offering a coherent interpretation of the typically disparate sources of data (whether qualitative alone or together with quantitative) is far from straightforward. Repeated reviewing and sorting of the voluminous and detail-rich data are integral to the process of analysis. In collective case studies, it is helpful to analyse data relating to the individual component cases first, before making comparisons across cases. Attention needs to be paid to variations within each case and, where relevant, the relationship between different causes, effects and outcomes[ 23 ]. Data will need to be organised and coded to allow the key issues, both derived from the literature and emerging from the dataset, to be easily retrieved at a later stage. An initial coding frame can help capture these issues and can be applied systematically to the whole dataset with the aid of a qualitative data analysis software package.
The Framework approach is a practical approach, comprising of five stages (familiarisation; identifying a thematic framework; indexing; charting; mapping and interpretation) , to managing and analysing large datasets particularly if time is limited, as was the case in our study of recruitment of South Asians into asthma research (Table 1 )[ 3 , 24 ]. Theoretical frameworks may also play an important role in integrating different sources of data and examining emerging themes. For example, we drew on a socio-technical framework to help explain the connections between different elements - technology; people; and the organisational settings within which they worked - in our study of the introduction of electronic health record systems (Table 3 )[ 5 ]. Our study of patient safety in undergraduate curricula drew on an evaluation-based approach to design and analysis, which emphasised the importance of the academic, organisational and practice contexts through which students learn (Table 4 )[ 6 ].
Case study findings can have implications both for theory development and theory testing. They may establish, strengthen or weaken historical explanations of a case and, in certain circumstances, allow theoretical (as opposed to statistical) generalisation beyond the particular cases studied[ 12 ]. These theoretical lenses should not, however, constitute a strait-jacket and the cases should not be "forced to fit" the particular theoretical framework that is being employed.
When reporting findings, it is important to provide the reader with enough contextual information to understand the processes that were followed and how the conclusions were reached. In a collective case study, researchers may choose to present the findings from individual cases separately before amalgamating across cases. Care must be taken to ensure the anonymity of both case sites and individual participants (if agreed in advance) by allocating appropriate codes or withholding descriptors. In the example given in Table 3 , we decided against providing detailed information on the NHS sites and individual participants in order to avoid the risk of inadvertent disclosure of identities[ 5 , 25 ].
What are the potential pitfalls and how can these be avoided?
The case study approach is, as with all research, not without its limitations. When investigating the formal and informal ways undergraduate students learn about patient safety (Table 4 ), for example, we rapidly accumulated a large quantity of data. The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources. This highlights a more general point of the importance of avoiding the temptation to collect as much data as possible; adequate time also needs to be set aside for data analysis and interpretation of what are often highly complex datasets.
Case study research has sometimes been criticised for lacking scientific rigour and providing little basis for generalisation (i.e. producing findings that may be transferable to other settings)[ 1 ]. There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table 8 )[ 8 , 18 – 21 , 23 , 26 ]. Transparency can be achieved by describing in detail the steps involved in case selection, data collection, the reasons for the particular methods chosen, and the researcher's background and level of involvement (i.e. being explicit about how the researcher has influenced data collection and interpretation). Seeking potential, alternative explanations, and being explicit about how interpretations and conclusions were reached, help readers to judge the trustworthiness of the case study report. Stake provides a critique checklist for a case study report (Table 9 )[ 8 ].
Conclusions
The case study approach allows, amongst other things, critical events, interventions, policy developments and programme-based service reforms to be studied in detail in a real-life context. It should therefore be considered when an experimental design is either inappropriate to answer the research questions posed or impossible to undertake. Considering the frequency with which implementations of innovations are now taking place in healthcare settings and how well the case study approach lends itself to in-depth, complex health service research, we believe this approach should be more widely considered by researchers. Though inherently challenging, the research case study can, if carefully conceptualised and thoughtfully undertaken and reported, yield powerful insights into many important aspects of health and healthcare delivery.
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Acknowledgements
We are grateful to the participants and colleagues who contributed to the individual case studies that we have drawn on. This work received no direct funding, but it has been informed by projects funded by Asthma UK, the NHS Service Delivery Organisation, NHS Connecting for Health Evaluation Programme, and Patient Safety Research Portfolio. We would also like to thank the expert reviewers for their insightful and constructive feedback. Our thanks are also due to Dr. Allison Worth who commented on an earlier draft of this manuscript.
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AS conceived this article. SC, KC and AR wrote this paper with GH, AA and AS all commenting on various drafts. SC and AS are guarantors.
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Crowe, S., Cresswell, K., Robertson, A. et al. The case study approach. BMC Med Res Methodol 11 , 100 (2011). https://doi.org/10.1186/1471-2288-11-100
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Tool-based renewable energy system planning using survey data: A case study in rural Vietnam
- Maria C. G. Hart ORCID: orcid.org/0000-0002-1031-9782 1 ,
- Sarah Eckhoff 1 &
- Michael H. Breitner 1
Environment, Development and Sustainability ( 2023 ) Cite this article
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Renewable energies provide effective sustainable development by raising living standards, accelerating economic growth, and mitigating pollution. However, specifically in developing countries, the lack of information, data, and local expertise challenges the design process and long-term success of renewable energy systems. Following the call for inter-disciplinary, solution-oriented research, this work uses a design science research-approach to facilitate multi-energy planning. The decision support system NESSI4D is developed, which considers site-specific economic, environmental, technological, and social factors and is tuned for stakeholder needs in developing countries. Following a step-by-step process model manual, the artifact’s applicability is demonstrated in a use case for a rural community in Thua Thien-Hue, Vietnam. Missing load data are synthesized from the TVSEP with the software RAMP. The results show that the implementation of renewable energy technologies only enables affordable, low-emission electrification with governmental financial incentives. Several sensitivity tests illustrate the impact of changing assumptions and highlight the importance of detailed analyses with highly specialized tools. The demonstrating use case validates the method’s relevance for research and practice towards the goals of effective sustainable development.
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1 Introduction
Access to electrical and thermal power allows to fulfill basic human needs and has proven to alleviate economic growth, transform societies, and raise living standards (UNDP, 2016 ; Oliveira & Moutinho, 2021 ). The trend toward an electricity-based economy has increased the importance of electric supply to provide equal economic chances (UNDP, 2016 ). Although the energy situation has improved worldwide in the past decades, 13 % of the population still lacks access to a reliable supply (United Nations, 2021 ). Dependence on fossil fuels, which provide 70 % of global demand, leaves players vulnerable to supply shocks, price changes, and political friction (Al-falahi et al., 2017 ; UNDP, 2016 ). Moreover, fossil fuels generate greenhouse gas (GHG) emissions that reinforce global warming and have adverse impacts on people’s well-being (United Nations, 2020 ). Therefore, the United Nations have formulated the 17 Sustainable Development Goals (SDGs) which include the global objective for access to affordable, modern, reliable, and sustainable energy for all (United Nations, 2021 ). Great potential lies particularly in the building sector, where a share of 22 % of global end-use energy is consumed and 17 % process-related GHG are emitted (IEA, 2019 ). Renewable energy technologies (RETs) contribute significantly towards more sustainable energy use in developing countries, as they are able to supply remote areas with modern electricity in an economically and ecologically viable manner, or to relieve the often overloaded electricity grids (Nong et al., 2020 ; Mandelli et al., 2016a ). Additionally, new technologies such as heat pumps and co-generation plants have emerged, allowing to design energy supply holistically as multi-energy systems. Cooperative generation in microgrids and heating networks offers great opportunities for cost and emission reductions. However, to promote the usage of RETs, stakeholders need to be informed about their technological capabilities as well as economic, ecological, and social impacts. Especially in developing countries, stakeholders face the challenge of complex energy components’ technical specifications, geographic and weather conditions, and consumer-specific energy demands in order to implement suitable energy systems (Al-falahi et al., 2017 ; Erdinc & Uzunoglu, 2012 ). Scarce data and the lack of studies in developing countries further complicate the formulation of evidence-based strategies and policies (Oliveira & Moutinho, 2021 ). Programs have been incorporated globally, but these often fail to include the users’ needs and views. Social and cultural issues of target communities result in low acceptance leading to long-term failures (Urmee & Md, 2016 ). Therefore, this work argues that stakeholders at the site must be assisted directly in their decision process for an economical, social, and ecologic sustainable energy composition. Mathematical models and Information and communication technologies (ICTs) provide new opportunities to reduce complexities, especially in developing and transitioning countries (Walsham, 2017 ). Thus, energy system planning and energy policy formulation are often supported with decision support systems (DSSs) (Cherni & Kalas, 2010 ). However, these tools are often commercial, need programming knowledge or are not suited for rural contexts in developing countries, see Sect. 2 . Thus, following several calls for inter-disciplinary development and solution-oriented research (Lehnhoff et al., 2021 ; Gholami et al., 2016 ; Siksnelyte et al., 2018 ), this work addresses the following research question:
How can stakeholders in developing countries make informed decisions to sustainably build and transform decentralized energy systems?
A Design Science Research (DSR) process according to Peffers et al. ( 2007 ) is conducted to develop a tool-based process to analyze small energy systems with scarce data and little capacities. The process includes the generation of input data that fulfills the conditions of detail, location-specificity, and topicality. This covers the synthesis of load profiles from survey data with the software RAMP and the inclusion of location-specific parameters. Second, the energy simulation software NESSI by Kraschewski et al. ( 2020 ) is modified and extended for the needs of stakeholders in developing countries and included in the process model. The research design is described in Sect. 3 and the resulting artifact is presented in Sect. 4 . In Sect. 5 , the method is tested and applied to a sample of thirty rural households in the Thua Thien-Hue province in Vietnam where the lack of information, data, local expertise, and scientific research was identified as a major challenge for the wide-spread use of RETs (Nguyen & Tuan, 2015 ; Nong et al., 2020 ). In Sect. 6 , the results and their implications are evaluated, before limitations and deducing future research are highlighted in Sect. 7 and a conclusion is given in Sect. 8 .
2 Literature review
2.1 information systems for sustainable development.
The United Nations (UN) defines sustainable development as a way to meet present needs without compromising the ability of future generations to satisfy their own needs (United Nations, 2021 ). This requires the enhancement and balance of inter-correlated economic, ecological, technological, and social conditions through individual, national, and international efforts (Siksnelyte et al., 2018 ). The UN has therefore agreed on 17 interrelated, but also sometimes mutually exclusive SDGs that define the common efforts to achieve a sustainable future (United Nations, 2021 ). As economies increasingly rely on electricity, the energy sector plays a significant role in sustainable development as it (among others) enhances living standards, increases international and national competitiveness, and transforms societies (UNDP, 2016 ; Oliveira & Moutinho, 2021 ). Simultaneously, the impacts of climate change that are further exacerbated by fossil fuel consumption call for a rapid energy transition, see SDG 7 (United Nations, 2021 ). However, inter-disciplinary decision-making is required to achieve the often contradicting goals of economic viability, energy resilience, and environmental friendliness (Siksnelyte et al., 2018 ). Broad consensus is found on the positive impact of decentralized hybrid energy systems such as mini- and micro-grids that mainly run on RETs (Balderrama et al., 2020 ; Herraiz-Cañete et al., 2022 ). However, the widespread dissemination of RETs is often hindered by missing knowledge about their long-term positive impacts or low transparency on the decision making process of third parties. Further, designing such systems is often overwhelming and requires detailed information on the energy components’ technical specifications and inter-correlations, local geographic and weather conditions, consumer-specific energy demands, market data, and soft social factors (Al-falahi et al., 2017 ; Erdinc & Uzunoglu, 2012 ). Deviations may lead to the inadequate choice and sizing of components, leading to high monetary burdens, low energy reliability, and sometimes long-term failure of the projects (Herraiz-Cañete et al., 2022 ; Urmee & Md, 2016 ). Thus, specialized DSS are necessary to reduce those complexities. The IS community acknowledges this need and implies that "Energy + Information > Energy," i.e., information is needed to enable and support economic and behaviorally driven solutions when designing energy systems (Watson et al., 2010 ). Walsham ( 2017 ) identified environment and climate change as the major societal issues of our century that must be addressed in the realm of Information and Communication Technology for Development (ICT4D). Thus, research that works on integrating and cooperating set of people, processes, software, and information technologies to support individual, organizational, or societal goals are called for (Watson et al., 2010 ; Gholami et al., 2016 ). Lehnhoff et al. ( 2021 ) further elaborates that IS research does not have to be theory-building at once, but must provide solutions for practical applications. Especially in the field of energy supply, access, and distribution, ICTs can effectively support stakeholders in developing and transitioning countries. However, despite its relevance, only few research provides national or empirical insights for policymakers or explicitly refer to the SDGs (Leong et al., 2020 ).
2.2 Related energy system simulation tools
Mathematical models, specifically multi-criteria decision support systems, have proven to address the challenges of energy system planning adequately. They allow to compare alternatives, rank target values depending on individual goals, and find suitable designs. In the past decade, a series of computational models have been developed for energy planning and found widespread research and practical applications, see Mandelli et al. ( 2016a ) and Mahmud et al. ( 2018 ). Widely-known tools are HOMER Pro (link) or iHoga (link) which conduct comprehensive techno-economic optimizations determining optimal sizing of components and minimizing net cost (HOMER Energy LLC, 2022 ; Dufo López, 2022 ). They have successfully been employed for case studies covering developing countries, see, e.g. Vendoti et al. ( 2021 ), Lau and Tan ( 2021 ), and Gebrehiwot et al. ( 2019 ). However, these tools often focus on the electric infrastructure, with only secondarily treating thermal loads. They further mostly require expert knowledge, often apply optimization algorithms which need high amounts of computing power, and were not explicitly designed for developing countries. In addition, their often commercial nature prevents stakeholders from using them. SURE-DSS by Cherni and Kalas ( 2010 ) uses a people-centered sustainable livelihood approach to plan the electrification of remote regions, but it is not an energy system simulator. OnSSET (link) , another established tool employed in developing countries, see Balderrama et al. ( 2020 ), requires programming knowledge and focuses solely on electrification. However, hot water and heat demands cannot be ruled out systematically to allow for analyses of countries or provinces in colder habitats. Stevanato et al. ( 2020 ) employ MicroGridsPy (link) , an open-source modeling framework for the optimization of hybrid micro-grids. However, it also does not have a graphical user interface, thus, limiting its widespread application. Another known energy system simulator is EnergyPLAN (link) , which has been used for case studies in both developed and developing countries, e.g. Ecuador, Tanzania, and Nicaragua (Lund et al., 2021 ). Although the freeware includes a variety of functionalities, it has been developed primarily for national-scale energy systems (Lund et al., 2021 ). The multi-energy tool NESSI by Kraschewski et al. ( 2020 ) is specialized in decentralized energy systems. The software focuses on its usability with a rich graphical user interface for stakeholders like building owners and politicians. However, NESSI was designed for applications in developed countries and potentially subject to built-in biases (al Irsyad et al., 2017 ).
2.3 Load profile generation for energy system simulation tools
Energy system analysis tools depend on suitable load profiles. Obtaining such load profiles is challenging and in developing countries often missing as they require information on household characteristics, a sufficient level of detail, and must be topical. Most simulation tools offer a library of pre-defined load profiles that are often not fitting for individual cases due to different cultural, social, and economic conditions (Proedrou, 2021 ). The tools HOMER Pro, iHoga and NESSI allow to import hourly or average user load data (Dufo López, 2022 ; Kraschewski et al., 2020 ). However, this data is often missing in developing countries. HOMER Pro additionally allows to import U.S.-American facility profiles from the OpenEI database and apply a similarity measure based on the Koeppen Geiger Climate Classification Index (HOMER Energy LLC, 2022 ). This is not sufficient in the context of rural areas in developing economies as the people’s living conditions differ considerably from those in industrial countries. Thus, in the reviewed body of literature, several tools, models, and methods are discussed to synthesize load profiles, see e.g. Marszal-Pomianowska et al. ( 2016 ) and McKenna and Thomson ( 2016 ). However, most tools are fed using data from detailed activity diaries, national time-use surveys, or device ownership statistics, and are context-specific to particular cases in developed countries or urban areas. For the developing world, an approach is needed that is able to cope with the dynamic settings at the site and inexact data. The software RAMP ( link ) by Lombardi et al. ( 2019 ) was specifically designed to generate high-resolution load profiles in developing countries. RAMP simulates users’ appliance habits accounting for the device’s nominal capacity, frequency of use, and total daily functioning time. Randomly varying parameters allow considering uncertainty and irregular usage behavior (Lombardi et al., 2019 ). The software is considered among the richest and most functional tools with respect to flexibility and customizability (Herraiz-Cañete et al., 2022 ).
3 Research design and methodology
No tools were found that meet the requirements of providing targeted decision support for sustainable multi-energy systems in developing countries (see Sect. 2.2 ). Thus, following the calls in the IS community for more solution-oriented research (Lehnhoff et al., 2021 ), an intuitive method for the design, transformation, and evaluation of energy systems in developing countries when data is scarce is developed using the design-science-oriented approach by Peffers et al. ( 2007 ) shown in Fig. 1 . In the IS community, DSR is a popular problem-solving paradigm that aims to improve technical and scientific knowledge through the development of innovative artifacts. Its potential to contribute to society’s critically needed sustainability transformation is explicitly highlighted (vom Brocke et al., 2020 ). Research outcomes of DSR can be design artifacts or design theories (Baskerville et al., 2018 ). Gregor and Hevner ( 2013 ) define three levels of DSR research contribution types: situated implementation of artifact, nascent design theory, and well-developed design theory about embedded phenomena. Multiple research processes exist in DSR, most prominently by Hevner ( 2007 ) and by Peffers et al. ( 2007 ). This work uses the process by Peffers et al. ( 2007 ) consisting of the 6 steps (1) identify problem and motivate, (2) derive objectives of solution, (3) design and development, (4) demonstration, (5) evaluation, and (6) communication. The process is iterative, feeding back lessons learned into earlier steps. For the problem identification of this work, see Sects. 1 and 2 . As a basis for the artifact, NESSI by Kraschewski et al. ( 2020 ) is used. In the design and development stage, NESSI is adapted and expanded to account for circumstances in developing countries. The new tool is called NESSI4D. Further, the usage of NESSI4D is described in a process model that serves as a comprehensive decision support manual for stakeholders that aim to design long-term sustainable energy systems. The process model also includes the usage of RAMP, a load profile generation tool that was identified in the literature review (Sect. 2.3 ). The development and resulting artifact are described in Sect. 4 . In the fourth stage, the applicability is demonstrated and validated in a carefully constructed case study as is common in DSR (Peffers et al., 2012 ) and DSS literature (Arnott & Pervan, 2012 ), see Sect. 5 . In Sect. 6 , the tool is evaluated and discussed. The artifact contributes not only practically but also theoretically by providing a research tool for conducting in-depth case studies in developing countries.
Design science research methodology adapted from Peffers et al. ( 2007 )
4 Artifact description
The Nano Energy System SImulator NESSI by Kraschewski et al. ( 2020 ) is specialized in decentralized energy systems. It simulates thermal and electrical energy flows, total costs, and GHG emissions. The simulation procedure is visualized in Fig. 4 step (ii). It is built upon DSR following software engineering guidelines. In this work, NESSI is adapted and expanded to account for circumstances in developing countries. For this purpose, the electric infrastructure is extended by small-scale wind turbines (WT) and diesel generators, to adapt to existing energy market structures and raise the flexibility as well as the robustness of the system. Given the developments in electric mobility and the cost advantages of electric two-wheelers, the simulation of battery and fuel-powered light motorcycles is also enabled. Models regarding the national power grid were altered to represent its availability in developing countries. Thus, the user is now able to simulate power system expansions and potential outages. For the case of an absent power grid and no storage possibilities, a reactive load is incorporated to use excess energy to heat a body of water. The economic calculations were improved by adding the U.S. dollar (USD) as a further currency option. Particularly in developing countries, microgrids provide an opportunity for electrification in remote areas where grid expansion is economically or technically infeasible. Additionally, they support the integration of distributed energy sources and reduce losses through shorter transmission distances (Nong et al., 2020 ; Mandelli et al., 2016b ). Thus, to allow for off-grid applications an island power grid is included. Additionally, the option of combining building analysis results to examine neighborhoods and villages is implemented. A high level of detail and flexibility is maintained by combining the results after simulating carefully constructed individual houses. The rich graphical user interface, optional country-specific standard input data for the components, underlying weather data, numerous currency options, and an extensive country-, building-, and household-specific load profile library, support users in performing simulations. To overcome the challenge of missing energy demand data, the user can choose load profiles from the library that were generated from detailed household survey data which were previously synthesized using RAMP by Lombardi et al. ( 2019 ). Alternatively, load profiles owned by the user can be imported. In summary, the model of the software has been extended with respect to the unique circumstances of the energy system in developing countries by including new energy producing, consuming, and storing components, changing underlying assumptions, and allowing for neighborhood simulation. For a visual impression of NESSI for Development (NESSI4D), see Figs. 2 and 3 or the Online Resources.
NESSI4D’s graphical user interface
NESSI4D’s graphical user interface: results
To further assist stakeholders that aim to design long-term sustainable energy systems, a comprehensive decision support manual was developed, depicted in Fig. 4 . The detailed step-by-step approach considers indicators that greatly influence the system’s final architecture and technical, economic, and ecological outcomes. First, the country’s situation, stakeholders’ objectives, and international literature must be assessed to evaluate the available technologies and possible barriers. Input data must be compiled or synthesized which includes detailed information on energy demand, geographic conditions and climate, as well as available technologies at the site, their settings, and local prices. It is emphasized that the inclusion and diligent consideration of each parameter is indispensable in the decision-making process to ensure the longevity of the energy project. To meet this need, this tool is designed to guide the user through each step and parameter of the process. Secondly, fitting energy system scenarios have to be formulated carefully and simulated with the software NESSI4D. Sensitivity analyses are advised that go beyond the chosen scenarios to test the robustness of the simulation’s outcomes. Finally, the results must be interpreted thoroughly, taking into account country- and context-specific factors.
Process model
5 Demonstration: rural community in Thua Thien-Hue, Vietnam
5.1 step 1: assess the country’s situation, stakeholders’ goals and international literature.
In the last years, improvements in the energy sector enabled quality increases of electricity supply, reduction of outages as well as grid expansions to virtually every household in Vietnam (Hien, 2019 ). Currently, stakeholders are faced with a rapid increase in energy demand due to rising prosperity and population growth. Ongoing investments to expand the grid’s capacity and agility, as well as the energy-generating infrastructure, are indispensable to ensure the continued reliability of the power supply (Nong et al., 2020 ). In rural areas specifically, the extension or reconstruction of the grid is often timely and economically impracticable, because of complex geographical conditions, low population density, and the households’ little energy demands (Gebrehiwot et al., 2019 ). Frequent occurring grid overloads further strengthen the need for alternative solutions, such as decentralized systems based on renewable energies (Nong et al., 2020 ).
Until now, electricity was mainly sourced from hydropower, natural gas, and coal (Dapice, 2018 ). As these resources are considered exploited and finite, the rising electricity load is met with imports and a stronger focus on coal mining. The Vietnamese government has set its energy targets oriented toward RET, specifically hydro, wind, and solar energy by committing to reduce GHG emissions by 25 % until 2030 at the \(21{\textrm{st}}\) Conference of the United Nations Framework Convention on Climate Change (Dapice, 2018 ).
Peer-reviewed studies for Vietnam of the past 10 years have been mainly regarding the country’s overall energy situation, e.g., Nguyen and Tuan ( 2015 ); Min and Gaba ( 2014 ), Zimmer et al. ( 2015 ), and Huong et al. ( 2021 ), consumption behavior, e.g., Hien ( 2019 ), renewable resource potentials and implementation challenges, e.g., Phap et al. ( 2020 ), Polo et al. ( 2015 ), Tran et al. ( 2016 ), and Nguyen et al. ( 2014 ), as well as energy or environmental (protection) policies, e.g., Lan et al. ( 2019 ), Nong ( 2018 ), Nong et al. ( 2019 ), Coxhead et al. ( 2013 ). Several studies have evaluated the economics of renewable energy generating components and the relation between energy consumption, income, economic growth, foreign direct investments or emissions, e.g., Tang and Tan ( 2015 ), Phuong and Tuyen ( 2018 ), Morelli and Mele ( 2020 ), Phong et al. ( 2018 ), Phrakhruopatnontakitti et al. ( 2020 ), Tang et al. ( 2016 ), Son and Yoon ( 2020 ), and Long et al. ( 2018 ). Other articles regard the conventional strategy of expanding the national grid, e.g., Le et al. ( 2013 ). Several works have simulated the option of feeding the central power grid with large solar or wind renewable energy plants (Le et al., 2018 ; Truong et al., 2021 ; Viet et al., 2018 ). Nguyen and Van ( 2021 ) and Thanh et al. ( 2021 ) analyze a grid-connected rooftop solar system for a household in urban settings. Decentralized solutions in the rural energy conditions have scarcely been evaluated. Nguyen et al. ( 2019a ) and Tran et al. ( 2021 ) analyze micro-grid design on Vietnamese islands with HOMER, but emphasize that further studies must be conducted where electricity is readily available. Nguyen ( 2007b ) has examined this possibility through evaluating the economics of hybrid wind and solar stand-alone renewable energy systems (RES) for rural households. However, they applied inexact input data by assuming a constant energy demand and using rough weather data. They further do not include the option of implementing RETs supplementary to the power grid and the environmental impacts of the energy systems. Due to this lack of research, Nong et al. ( 2020 ) demand more scientific studies that do not only aid policy-makers in their strategy formulation, but also facilitate stakeholders to generate regional-specific inquiries.
5.2 Step 2: evaluate energy demand and synthesize load profiles
There have been several studies closing the gap of missing load data by forecasting the Vietnamese energy demand (Võ et al., 2020 ; Nguyen et al., 2019b , 2018 ; Lee et al., 2020 ). These studies focus on the industry and construction sectors or the overall electricity consumption. Inferences about rural demands are infeasible. Load profiles with data from the Thailand Vietnam Socio Economic Panel (TVSEP) of the year 2017, see tvsep.de , is generated. The survey contains information on 609 rural households in the low per-capita-income province Thua Thien-Hue in Vietnam. The households are selected based on a three-stage cluster sampling design and acknowledged to be representative for the rural population in this region (Hardeweg et al., 2013 ).
Most households comprise of couples with up to two children. Using an exchange rate of 0.000043 US$/VND, the annual mean income is 4,653 US$ per household and 1,265 US$ per capita. The houses have a mean size of 84.5 m \(^2\) and three rooms on average. The majority uses electricity for lighting and bottled gas for cooking. Almost every household owns one television, refrigerator, and rice cooker, as well as three fans. Smartphones are less common with a share of 53 %. Other electrical appliances are owned infrequently in the sample as depicted in Fig. 5 . Air conditioners, for example, are rarely owned, which might be due to the high costs of its operation (Le & Pitts, 2019 ).
Share of electrical appliance ownership in rural Thua Thien-Hue, Vietnam
As no information about the lighting system is available, the satisfaction of basic visual demand is assumed, concluding in the presence of one indoor light per room and one outdoor light per house. The assumptions of the assets’ usage are dependent on the average time between sunrise and sunset, assumed working hours, and free-time behaviors. Selected appliances are considered to be used occasionally. Further information about the typical usage characteristics, and power needs per appliance, is obtained from Le and Pitts ( 2019 ); Mandelli et al. ( 2016b ), and Lombardi et al. ( 2019 ). For simplicity, weekends, vacation days, as well as the differentiation between seasons, are omitted. Table 1 summarizes the appliance’s settings and its assumed usage.
For this analysis, thirty households are randomly chosen to form a representative, small village. The above-mentioned information is then used to generate load profiles with RAMP based on the households’ individual asset ownership. In Fig. 6 , the summation of these load profiles for one day is depicted. Interested readers find the characteristics and appliance ownership for each selected household in Appendix A in the Online Resources.
Example of 365 different stochastic daily load profiles of the thirty rural households in Thua Thien-Hue
5.3 Step 3: compile data on geographic conditions and climate
Another critical factor for energy systems is the climate conditions at the site. Climate data is needed to enable the calculation of the components’ energy yield. For instance, to obtain the PV module’s yield, information on the diffuse, beam, and reflected solar radiation is needed. The WT’s simulation requires wind speed data and air density. Depending on the country, different datasets are available with varying time steps. As this approach strives for a high degree of detail, data with minutely or hourly time steps is desired. This enables the analysts to interpret the results in more detail and discover weaknesses and limitations. Thus, location-specific data from the NASA-Merra2 dataset for wind and temperature data and Copernicus Atmosphere Monitoring Service for radiation data were compiled (CAMS, 2021 ; Renewables Ninja, 2021 ).
5.4 Step 4: assess available energy producing, storing and consuming technologies on site, its settings and local prices
Vietnam’s wind and solar resources provide suitable conditions for related renewable energy generating components (Nguyen, 2007a ; Tran & Chen, 2013 ; Phap et al., 2020 ; Polo et al., 2015 ). Thus, electrification via the grid is compared with systems that include supplementary photovoltaic modules (PV) and small scale WTs. Battery storage units (BS) are included due to their capabilities to smooth the RET’s fluctuating yields and increase the system’s efficiency (Gebrehiwot et al., 2019 ). The diesel generator is excluded since it does not fulfill the policymakers’ desire to shift toward ecological sustainable energy systems. The evaluation of thermal energy is omitted, because the climatic conditions induce no heat demands. The warm water demand for showering or cooking is assumed to be fulfilled with the electric heater since no related data is available. Six RES with different combinations of thirty \(6\,\textrm{m}^{2}\) rooftop PVs, two WTs, and one BS for a representative grid-connected rural neighborhood are simulated and compared to the scenario of sole grid supply. The predetermined energy component settings, operation and management costs (O &M), and investments are summarized in Table 2 . Because there are comparatively low wind speeds in the Thua Thien-Hue region, input data from a WT model designed for low wind speeds is used (Nord, 2020 ; Nguyen, 2007a ).Costs of converters and inverters are assumed to be included in the components’ prices.
Additionally, three sensitivity analyses to show the importance of simulations for the decision process are conducted. The first analysis accounts for future cost developments. Data suggests that RETs are becoming financially more attractive, whereas the electricity price in Vietnam is expected to rise continuously due to non-sustainable governmental subsidies (Le, 2019 ; Hiep & Hoffmann, 2020 ). The predicted electricity price development of 8.5 %/a, decreasing RET investments of 30 % by 2030, and further 20 % until 2050 (Dapice, 2018 ) is simulated. Second, the influence of policymakers through feed-in tariffs (FITs) is assessed. Especially in developing countries, FITs need to be set at an appropriate level to solve the implementation bias toward the rich and achieve access to modern electricity for the poor (Kobayakawa & Kandpal, 2014 ). Third, the potentials to reduce the value of initial investments is examined. Batteries, originally designed for electric vehicles, are expected to enter the energy market as reconditioned second-life batteries. For the residential sector, the batteries’ capacity is sufficient and shows a high application potential as a cheaper alternative (Kamath et al., 2020 ). Additionally, WTs from the company Rivogy whose parts can be mostly manufactured at the site using local products (Kroeger, 2020 ) are included. Because of a lower-rated power per WT, a higher number of installed WTs to ensure the scenarios’ comparability is assumed. Step-by-step screenshots of the analyses for one exemplary RES are provided in Appendices B and C in the Online Resources.
5.5 Step 5: conduct computations
First the results and findings of the base analysis is presented, comparing the simulated RES with a reference scenario which does not consider additional components. As no space heating is required, due to sufficiently high temperatures, the village’s load comprises solely of electrical demand that sums up to 45,355 kWh/a. The components’ prices result in investments of 37,944 US$ for the PVs, 44,500 US$ for the two WTs, and an additional 9,614 US$ for systems including BS. With the local conditions and selected RES settings, the WTs and PVs generate 36,683 kWh/a and 63,922 kWh/a, respectively. The degree of autarchy spans from 32 % (Grid–PV) to 66 % (Grid–WT–PV), whose values increase up to 90 % (Grid–WT–PV–BS) when a BS is added. Additional BS also have the potential to increase the degree of self-consumption, for example, from 60 % to 75 % in the case of Grid–WT.
Economic and ecological performance of analyzed energy system configurations for a representative neighborhood in Thua Thien-Hue, Vietnam
Figure 7 summarizes the annual grid supply, GHG emissions, and total costs of each energy system. The latter is presented by a fixed annualized value and comprises the discounted initial investments, O &M and demand-related costs, as well as the generated yields from selling surplus energy. The total costs in the reference scenario are 3,673 US$/a. More cost-effective are the three compositions Grid–PV, Grid–PV–WT, and Grid–PV–BS with cost reduction potentials of up to 50 % (Grid–PV). Considering the average annual household income of 4,653.52 US$/a, the share of electricity expenditures can be reduced from 2.6 % to 1.3 %. These results are driven by the high FITs that allow to sell excess generated energy. The Grid–WT–PV system, for instance, generates 70,684 kWh surplus energy per year. Due to the inherent characteristic of fluctuating yields of WTs and PVs, the energy cannot be put into productive use at all times. Thus, selling this surplus energy allows high monetary yields that reduce the RES investment and O &M costs. The RES Grid–WT–PV–BS, Grid–WT, and Grid–WT–BS increase the charges by 340 US$/a, 1,260 US$/a, and 2,112 US$/a, respectively. This is due to three factors: Firstly, the high investment costs of each WT and the additional BS. Secondly, the comparably high electricity costs from the central power grid due to the wind turbine’s low efficiency. And closely related to this, the low yields through insufficient amounts of sold surplus energy.
Regarding the ecological impacts, most GHG are emitted in the reference scenario ( \(41,400\,\textrm{kg}_{\textrm{CO}_{2}}\) ) due to the grid’s emission factor of \(0.913\,\textrm{kg}_{\textrm{CO}_{2}}\) /kWh. Since only RETs are considered, the lower the annual electricity purchase from the grid, the more environmentally friendly the system. The simulated RES show annual GHG emission reductions from \(12,273 \,\textrm{kg}_{\textrm{CO}_{2}}\) /a (Grid–PV) to \(27,317\,\textrm{kg}_{\textrm{CO}_{2}}\) /a (Grid–WT–PV). Because BS increase a system’s efficiency, the resulting decreased amounts of procured power lead to less GHG emissions for all compositions that include storage. Thus, the environmentally most advantageous RES is the Grid–PV–WT–BS combination with 4,749 kWh/a procured from the grid and annual GHG emission reductions of \(37,073\,\textrm{kg}_{\textrm{CO}_{2}}\) /a. Thus, this RES is capable of reducing annual emissions to 10 \(\dot{\%}\) /a of the reference scenario’s amount. However, this RES results in higher costs indicating a trade-off between the goals of economic viability and emission reductions. Despite the lower overall WT yield, the RES Grid–WT emits fewer GHG than the Grid–PV system. This suggests that the timing of wind yields matches the timing of demand better than solar yields. As a result, the positive impact of BS on GHG emissions is smaller in Grid–WT than Grid–PV RES.
The results of the sensitivity analyses are shown in Fig. 8 . For a visual comparison, initial results are referenced in gray.
Economic and ecological performance of energy systems of four sensitivity analyses
First, the predicted price developments for 2030 and 2050 are analyzed. The corresponding results are summarized in Fig. 8 a and b, relating annual total costs to GHG emissions. In most cases, a large upward shifts in expenses is found. The reference scenario’s costs rise to 8,304 US$/a in the year 2030, and successively increase to 42,462 US$/a in the year 2050. These results show the magnitude of monetary strains on electricity supply that can be expected in Vietnam in future. The cost reduction potentials with the application of RETs are now strongly dependent on the grid supply of each energy system. The higher the amount of electricity procured, the greater the cost difference from both the reference scenario and the 2020 values. For systems with strong dependencies on the power grid (Grid–PV, Grid–WT, Grid–PV–BS, Grid–PV–WT–BS), the savings from lower RET investments are not sufficient to offset the increased electricity costs from the grid. These systems are more cost-intensive in future. In contrast, systems with low electricity procurement (Grid–PV–WT and Grid–PV–WT–BS) show cost reductions in the year 2030 of 409 US$/a and 1,500 US$/a, respectively. Moreover, the combination Grid–WT–PV–BS enables cost stability in the year 2050 with relatively slight increases of 754 US$/a. The total annual costs of the latter RES are only a \(10^{\textrm{th}}\) of the costs for the reference scenario in the same year. These results strengthen the argument toward RET implementations to reduce the expected high cost of sufficient residential electrification in future. Generally, overall lower costs and emissions compared to the reference scenario are found. The earlier mentioned trade-off between economic viability and emission reductions shrinks as now the BS’s positively influence both factors in the RES Grid–PV–WT. Figure 8 b displays significant positive correlations in 2050, eliminating this trade-off completely.
In the following, the outcomes with varying FITs are compared. Figure 8 c depicts the annual total costs and GHG emissions for the currently set FITs of 0.0806 US$/kWh (PV) and 0.085 US$/kWh (WT), no FITs, and increased FITs with values of 0.1 US$/kWh for both RETs. RES without FIT have higher costs than the reference scenario. The most expensive system is Grid–PV–WT with 8,927 US$/a, which was previously an economically viable composition. This exemplifies the FITs’ influence on low total costs. For Grid–PV and Grid–PV–WT, BS are now not only ecologically but also economically advantageous compared to their counterparts without BS when no FITs are applied as they reduce the costs by up to 2,444 US$/a. The increased tariffs do not have a promising impact on Grid–WT and Grid–WT–BS compositions indicating further necessary incentives for the set-up of WTs such as investment subsidies. Nevertheless, with an additional BS the RES Grid–PV–WT becomes economically viable resulting in the most emission reducing and also more economically advantageous option than the sole grid supply. In comparison to the altered FIT levels, the current scheme is suitable to incentivize investments, generally, but should be increased slightly to motivate stakeholders to apply solutions with the highest emission reducing potentials.
Lastly, the potentials to reduce the amount of initial investments and, thus, the total costs per year are examined. The results are depicted in Fig. 8 d. With locally produced WT and second-life batteries, the initial investments reduce by 17,500 US$/a (i.e., 27,000 US$/a) and 6,624 US$/a (i.e., 2,990 US$/a), respectively. Batteries have a significant positive effect on the system’s efficiency. The RES Grid–WT, Grid–PV, and Grid–WT–PV procure 20 %, 40 %, and 70 % less electricity from the grid with additional BS. These systems also come with higher total costs of 800 US$/a–900 US$/a. This analysis depicts that the cost differences between BS including and non-including systems reduce by 300 US$/a–400 US$/a, leaving the investment in BS still economically disadvantageous—despite a price reduction of approximately 70 %. The cost cuts in WT through local production result in significant cost decreases for Grid–WT and Grid–WT–BS by up to 1,340 US$/a. However, compared to the reference scenario, these systems are still not cost competitive. Regarding the ecological changes, the lower efficiency of the systems resulted in an increase of GHG emissions by \(1,824\,\textrm{kg}_{\textrm{CO}_{2}}\) /a to \(4,478\,\textrm{kg}_{\textrm{CO}_{2}}\) /a. All economic results are summarized in Table 3 . For interested readers, further outcomes not included here can be found in the Online Resources, see Appendices B and C.
5.6 Interpret, infer, and recommend
In line with Nguyen ( 2007b ), the results and findings show that with the current market structure and FIT value, most RES are ecologically and economically advantageous over the baseline scenario.
The use of RETs reduces electricity procurement which influences the indirect GHG emissions. In accordance, these results show significant ecological improvements in each RES with additional RETs and are validated by various research works, see, e.g., Nguyen et al. ( 2019a ), Nguyen and Van ( 2021 ) or Nguyen ( 2007b ). These changes are expected to elevate in future, as the rising electricity loads are currently met with imports and coal mining. These developments have lead to an increase of indirect emissions from 0.541 to \(0.913\,\textrm{kg}_{\textrm{CO}_{2}}\) /kWh in the past 10 years and are expected to rise further (IGES, 2020 ). The associated negative environmental and health impacts, which often disproportionately affect the poor population, strengthen the argument toward the implementation of decentralized renewable energy. Regarding the rapidly increasing load demand, decentralized wind and solar energy solutions may be of particular interest for the Vietnamese stakeholders as their set-up generally takes less time than coal plant constructions, hydroelectric dams, or large-scale RES projects (Dapice, 2018 , 2017 ).
Economically, RES are often advantageous due to income generation from the sold surplus energy and cost savings from grid supply reductions. Due to relatively low wind speeds at site, the WT’s income through generating surplus energy does not cover their costs. Nguyen ( 2007b ) validates these findings, but states that in areas with high wind speeds, WTs may be more economically and, thus, underlies the importance of location-specific simulations. Feeding-in electricity is also beneficial to relieve the national power grid and postpone necessary grid upgrades due to higher load requirements. However, high power feeds may also lead to grid overloads, which have already been observed in some regions of Vietnam (Nong et al., 2020 ). These risks will be reduced by higher self-consumption rates through, e.g., additional electrical appliances whose amounts typically increase with a newly available, reliable, and financially viable energy supply. Another option is the use of surplus electricity for electric mobility like cars, tuk-tuks or scooters, and heat generation, e.g., heat pumps and air conditioning.
RES can also decrease energy cost-induced poverty. With the current FIT policies, electricity costs can be reduced due to self-consumption and additionally generated income. However, the economically feasible energy systems require investments of up to 50 % of the annual income. These sudden costs would disproportionately affect other consumption goods and the household member’s welfare. In line with Nguyen ( 2007b )’s findings and propositions, energy policies should be implemented that offer particular financial and technical support targeted toward the most disadvantaged population. The simulations do not include the cost of capital for loans. It is estimated that if the entire initial investment is financed over 20 years, an interest rate of 2 % must not be exceeded for individuals. Alternatively, the Vietnamese government could introduce subsidies to encourage investments. In any case, citizens need support in applying for subsidies and loans, as the financial literacy of the rural population in Vietnam is limited (Morgan & Trinh, 2017 ).
In the subsequent sensitivity analysis, it is observed that the expected price trends will increase the costs of most energy systems, although disproportionately. Energy-cost-induced poverty risks rise in future, however, the severance can be reduced by additional RETs. Tran et al. ( 2021 ) further validates these results stating that reduced RET prices will make isolated RES economically feasible—potentially even without governmental incentives.
FIT values have been successively increased in the past five years by the government. The second sensitivity analysis visualizes the importance of these tariff changes and shows promising effects for the current level. Lower FITs result in infeasible RES-including scenarios whereas higher FIT cannot decrease the system costs of the prior uneconomical scenarios to a satisfactory level. Several research set in Vietnam have not considered feed-in tariffs and validate our findings of RES being uneconomic without governmental incentives, see, e.g., Nguyen and Van ( 2021 ).
In contrast, the current electricity price is too low to encourage investments in RETs without corresponding monetary incentives. This is especially prominent for BS. With FITs and the electricity prices at a similar level, there are no economical incentives to purchase BS. The grid is able to function as a storage system with virtually no costs. As shown in the third sensitivity analysis, the costs of BS do not influence the investment decisions as grid usage is always more economical under current tariffs than BS investments. Thanh et al. ( 2021 ) validates these results, but argues that in light of deteriorating energy security, e.g., power grid failures, back-up batteries are useful and in some instances necessary.
Next to the economic and ecological sustainability analyzed in the simulation, social sustainability is an important, non-omittable factor for the long-term success of energy systems (Urmee & Md, 2016 ). Locally produced WTs are included to emphasize the importance of local value creation. The introduction of RETs results in local business opportunities through distribution, installation, and repair. The generation of new job prospects promotes knowledge transfers and skill developments through training in technical schools and companies. Comparing PVs and WTs, the creation of local employment is particularly strong when implementing the latter, as the installation, operation, and maintenance are mostly set in rural areas (Nguyen, 2007a ). In conclusion, the slightly increased costs for systems without supporting PVs would still provide a promising application in future when considering the social factors and predicted price trends. It should be noted, that the use of second-life BS is also auspicious, but must be preceded by the formation of thoughtful regulatory frameworks clarifying the product’s liability and capacity.
Based on the computational results and further validated by related literature, it becomes evident that the implementation of RETs does not only have promising long-term ecological, economic, and social benefits, but also decreases the risk of power grid overloads, localizes industries, and aids in poverty alleviation. Ultimately, the extent of the success of an economically viable, emission-reducing energy supply lies in the components’ settings, prices, and market development. To formulate suitable policies promoting appropriate RES to residents in rural areas, it is advised that stakeholders conduct further analyses applying NESSI4D. In light of the SDGs, this work’s implications do not only address Vietnamese interest groups but also international organizations and developed countries as the Vietnamese Government has limited financial resources (Nguyen et al., 2019c ).
6 Evaluation, implications, and generalized recommendations
The artifact is evaluated through the demonstrating use case from Sect. 5 as is common in DSR Peffers et al. ( 2012 ) and DSS literature Arnott and Pervan ( 2012 ). The demonstration shows that the developed tool and process model are suitable for the intended application, i.e., the design of an RES under consideration of the location-specific energy situation in developing countries. Following step (i), all input data needed for NESSI4D is compiled or generated and the challenge framed. Missing data can be drawn from the tool’s library or synthesized in detail with the help of the software RAMP. When the computations are conducted in step (ii), users are supported with numerous values and illustrative graphics provided by the software. With this tool, solution-oriented research on virtually all SDGs is enabled as called for by Leong et al. ( 2020 ), Gholami et al. ( 2016 ), and Walsham ( 2017 ). For instance, as NESSI4D provides renewable and traditional, fossil solutions, differences in GHG emissions are quantified and the advantages of renewable RETs highlighted, thus, supporting SDG 13 (climate protection), SDG 11 (sustainable cities), and SDG 3 (good health and well-being). SDG 7 calls for affordable energy, thus, NESSI4D carefully calculates the cost of energy systems to design governmental policies and avoid energy poverty which simultaneously tackles SDG 1 (end poverty). In step (iii) the user interprets, infers, and recommends about a suitable RES design with the given information. Using NESSI4D, household members and village leaders can factor numerous key values into their decisions, understand the impact of small changes, and design their customized optimal energy system. More broadly, policymakers are supported in forming site- and target-specific policy recommendations that align with national and international goals of feasibility, reliability, and emissions reductions. By empowering people to actively participate in the energy planning process, new potential is created, potentially leading to longer-term more successful projects and job creation, as Urmee and Md ( 2016 ) call for. Thus, NESSI4D contributes to practice as a measure to reduce complexities in the energy system planning process and to theory as a research tool. In summary, this work demonstrates the suitability of the tool-based method for performing structured analyses that include the most relevant indicators for energy system planning in developing countries.
In the demonstration, the software’s results are validated with findings from related simulation research showing that energy systems powered by RES reduce environmental pollution and contribute to energy security, but must be financially supported through governmental incentives, see, e.g., Nguyen and Van ( 2021 ); Thanh et al. ( 2021 ); Tran et al. ( 2021 ); Nguyen et al. ( 2019a ). However, this type of analysis is subject to the conflict between accuracy and generalizability, which means that transferring them to other energy projects should be done with caution. It is recommended to analyze each energy project individually with tools such as NESSI4D in order to achieve a long-term project success. Thus, the validation’s expressiveness through comparison with other research literature is limited. Thus, the recommendations following the tool’s results must be applied in practice and monitored in the long term. Thorough interviews should be conducted with experts in the fields of energy planning, development aid, construction, academic research, and private stakeholders to further validate and improve this work’s approach.
7 Limitations and further research
The analyses show that this method allows stakeholders to support fundamental inferences about an optimal energy composition considering the circumstances and individual preferences of stakeholders. Regarding the input data, the usage of synthesized load profiles from survey data is sufficiently detailed to assess energy system configurations when data is scarce. Nonetheless, measuring load profiles at the site provides more precise results, as weekdays, vacations, and seasons were disregarded. In addition, the used survey was conducted in 2017. With energy demands rising by 8 % per year, results get outdated quickly. In its current version, NESSI4D does not account for demand increases. These must be considered in the energy system’s final implementation to avoid the risk of undersized components. Further, NESSI4D solely accounts for emissions associated with energy flows whereas life cycle costs, including emissions during production and environmental risks due to poor waste management, are omitted. Knowledge of the component’s operation, supervision, and repair, as well as accompanying technical capacities, also influences the long-term economic and ecological sustainability of an energy system. Besides, social sustainability is only discussed qualitatively but has been proven important for the long-term success of modern electrification projects (Urmee & Md, 2016 ). The omission of these factors may distort the results and findings.
Next to addressing the above-mentioned shortcomings, future research should conduct even more in-depth case studies using this or a further developed method. Regarding the case study, not all capabilities of the developed method have been showcased yet. The thermal infrastructure, as well as electric vehicles, have not been accounted for. The operation of the latter with excess energy, for instance, might enable an additional mode of affordable transportation that allows for better employment opportunities, time-efficiency increases, and health benefits due to decreased emissions. Further research examining buildings beyond the residential sector such as schools or administration offices can also prove beneficial, provided corresponding data can be obtained. On the subject of NESSI4D, the inclusion of additional renewable energies such as biomass, hydro, or hydrogen and incorporation of load evolution will be future tasks. The ultimate objective is to develop a comprehensive decision support system for politicians and building owners in developing countries to make informed decisions about their energy systems. The research goals, therefore, overlap with the academic field labeled ICT4D where Walsham ( 2017 ) identified environment and climate change as major societal issues that must be addressed with information and communication technology. The authors aim to make NESSI4D available for said stakeholders in future via a web application.
8 Conclusions
Rapidly rising energy demands, depleting fossil fuels, and the aim for an ecologically, economically, and socially more sustainable energy system motivate stakeholders to rethink energy infrastructures for buildings and small, decentralized energy networks. The lack of information, data, and local expertise is a major challenge for the future wide-spread use of renewable energy in developing countries. Following the call for inter-disciplinary, solution-oriented research, a tool-based method to enable multi-energy planning considering location-specific circumstances is developed. Following a DSR approach, the energy system simulation tool NESSI is adapted to address stakeholders’ needs in developing countries. To further reduce complexities, a detailed process model is provided as a manual for energy system planning with simulation models. As common in DSR and DSS research, the applicability of the approach is then evaluated and validated with a demonstrating use case. Following the demand for scientific energy research in Vietnam, a case study for a representative village of thirty rural poor households in the Thua Thien-Hue province is conducted. For this purpose, load profiles evaluated from detailed household survey data and synthesized with RAMP are used. It is found that the implementation of PV modules and WTs is more economically, environmentally, and socially sustainable than sole grid utilization. Predicted price trends depict cost increases for electrification and higher risk for energy-cost induced poverty reinforcing the need for the promotion of renewable components. The demonstration shows the importance of careful policy planning when setting incentives such as feed-in tariffs and cost reduction potentials through second-life batteries and locally produced wind turbines. Investments in RES are suitable for poverty alleviation, job creation, and industry localization for the rural population in Vietnam. It is recommended to promote RETs in rural areas, formulate tailored energy policies, and support local stakeholders to facilitate the transition to modern electrification. The demonstrating case study validates the artifact’s relevance and emphasized the importance of providing highly specified DSS tools for energy system planning in developing countries. Thus, NESSI4D contributes to practice as a measure to meet the SDGs and to theory as a research tool and must be further improved in future works.
Availability of data and material
All supplementary data can be viewed in the file named “Online Supplements.” For information about the raw survey data, please, contact the authors.
Code availability
The software is not open-source yet, but an open-access web-application is being programmed at the moment. We provide screenshots of our analysis in our Online Resources.
Abbreviations
Kilowatt hours
Kilogram carbon dioxid equivalents
United States dollar
Vietnam dong
Hybrid optimization of multiple energy resources
Improved hybrid optimization by genetic algorithms
Nano energy system simulator
Nano energy system simulator for development
Open source spatial electrification tool
Remote-areas multi-energy systems load profiles
Sustainable rural energy decision support system
Battery storage
Photovoltaic system
Wind turbine
Central power grid
Central power grid and photovoltaic system
Central power grid and wind turbine
Central power grid, photovoltaic system, and battery storage
Central power grid, wind turbine, and battery storage
Central power grid, wind turbine, and photovoltaic system
Central power grid, wind turbine, photovoltaic system, and battery storage
- Design science research
- Decision support system
Feed-in tariff
Greenhouse gases in \(\hbox {kg}_{\textrm{CO}_{2}}\) -eq.
Information and communication technologies
Information and Communication Technologies for Development
Information systems
Operation and management
- Sustainable development goals
Thailand Vietnam Socio Economic Panel
Renewable energy technologies
- Renewable energy systems
United Nations
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Hart, M.C.G., Eckhoff, S. & Breitner, M.H. Tool-based renewable energy system planning using survey data: A case study in rural Vietnam. Environ Dev Sustain (2023). https://doi.org/10.1007/s10668-023-03120-4
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A green cooperative development method based on the idef0 model of manufacturing knowledge: case study of a carton-filling machine, 1. introduction, 2. idef0 model of manufacturing knowledge that supports the design process, 2.1. design process and manufacturing knowledge requirements, 2.2. idef0 model that support the design process, 2.3. idef0 model of manufacturing knowledge for college-enterprise collaborative design decisions, 3. idef0 model of manufacturing knowledge building for the development of a carton filling machine, 3.1. overall goals and requirements of the carton filling machine, 3.2. idef0 model of manufacturing knowledge-building for cooperative development, 3.3. idef0 model of manufacturing knowledge for the key component, 4. process control based on the idef0 model of manufacturing knowledge, 4.1. building the college–enterprise development team based on the idef0 model of manufacturing knowledge, 4.2. communication of manufacturing technologies and conditions based on the idef0 model of manufacturing knowledge, 4.3. design process control, 5. results and discussion, 6. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.
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Share and Cite
Wang, B.; Yao, C.; Li, X.; Wei, G. A Green Cooperative Development Method Based on the IDEF0 Model of Manufacturing Knowledge: Case Study of a Carton-Filling Machine. Sustainability 2023 , 15 , 4047. https://doi.org/10.3390/su15054047
Wang B, Yao C, Li X, Wei G. A Green Cooperative Development Method Based on the IDEF0 Model of Manufacturing Knowledge: Case Study of a Carton-Filling Machine. Sustainability . 2023; 15(5):4047. https://doi.org/10.3390/su15054047
Wang, Beihai, Chenghan Yao, Xuezhong Li, and Guoliang Wei. 2023. "A Green Cooperative Development Method Based on the IDEF0 Model of Manufacturing Knowledge: Case Study of a Carton-Filling Machine" Sustainability 15, no. 5: 4047. https://doi.org/10.3390/su15054047
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Overthrown in 2001 by a U.S.-led military campaign, the Taliban has since waged an insurgency against the internationally backed Afghan government, resulting in widespread displacement and destruction, including significant physical threats and restrictions for Afghan women.
The seemingly intractable Israeli-Palestinian conflict is rooted in a dispute over the land that makes up present-day Israel, the West Bank, and the Gaza Strip.
Following the 2011 uprising against Muammar al-Qaddafi and military intervention by the North Atlantic Treaty Organization (NATO), interim governments struggled for legitimacy as armed militias vied for power.
Since Myanmar gained independence in 1948, various armed ethnic groups seeking greater autonomy from the government have fought the world’s longest-running civil war . Tens of thousands have been killed and hundreds of thousands displaced by ongoing sectarian violence between the Buddhist community and the persecuted Rohingya Muslim minority.
Sudan has been plagued by intermittent civil wars. To the west, conflict in Darfur since 2003 has caused widespread death and displacement. To the south, a 2005 peace agreement prefaced South Sudan’s 2011 secession, but conflict continues between the government and armed groups in the South Kordofan and Blue Nile regions (the “Two Areas”). In 2019, Sudan began transitioning to democratic civilian rule after a military coup d’état.
In 2011, protests against Syrian President Bashar al-Assad’s regime quickly escalated into a full-scale armed conflict between anti-government rebel groups and the Syrian government. Outside parties have significantly intervened, particularly as the self-proclaimed Islamic State expanded from Iraq into Syria.
In response to the Ukrainian revolution, Russian troops—in violation of international law— annexed Ukraine’s Crimean Peninsula in March 2014. This invasion incited pro-Russian separatists in two eastern Ukrainian territories to declare independence from Ukraine and prompted an ongoing conflict between Russia-backed separatist forces and the Ukrainian military that has resulted in over fourteen thousand deaths and over 1.5 million internally displaced persons, 59 percent of whom are women.
Yemen continues to be devastated by fighting between government loyalists and Houthi rebels sparked by the 2011 uprising that transferred power from former President Ali Abdullah Saleh to Abd Rabbuh Mansour Hadi. Ethnic Houthi rebels from northern Yemen exploited the central government’s weak influence and seized Sanaa in 2014. South Yemen’s separatist militias continue their violent push for secession.
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IMAGES
VIDEO
COMMENTS
Step 1: Select a case Step 2: Build a theoretical framework Step 3: Collect your data Step 4: Describe and analyze the case When to do a case study A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject.
Cooperative research process was also used by Payne and Storbacka (2009) in the development of brand cocreation model. After this feedback, the transcribed interview texts were coded and concepts were developed. ... This understanding of the process is vital for the case study researcher in order to decide what to look for, how to look, and ...
Pioneered by HBS faculty, the case method puts you in the role of the chief decision maker as you explore the challenges facing leading companies across the globe. Learning to think fast on your feet with limited information sharpens your analytical skills and empowers you to make critical decisions in real time. Read More
In simpler terms — a case study is an investigative research into a problem aimed at presenting or highlighting solution (s) to the analyzed issues. A standard business case study provides insights into: General business/market conditions The main problem faced Methods applied The outcomes gained using a specific tool or approach
A case study is an in-depth study of one person, group, or event. In a case study, nearly every aspect of the subject's life and history is analyzed to seek patterns and causes of behavior. Case studies can be used in various fields, including psychology, medicine, education, anthropology, political science, and social work.
Conference Paper Case Study Model August 2014 DOI: 10.13140/2.1.1671.3603 Conference: This was not presented at a conference. Authors: Freya Magnusson University of California, San Francisco...
Case analysis introduces students to the real-world process of making business decisions quickly and correctly, often with limited information. This framework supplies an organized and disciplined process that students can readily defend in writing and in class discussions. PACADI in Action: An Example
The case shows how a strategic approach to human resource and talent development at all levels really matters. This company competes in an industry not known for engaging its front-line workers. The case shows how engaging these workers can really pay off. 3. Finally, Pal's is really unusual in its approach to growth.
Process improvement solutions help businesses define weaknesses and take action to solve these problems. In the case studies we collected, the most common project results that we came across are as follows: 1- Improved efficiency: Most businesses increase the efficiency of their processes by adapting process improvement methodologies.
Case Study: Applying a Data Science Process Model to a Real-World Scenario | by Jonas Dieckmann | Mar, 2023 | Towards Data Science Write Sign up Sign In 500 Apologies, but something went wrong on our end. Refresh the page, check Medium 's site status, or find something interesting to read. Jonas Dieckmann 191 Followers
The case study format is typically made up of eight parts: Executive Summary. Explain what you will examine in the case study. Write an overview of the field you're researching. Make a thesis statement and sum up the results of your observation in a maximum of 2 sentences. Background. Provide background information and the most relevant facts.
A case study is a document that focuses on a business problem and provides a clear solution. Marketers use case studies to tell a story about a customer's journey or how a product or service solves a specific issue. Case studies can be used in all levels of business and in many industries.
A marketing case study is a type of marketing where you use your existing customers as an example of what your product or services can achieve. You can also create case studies of internal, successful marketing projects. Here's an example of a marketing case study template: CREATE THIS CASE STUDY TEMPLATE Return to Table of Contents
Process modeling is the practice of visualizing business processes and workflows. By including every individual step, process models provide an end-to-end overview of the tasks and activities in business processes. Process modeling reveals insights about: Events and activities in a workflow The people involved in these activities and events
A business case study is simply a story about how you successfully delivered a solution to your client. Case studies start with background information about the customer, describe problems they were facing, present the solutions you developed, and explain how those solutions positively impacted the customer's business. Back to Top
Case Study: Auditing With Process Mining — Part VIII: Discovered Model Anne 16 Mar. This is the 8th article in our case study series on auditing with process mining. The series is written by Jasmine Handler and Andreas Preslmayr from the City of Vienna. You can find an overview of all the articles in the series here.
Case Studies in Process Modeling. Detailed, Realistic Examples. The general points of the first five sections are illustrated in this section using data from physical science and engineering applications. Each example is presented step-by-step in the text and is often cross-linked with the relevant sections of the chapter describing the ...
The clinical case management model involves a case manager (often a therapist or counselor) assigned by a clinical care provider. The case manager works directly with the client in a clinical capacity, providing care as well as coordinating and developing treatment plans.
The open-ended problems presented in case studies give students work that feels connected to their lives. Close. ... One way to do this is by teaching content and skills using real-world case studies, a learning model that's focused on reflection during the problem-solving process. It's similar to project-based learning, but PBL is more ...
Case-Based Learning. Case-based learning (CBL) is an established approach used across disciplines where students apply their knowledge to real-world scenarios, promoting higher levels of cognition (see Bloom's Taxonomy ). In CBL classrooms, students typically work in groups on case studies, stories involving one or more characters and/or ...
A case analysis in business is a study of a business problem. Anyone conducting a case analysis can use evidence to propose viable solutions to business problems, then provide recommendations on the best way to implement these solutions to produce the desired results. Related: Analytical Skills: Definitions and Examples
Five Case Studies of Transformation Excellence. November 03, 2014 By Lars Fæste , Jim Hemerling , Perry Keenan, and Martin Reeves. In a business environment characterized by greater volatility and more frequent disruptions, companies face a clear imperative: they must transform or fall behind. Yet most transformation efforts are highly complex ...
The three case study boards are companies operating within the United Kingdom and owned by the state. There is a history of using state-owned companies as case studies in the WoB literature as they tend to have higher proportions of women and access to multiple companies is facilitated through contact with a single shareholder representative ...
It is the process in which the element identified in CLDs will be quantified and simulated, where it represents integral finite difference equations variables of the feedback loop structure of the system and simulates the dynamics behaviours. ... E.E., Setiawan, Y., Syartinilia. (2017). Monitoring of landscape change in paddy fields: Case study ...
The case study approach allows in-depth, multi-faceted explorations of complex issues in their real-life settings. The value of the case study approach is well recognised in the fields of business, law and policy, but somewhat less so in health services research. Based on our experiences of conducting several health-related case studies, we reflect on the different types of case study design ...
The process model also includes the usage of RAMP, ... The demonstrating case study validates the artifact's relevance and emphasized the importance of providing highly specified DSS tools for energy system planning in developing countries. Thus, NESSI4D contributes to practice as a measure to meet the SDGs and to theory as a research tool ...
This is a case study of cooperative development between a college and a corporation to manufacture a carton-filling machine. Specifically, a green cooperative development method was proposed that would match the college's design capabilities with the manufacturing capacity of the enterprise. This college-enterprise cooperative development represents an extensive collaboration ...
This qualitative analysis documents how women participate in peace processes—whether in official negotiating roles or through grassroots efforts—and why their inclusion advances security.