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What are Decision Criteria? (Explained With Examples)

Oct 11, 2023

What are Decision Criteria? (Explained With Examples)

Decision criteria are essential factors that individuals or organizations consider when making a decision. They serve as the basis for evaluating different options and ultimately choosing the best course of action. In this article, we will delve into the definition of decision criteria, explore their advantages and disadvantages, and provide practical examples in various contexts, such as startups, consulting, and digital marketing agencies. We will also utilize analogies to help illustrate the concept further.

1. What are Decision Criteria?

Decision criteria encompass the specific factors that individuals or organizations prioritize when making a decision. These factors can include financial considerations, strategic objectives, customer preferences, technological feasibility, and many other relevant aspects. By establishing decision criteria, individuals or organizations can systematically evaluate different options and determine the best course of action.

When it comes to decision-making, having clear and well-defined criteria is crucial. Decision criteria serve as a set of guidelines or standards that help individuals or organizations assess and compare different alternatives. These criteria can be quantitative or qualitative, depending on the nature of the decision and the available information.

1.1 Definition of Decision Criteria

Decision criteria refer to the specific standards or benchmarks used to assess different alternatives during a decision-making process. These criteria can be quantitative or qualitative and are often tailored to the specific context or goals of the decision-making process.

Quantitative decision criteria involve measurable factors that can be assigned numerical values. For example, in a financial decision, criteria such as return on investment (ROI), net present value (NPV), or payback period may be used. These criteria provide a clear and objective basis for evaluating options.

On the other hand, qualitative decision criteria involve subjective factors that are difficult to quantify but still play a significant role in the decision-making process. These criteria can include factors such as brand reputation, customer satisfaction, or ethical considerations. While they may not have precise numerical values, they are essential for capturing the intangible aspects that influence decision outcomes.

1.2 Advantages of Decision Criteria

Using decision criteria provides several benefits. Firstly, decision criteria help ensure that all relevant aspects are taken into account, leading to more comprehensive and informed decisions. By considering a range of factors, decision-makers can avoid overlooking critical aspects that could impact the success of the chosen option.

Secondly, decision criteria enable individuals or organizations to compare and prioritize different options based on their importance. By assigning weights or rankings to each criterion, decision-makers can objectively assess the pros and cons of each alternative. This allows for a more structured decision-making process and reduces the likelihood of relying on subjective judgments solely.

Lastly, decision criteria facilitate stakeholder collaboration and transparency as they provide a clear framework for evaluating options and aligning diverse perspectives. When decision criteria are well-defined and communicated, stakeholders can understand the rationale behind the chosen option and feel more engaged in the decision-making process.

1.3 Disadvantages of Decision Criteria

While decision criteria offer significant advantages, they are not without their limitations. One potential disadvantage is that decision criteria can oversimplify complex problems or situations. By focusing on specific factors, decision criteria may overlook critical nuances or underlying complexities that could impact the final decision. It is important for decision-makers to be aware of this limitation and consider additional information or expert opinions to supplement the criteria.

Additionally, decision criteria can be influenced by biases or limited perspectives, potentially leading to suboptimal outcomes. For example, if decision criteria heavily prioritize short-term financial gains, long-term sustainability or ethical considerations may be overlooked. To mitigate this risk, decision-makers should strive for a diverse and inclusive decision-making process that incorporates a wide range of perspectives and expertise.

In conclusion, decision criteria play a vital role in the decision-making process. They provide a structured framework for evaluating alternatives and help ensure that all relevant aspects are considered. However, decision criteria should be used judiciously, taking into account the limitations and potential biases they may introduce. By combining decision criteria with broader considerations and expert insights, individuals and organizations can make more informed and effective decisions.

2. Examples of Decision Criteria

Examining practical examples will further illuminate the concept of decision criteria. Let's explore how decision criteria can be applied in different contexts:

2.1 Example in a Startup Context

In a startup context, decision criteria could include factors such as market potential, cost-effectiveness, scalability, and alignment with the company's vision and mission. By prioritizing these criteria, startup founders can evaluate potential business opportunities and make data-driven decisions that maximize chances of success.

For example, let's consider a tech startup that is developing a new mobile app. The decision criteria for this startup could involve analyzing the size of the target market, assessing the potential demand for the app, and evaluating the competition in the app market. Additionally, the startup may consider the cost-effectiveness of developing and maintaining the app, as well as its scalability potential in terms of user growth and revenue generation.

By carefully considering these decision criteria, the startup can make informed choices about whether to proceed with the app development, how to allocate resources, and how to position the app in the market.

2.2 Example in a Consulting Context

When working on a consulting project, decision criteria might involve client requirements, industry best practices, profitability, and long-term sustainability. By utilizing these criteria, consultants can assess alternative solutions and recommend the most suitable strategy to address the client's challenges and achieve their goals.

For instance, let's imagine a consulting firm that is tasked with helping a manufacturing company optimize its production processes. The decision criteria in this context could include analyzing the client's specific requirements, benchmarking against industry best practices, evaluating the potential profitability of proposed solutions, and considering the long-term sustainability of the implemented changes.

By carefully evaluating these decision criteria, the consulting firm can provide the client with a well-informed recommendation on how to streamline their production processes, improve efficiency, and ultimately achieve their desired business outcomes.

2.3 Example in a Digital Marketing Agency Context

In the context of a digital marketing agency, decision criteria could include factors such as target audience reach, cost per acquisition, return on investment, and campaign performance metrics. By incorporating these criteria, digital marketers can make data-informed decisions on the optimal marketing channels, strategies, and campaigns to maximize client's online presence and achieve desired business outcomes.

For example, let's consider a digital marketing agency that is working with an e-commerce client to increase their online sales. The decision criteria for this agency could involve analyzing the potential reach of different marketing channels, calculating the cost per acquisition for each channel, evaluating the expected return on investment for various marketing strategies, and monitoring campaign performance metrics such as click-through rates and conversion rates.

By carefully considering these decision criteria, the digital marketing agency can develop a tailored marketing plan that focuses on the most effective channels, strategies, and campaigns to drive targeted traffic to the client's website, increase conversions, and ultimately boost online sales.

2.4 Example with Analogies

To grasp the concept of decision criteria further, let's consider an analogy. Imagine you are choosing a holiday destination. The decision criteria might encompass factors such as travel costs, weather preferences, available activities, and cultural experiences. By evaluating these criteria, you can prioritize destinations that align with your preferences and make an informed decision on the best holiday spot.

For instance, let's say you are planning a vacation and have several potential destinations in mind. The decision criteria you might consider could include analyzing the cost of travel and accommodation, assessing the weather conditions and climate preferences, evaluating the availability of activities and attractions, and considering the cultural experiences each destination offers.

By carefully evaluating these decision criteria, you can narrow down your options and choose a holiday destination that suits your budget, weather preferences, desired activities, and cultural interests.

In conclusion, decision criteria play a crucial role in the decision-making process. They allow individuals or organizations to assess alternatives systematically, considering crucial factors and aligning decisions with their goals. While decision criteria have advantages such as comprehensiveness and clarity, it is important to be aware of their limitations and use them judiciously alongside broader considerations. By examining practical examples and analogies, we can better understand how decision criteria apply in various contexts and enhance our decision-making capabilities.

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decision criteria in case study examples

Arnaud Belinga

decision criteria in case study examples

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Do Your Students Know How to Analyze a Case—Really?

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  • Case Teaching
  • Student Engagement

J ust as actors, athletes, and musicians spend thousands of hours practicing their craft, business students benefit from practicing their critical-thinking and decision-making skills. Students, however, often have limited exposure to real-world problem-solving scenarios; they need more opportunities to practice tackling tough business problems and deciding on—and executing—the best solutions.

To ensure students have ample opportunity to develop these critical-thinking and decision-making skills, we believe business faculty should shift from teaching mostly principles and ideas to mostly applications and practices. And in doing so, they should emphasize the case method, which simulates real-world management challenges and opportunities for students.

To help educators facilitate this shift and help students get the most out of case-based learning, we have developed a framework for analyzing cases. We call it PACADI (Problem, Alternatives, Criteria, Analysis, Decision, Implementation); it can improve learning outcomes by helping students better solve and analyze business problems, make decisions, and develop and implement strategy. Here, we’ll explain why we developed this framework, how it works, and what makes it an effective learning tool.

The Case for Cases: Helping Students Think Critically

Business students must develop critical-thinking and analytical skills, which are essential to their ability to make good decisions in functional areas such as marketing, finance, operations, and information technology, as well as to understand the relationships among these functions. For example, the decisions a marketing manager must make include strategic planning (segments, products, and channels); execution (digital messaging, media, branding, budgets, and pricing); and operations (integrated communications and technologies), as well as how to implement decisions across functional areas.

Faculty can use many types of cases to help students develop these skills. These include the prototypical “paper cases”; live cases , which feature guest lecturers such as entrepreneurs or corporate leaders and on-site visits; and multimedia cases , which immerse students into real situations. Most cases feature an explicit or implicit decision that a protagonist—whether it is an individual, a group, or an organization—must make.

For students new to learning by the case method—and even for those with case experience—some common issues can emerge; these issues can sometimes be a barrier for educators looking to ensure the best possible outcomes in their case classrooms. Unsure of how to dig into case analysis on their own, students may turn to the internet or rely on former students for “answers” to assigned cases. Or, when assigned to provide answers to assignment questions in teams, students might take a divide-and-conquer approach but not take the time to regroup and provide answers that are consistent with one other.

To help address these issues, which we commonly experienced in our classes, we wanted to provide our students with a more structured approach for how they analyze cases—and to really think about making decisions from the protagonists’ point of view. We developed the PACADI framework to address this need.

PACADI: A Six-Step Decision-Making Approach

The PACADI framework is a six-step decision-making approach that can be used in lieu of traditional end-of-case questions. It offers a structured, integrated, and iterative process that requires students to analyze case information, apply business concepts to derive valuable insights, and develop recommendations based on these insights.

Prior to beginning a PACADI assessment, which we’ll outline here, students should first prepare a two-paragraph summary—a situation analysis—that highlights the key case facts. Then, we task students with providing a five-page PACADI case analysis (excluding appendices) based on the following six steps.

Step 1: Problem definition. What is the major challenge, problem, opportunity, or decision that has to be made? If there is more than one problem, choose the most important one. Often when solving the key problem, other issues will surface and be addressed. The problem statement may be framed as a question; for example, How can brand X improve market share among millennials in Canada? Usually the problem statement has to be re-written several times during the analysis of a case as students peel back the layers of symptoms or causation.

Step 2: Alternatives. Identify in detail the strategic alternatives to address the problem; three to five options generally work best. Alternatives should be mutually exclusive, realistic, creative, and feasible given the constraints of the situation. Doing nothing or delaying the decision to a later date are not considered acceptable alternatives.

Step 3: Criteria. What are the key decision criteria that will guide decision-making? In a marketing course, for example, these may include relevant marketing criteria such as segmentation, positioning, advertising and sales, distribution, and pricing. Financial criteria useful in evaluating the alternatives should be included—for example, income statement variables, customer lifetime value, payback, etc. Students must discuss their rationale for selecting the decision criteria and the weights and importance for each factor.

Step 4: Analysis. Provide an in-depth analysis of each alternative based on the criteria chosen in step three. Decision tables using criteria as columns and alternatives as rows can be helpful. The pros and cons of the various choices as well as the short- and long-term implications of each may be evaluated. Best, worst, and most likely scenarios can also be insightful.

Step 5: Decision. Students propose their solution to the problem. This decision is justified based on an in-depth analysis. Explain why the recommendation made is the best fit for the criteria.

Step 6: Implementation plan. Sound business decisions may fail due to poor execution. To enhance the likeliness of a successful project outcome, students describe the key steps (activities) to implement the recommendation, timetable, projected costs, expected competitive reaction, success metrics, and risks in the plan.

“Students note that using the PACADI framework yields ‘aha moments’—they learned something surprising in the case that led them to think differently about the problem and their proposed solution.”

PACADI’s Benefits: Meaningfully and Thoughtfully Applying Business Concepts

The PACADI framework covers all of the major elements of business decision-making, including implementation, which is often overlooked. By stepping through the whole framework, students apply relevant business concepts and solve management problems via a systematic, comprehensive approach; they’re far less likely to surface piecemeal responses.

As students explore each part of the framework, they may realize that they need to make changes to a previous step. For instance, when working on implementation, students may realize that the alternative they selected cannot be executed or will not be profitable, and thus need to rethink their decision. Or, they may discover that the criteria need to be revised since the list of decision factors they identified is incomplete (for example, the factors may explain key marketing concerns but fail to address relevant financial considerations) or is unrealistic (for example, they suggest a 25 percent increase in revenues without proposing an increased promotional budget).

In addition, the PACADI framework can be used alongside quantitative assignments, in-class exercises, and business and management simulations. The structured, multi-step decision framework encourages careful and sequential analysis to solve business problems. Incorporating PACADI as an overarching decision-making method across different projects will ultimately help students achieve desired learning outcomes. As a practical “beyond-the-classroom” tool, the PACADI framework is not a contrived course assignment; it reflects the decision-making approach that managers, executives, and entrepreneurs exercise daily. 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

Here’s an example of how students used the PACADI framework for a recent case analysis on CVS, a large North American drugstore chain.

The CVS Prescription for Customer Value*

PACADI Stage

Summary Response

How should CVS Health evolve from the “drugstore of your neighborhood” to the “drugstore of your future”?

Alternatives

A1. Kaizen (continuous improvement)

A2. Product development

A3. Market development

A4. Personalization (micro-targeting)

Criteria (include weights)

C1. Customer value: service, quality, image, and price (40%)

C2. Customer obsession (20%)

C3. Growth through related businesses (20%)

C4. Customer retention and customer lifetime value (20%)

Each alternative was analyzed by each criterion using a Customer Value Assessment Tool

Alternative 4 (A4): Personalization was selected. This is operationalized via: segmentation—move toward segment-of-1 marketing; geodemographics and lifestyle emphasis; predictive data analysis; relationship marketing; people, principles, and supply chain management; and exceptional customer service.

Implementation

Partner with leading medical school

Curbside pick-up

Pet pharmacy

E-newsletter for customers and employees

Employee incentive program

CVS beauty days

Expand to Latin America and Caribbean

Healthier/happier corner

Holiday toy drives/community outreach

*Source: A. Weinstein, Y. Rodriguez, K. Sims, R. Vergara, “The CVS Prescription for Superior Customer Value—A Case Study,” Back to the Future: Revisiting the Foundations of Marketing from Society for Marketing Advances, West Palm Beach, FL (November 2, 2018).

Results of Using the PACADI Framework

When faculty members at our respective institutions at Nova Southeastern University (NSU) and the University of North Carolina Wilmington have used the PACADI framework, our classes have been more structured and engaging. Students vigorously debate each element of their decision and note that this framework yields an “aha moment”—they learned something surprising in the case that led them to think differently about the problem and their proposed solution.

These lively discussions enhance individual and collective learning. As one external metric of this improvement, we have observed a 2.5 percent increase in student case grade performance at NSU since this framework was introduced.

Tips to Get Started

The PACADI approach works well in in-person, online, and hybrid courses. This is particularly important as more universities have moved to remote learning options. Because students have varied educational and cultural backgrounds, work experience, and familiarity with case analysis, we recommend that faculty members have students work on their first case using this new framework in small teams (two or three students). Additional analyses should then be solo efforts.

To use PACADI effectively in your classroom, we suggest the following:

Advise your students that your course will stress critical thinking and decision-making skills, not just course concepts and theory.

Use a varied mix of case studies. As marketing professors, we often address consumer and business markets; goods, services, and digital commerce; domestic and global business; and small and large companies in a single MBA course.

As a starting point, provide a short explanation (about 20 to 30 minutes) of the PACADI framework with a focus on the conceptual elements. You can deliver this face to face or through videoconferencing.

Give students an opportunity to practice the case analysis methodology via an ungraded sample case study. Designate groups of five to seven students to discuss the case and the six steps in breakout sessions (in class or via Zoom).

Ensure case analyses are weighted heavily as a grading component. We suggest 30–50 percent of the overall course grade.

Once cases are graded, debrief with the class on what they did right and areas needing improvement (30- to 40-minute in-person or Zoom session).

Encourage faculty teams that teach common courses to build appropriate instructional materials, grading rubrics, videos, sample cases, and teaching notes.

When selecting case studies, we have found that the best ones for PACADI analyses are about 15 pages long and revolve around a focal management decision. This length provides adequate depth yet is not protracted. Some of our tested and favorite marketing cases include Brand W , Hubspot , Kraft Foods Canada , TRSB(A) , and Whiskey & Cheddar .

Art Weinstein

Art Weinstein , Ph.D., is a professor of marketing at Nova Southeastern University, Fort Lauderdale, Florida. He has published more than 80 scholarly articles and papers and eight books on customer-focused marketing strategy. His latest book is Superior Customer Value—Finding and Keeping Customers in the Now Economy . Dr. Weinstein has consulted for many leading technology and service companies.

Herbert V. Brotspies

Herbert V. Brotspies , D.B.A., is an adjunct professor of marketing at Nova Southeastern University. He has over 30 years’ experience as a vice president in marketing, strategic planning, and acquisitions for Fortune 50 consumer products companies working in the United States and internationally. His research interests include return on marketing investment, consumer behavior, business-to-business strategy, and strategic planning.

John T. Gironda

John T. Gironda , Ph.D., is an assistant professor of marketing at the University of North Carolina Wilmington. His research has been published in Industrial Marketing Management, Psychology & Marketing , and Journal of Marketing Management . He has also presented at major marketing conferences including the American Marketing Association, Academy of Marketing Science, and Society for Marketing Advances.

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decision criteria in case study examples

  • How it works

A Quick Guide to Case Study with Examples

Published by Alvin Nicolas at August 14th, 2021 , Revised On August 29, 2023

A case study is a documented history and detailed analysis of a situation concerning organisations, industries, and markets.

A case study:

  • Focuses on discovering new facts of the situation under observation.
  • Includes data collection from multiple sources over time.
  • Widely used in social sciences to study the underlying information, organisation, community, or event.
  • It does not provide any solution to the problem .

When to Use Case Study? 

You can use a case study in your research when:

  • The focus of your study is to find answers to how and why questions .
  • You don’t have enough time to conduct extensive research; case studies are convenient for completing your project successfully.
  • You want to analyse real-world problems in-depth, then you can use the method of the case study.

You can consider a single case to gain in-depth knowledge about the subject, or you can choose multiple cases to know about various aspects of your  research problem .

What are the Aims of the Case Study?

  • The case study aims at identifying weak areas that can be improved.
  • This method is often used for idiographic research (focuses on individual cases or events).
  • Another aim of the case study is nomothetic research (aims to discover new theories through data analysis of multiple cases).

Types of Case Studies

There are different types of case studies that can be categorised based on the purpose of the investigation.

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How to Conduct a Case Study?

  • Select the Case to Investigate
  • Formulate the Research Question
  • Review of Literature
  • Choose the Precise Case to Use in your Study
  • Select Data Collection and Analysis Techniques
  • Collect the Data
  • Analyse the Data
  • Prepare the Report

Step1: Select the Case to Investigate

The first step is to select a case to conduct your investigation. You should remember the following points.

  • Make sure that you perform the study in the available timeframe.
  • There should not be too much information available about the organisation.
  • You should be able to get access to the organisation.
  • There should be enough information available about the subject to conduct further research.

Step2: Formulate the Research Question

It’s necessary to  formulate a research question  to proceed with your case study. Most of the research questions begin with  how, why, what, or what can . 

You can also use a research statement instead of a research question to conduct your research which can be conditional or non-conditional. 

Step 3: Review of Literature

Once you formulate your research statement or question, you need to extensively  review the documentation about the existing discoveries related to your research question or statement.

Step 4: Choose the Precise Case to Use in your Study

You need to select a specific case or multiple cases related to your research. It would help if you treated each case individually while using multiple cases. The outcomes of each case can be used as contributors to the outcomes of the entire study.  You can select the following cases. 

  • Representing various geographic regions
  • Cases with various size parameters
  • Explaining the existing theories or assumptions
  • Leading to discoveries
  • Providing a base for future research.

Step 5: Select Data Collection and Analysis Techniques

You can choose both  qualitative or quantitative approaches  for  collecting the data . You can use  interviews ,  surveys , artifacts, documentation, newspapers, and photographs, etc. To avoid biased observation, you can triangulate  your research to provide different views of your case. Even if you are focusing on a single case, you need to observe various case angles. It would help if you constructed validity, internal and external validity, as well as reliability.

Example: Identifying the impacts of contaminated water on people’s health and the factors responsible for it. You need to gather the data using qualitative and quantitative approaches to understand the case in such cases.

Construct validity:  You should select the most suitable measurement tool for your research. 

Internal validity:   You should use various methodological tools to  triangulate  the data. Try different methods to study the same hypothesis.

External validity:  You need to effectively apply the data beyond the case’s circumstances to more general issues.

Reliability:   You need to be confident enough to formulate the new direction for future studies based on your findings.

Also Read:  Reliability and Validity

Step 6: Collect the Data

Beware of the following when collecting data:

  • Information should be gathered systematically, and the collected evidence from various sources should contribute to your research objectives.
  • Don’t collect your data randomly.
  • Recheck your research questions to avoid mistakes.
  • You should save the collected data in any popular format for clear understanding.
  • While making any changes to collecting information, make sure to record the changes in a document.
  • You should maintain a case diary and note your opinions and thoughts evolved throughout the study.

Step 7: Analyse the Data

The research data identifies the relationship between the objects of study and the research questions or statements. You need to reconfirm the collected information and tabulate it correctly for better understanding. 

Step 8: Prepare the Report

It’s essential to prepare a report for your case study. You can write your case study in the form of a scientific paper or thesis discussing its detail with supporting evidence. 

A case study can be represented by incorporating  quotations,  stories, anecdotes,  interview transcripts , etc., with empirical data in the result section. 

You can also write it in narrative styles using  textual analysis  or   discourse analysis . Your report should also include evidence from published literature, and you can put it in the discussion section.

Advantages and Disadvantages of Case Study

Frequently asked questions, what is the case study.

A case study is a research method where a specific instance, event, or situation is deeply examined to gain insights into real-world complexities. It involves detailed analysis of context, data, and variables to understand patterns, causes, and effects, often used in various disciplines for in-depth exploration.

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Content analysis is used to identify specific words, patterns, concepts, themes, phrases, or sentences within the content in the recorded communication.

In correlational research, a researcher measures the relationship between two or more variables or sets of scores without having control over the variables.

A survey includes questions relevant to the research topic. The participants are selected, and the questionnaire is distributed to collect the data.

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20 – Recommendation Reports

Decision-Making and Criteria

David McMurrey; Jonathan Arnett; Kalani Pattison; and Nicole Hagstrom-Schmidt

The previous parts of this chapter have dealt mostly with expectations regarding the sections of a recommendation or feasibility report. However, underlying the report as a whole, a decision-making process is taking place. Presenting a clear recommendation or suggestions to your audience depends on clearly informing your readers how you reached your decision.

Depending on the structure of your report and the delineation of your research tasks within your results, conclusions, recommendations, or all of these sections, you will have to justify evaluations, comparisons, and decisions that you made in the course of your research. Below are several common places where you may make crucial decisions that affect the content and results of your entire report:

  • If one of your research tasks is to determine the best product to buy, and another task is to determine where to install it, you will have to evaluate multiple options as part of the results of those tasks.
  • If you administer a survey, conduct interviews, and find secondary resources about website builders, you may have to determine the most important information to include in your conclusion in order to draw your results or findings together into logical conclusions.
  • If you find that a suggested course of action isn’t actually going to improve a situation, a decision-making tree or a decision matrix in the recommendation might help support your recommendation of keeping the status quo.

In all of these cases, and in almost all recommendation or feasibility reports, you need to be able to clearly explain your decision-making processes to your audience in an objective way. Three tools that you can use to do so are criteria, decision matrices, and decision trees.

Criteria (singular: criterion) are the quantitative and qualitative categories and standards you use to judge something. If your technical report requires you to make a judgment of some sort—is the project feasible? What is the best option? Did the item pass or fail a test?—you should describe and define the factors that guide your decision. Common examples of decision-making criteria include costs, schedules, popular opinions, demonstrated needs, and degrees of quality. Here are some examples:

  • If you are recommending a tablet computer for use by employees, your requirements are likely to involve size, cost, hard-disk storage, display quality, durability, and battery life.
  • If you are looking into the feasibility of providing every student at Austin Community College with an ID on the ACC computer network, you need to define the basic requirements of such a program: what it would be expected to accomplish, problems that it would have to avoid, and so on.
  • If you are evaluating the logistics of the free bus public transportation program in Bryan/College Station for Texas A&M students, you need to know what is expected of the program and then explore costs, locations, and other factors in relation to those requirements.

Criteria may need to be defined on a very specific level. For example, “chocolate flavor” may be a criterion for choosing among brands of chocolate truffles, but what defines a desirable chocolate flavor? Do you want a milk chocolate flavor? A dark chocolate flavor? White chocolate? A high or low percentage of cacao? Sweet, bitter, or spicy? Single-origin cacao beans or a blend? If single-origin, do you want Ghanian, Venezuelan, Honduran, Ecuadorian, or Filipino? The more you know about a criterion, the more precise you can be in your evaluation.

Criteria may also be referred to as requirements and can be defined in three basic ways:

  • Numerical values. Many requirements are stated as maximum or minimum numerical values. For example, there may be a cost requirement, such as the tablet computer for employees should cost no more than $900.
  • Yes/no values. Some requirements are simply a yes-no question. For instance, does the tablet come equipped with Bluetooth? Is the car equipped with voice recognition?
  • Ratings values. In some cases, key considerations cannot be handled either with numerical values or yes/no values. For example, your organization might want a tablet that has an ease-of-use rating of at least “good” by some nationally accepted ratings group. In other situations, you may have to assign ratings yourself.

The criteria section should also discuss how important the individual requirements are in relation to each other. Picture the typical situation where no one option is best in all categories of comparison. One option is cheaper; another has more functions; one has better ease-of-use ratings; another is known to be more durable. Set up your criteria so that they dictate a “winner” from a situation where there is no obvious winner.

Decision Matrices

One useful tool for decision-making based on criteria of varying importance is a decision matrix (plural: matrices). Decision matrices allow for numerical calculations and comparisons of different choices with criteria that have varying levels of importance.

To create a decision matrix, you start with the options to be compared, the criteria to be used to evaluate the options, and the relative weight or importance of each criterion in the decision. Table 20.2 [1] shows how a generic decision matrix would be set up.

Table 20.2. Generic decision matrix example.

In the weight column, each criterion would be given a number within a certain range—from 1 (least important) to 5 (most important), or 1 to 10, depending on how much the levels differ in importance. Some writers may be more comfortable with using percentages out of 100 when considering weight. Criteria can share the same weight or importance. The options would then be scored along a similar scale according to how well they perform in the particular criterion. The weight and score would then be multiplied and the whole column added together to give a total.

The following Table 20.3 [2] is a decision matrix reflecting different options for communicating to students in an online course. The weights are given in the shaded columns, the score each option earns for each criterion are shown in bold, and the maroon multiplication next to the score shows how the weight and score are multiplied. These totals are then added for a total of the whole column.

Table 20.3. Example decision matrix with randomly generated data.

As you can see in Table 20.3, if you went strictly by the number of criteria that an option excelled in, you might determine that emails are the best way to contact students. However, if you use the more nuanced decision matrix, then you could conclude that Canvas Announcements are the best way to communicate with students. The varying weights of each criterion and the score each option earns should be based on solid research. This matrix, then, allows you to quantify the reasons for choosing one option over another, despite the weights and scores being a little subjective.

Decision Trees

In addition to making a recommendation based on criteria or on weighted criteria, sometimes recommendations can be made after following a decision tree. Creating a visual representation of a decision tree can be useful in illuminating your thought process so that readers can follow your reasoning. Such decision trees can also be useful in communicating procedures for others to follow, especially in problem-solving situations.

The following decision tree in Figure 20.12 [3] illustrates how to determine whether to hire a professional to complete a household project or to do it yourself. As you can see, most decision trees are based on a series of Yes/No, Either/Or limited choices. There may be a choice out of three or four options at a particular step, but that isn’t as common, and so it is not depicted in the example.

Decision tree titled: "Should you hire a professional for a household project or do it yourself?" Decision trees work by asking us yes/no questions. Our answers lead us further down the chart either to other questions or directly to a decision. In the present example, branches asking questions about various project characteristics are followed by yes/no boxes with arrows leading down to three ultimate decision options: "do it yourself," "wait to complete the project," or "hire a professional." Examples of the questions in the branches include: "Do you have access to the tools needed?" "Is the cost of materials significantly less than the cost of hiring a professional?" and "Do you understand how to complete the task?" Here's an example of how this works. One of the final questions asks "Can you afford to hire a professional?" If your answer is yes, an arrow leads to the decision to hire a professional. If your answer is no, another arrow leads to the option to "wait to complete the project."

This text was derived from

McMurrey, David and Jonathan Arnett, “Recommendation and Feasibility Reports,” in Tiffani Reardon, Tamara Powell, Jonathan Arnett, Monique Logan, and Cassandra Race, with contributors David McMurrey, Steve Miller, Cherie Miller, Megan Gibbs, Jennifer Nguyen, James Monroe, and Lance Linimon. Open Technical Communication . 4th ed. Athens, GA: Affordable Learning Georgia, n.d. https://alg.manifoldapp.org/projects/open-tc . Licensed under a Creative Commons Attribution 4.0 International License .

  • Kalani Pattison, “Generic Decision Matrix Example,” 2020. This image is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License . ↵
  • Kalani Pattison, “Example Decision Matrix with Randomly Generated Data,” 2020. This image is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License . ↵
  • Kalani Pattison, “Example of Decision Tree,” 2020. This image is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License . ↵

The quantitative and qualitative categories and standards used to evaluate something. (singular: criterion)

Decision-Making and Criteria Copyright © 2022 by David McMurrey; Jonathan Arnett; Kalani Pattison; and Nicole Hagstrom-Schmidt is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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  • Introduction
  • About Case Study Reports
  • Section A: Overview
  • Section B: Planning and Researching

Section C: Parts of a Case Study

  • Section D: Reviewing and Presenting
  • Section E: Revising Your Work
  • Section F: Resources
  • Your Workspace
  • Guided Writing Tools

Reflective Writing guide

  • About Lab Reports
  • Section C: Critical Features
  • Section D: Parts of a Lab Report

Reflective Writing guide

  • About Literature Review
  • Section C: Parts of a Literature Review
  • Section D: Critical Writing Skills

Lab Report writing guide

  • About Reflective Writing
  • Section B: How Can I Reflect?
  • Section C: How Do I Get Started?
  • Section D: Writing a Reflection

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Case Study Report Prepared by University of Guelph

In this section, we will take a closer look at the common components of case study reports and what readers expect to find in them.

What Will I Learn?

By successfully completing this section, you should be able to:

  • analyze the purpose and features of the sections of a case study report,
  • develop writing and organization strategies for writing each section, and
  • examine a case study report for strengths and weaknesses.

Female student studying with a partner.

Prepared by

University of Guelph

What Do I Need to Include in Each Section?

Each section of the case study report serves a unique purpose and includes key elements. While reports will vary from case to case and course to course, there are some “moves” that you will typically see writers make in each section.

In this part of the guide, we will help you learn what these moves are and how you can make them in your own case study report.

Worksheet: Case Study Report Outline

You were introduced to the Case Study Report Outline Template in Section A of this guide. It contains an outline of the major components of a case study report that you can consider using as a template when completing case study reports. If you haven’t already, it is recommended that you download the template now.

Case Study Report Outline Template

This outline sample of a Case Study Report should serve as a useful guide to help you get started.

Download PDF

Download the Case Study Report Outline Template .

Preview: PDF Worksheet

Case Study Sample: Cover Page

Tip: The components of a case study report will vary depending on the preferences of your institution and instructor. Be sure to refer to your assignment instructions in order to find out exactly what will be required when it comes to sections as well as formatting requirements for your report.

The Executive Summary

What is the purpose of an executive summary.

An executive summary typically provides a one-page snapshot of the entire report, focusing on the main highlights. It is usually included at the start of a case report before the main text. Depending on the preferences of your instructor and institution, the executive summary can be written in either paragraph- or point-form.

What should be included in an executive summary?

The executive summary of a case study report should include the following:

  • Problem statement

Tell readers in 1–2 sentences what the issue at hand is.

Example: The main problem facing Company XYZ is that sales are declining and employee morale is low. Without addressing these concerns, Company XYZ will be in serious trouble and may not be able to regain their standing as an industry leader.

Recommendation

What should be done to address the problem?

Example : In order to solve this problem it is recommended that Company XYZ undergo a change in strategy, structure, and culture. Specifically, it is recommended that Company XYZ

  • pursue a strategy that places a high level of importance on innovation;
  • restructure the organization so that it is flexible, innovative, and appropriate for the size of the organization; and
  • begin to reshape the company’s organizational culture and the way in which day-to-day business is conducted; managers at all levels of Company XYZ will need to emphasize the values of ethics, creativity, and trust.

Supporting arguments and evidence

Summary of all of the major sections of your report, highlighting the arguments and evidence that support your recommendation.

What is the key message you want readers to take away? Why is it important to solve this problem and what do you anticipate the outcomes will be if the recommendations are followed?

Tip: Keep these arguments in the same order they appear in the main text.

What Tips And Strategies Can I Employ to Write the Executive Summary?

The following is a list of tips and strategies for writing the executive summary section of a case study report:

  • Write the executive summary after all of the other sections of the report have been written.
  • Consider your role. Write from the perspective that you are asked to adopt; for example, did the case instructions ask you to assume the role of an internal organizational member? An external organizational consultant? Some other stakeholder? How will this influence the tone and content of the summary?
  • Avoid repeating case facts in detail. There can be a more general, summative opening sentence but the remainder of your executive summary should focus on going beyond the case information that was provided.
  • Clearly state and justify the specific recommendation that will solve the problem that is being encountered. Imagine a skeptical audience: Why should they believe you?
  • Include only key financial numbers and associated costing information.
  • Make the executive summary can stand alone. Readers should be able to understand the Executive Summary even if they don’t read the rest of the report.

Example: Annotated Case Study Report

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The Introduction

What is the purpose of the introduction.

The introduction should briefly introduce the report to the reader and should then clearly, succinctly, and accurately identify the main problem being faced by the key decision-maker.

What Should Be Included In An Introduction?

The introduction of a case study report should include the following:

  • Introductory sentence
  • Details about the problem (stick to details that relate to your recommendation)
  • Who are the most important decision-makers? Stakeholders?
  • What are the most important issues?
  • Why is this problem occurring? What are the root causes? Underlying factors?
  • When does this decision need to be made by? What is the decision timeline? Due date?
  • Recommendation: “It is recommended in the current report that [Company XYZ] pursue [this course of action] to address [these issues].”
  • Outline or road map of the remainder of the report

What Tips And Strategies Can I Employ to Write the Introduction?

The following is a list of tips and strategies for writing the introduction section of a case study report:

  • Avoid repeating case facts in detail and unnecessarily summarizing case facts that are already familiar to the reader.
  • State the main problem up front—be as specific and simple as possible.
  • Create a sense of urgency and importance associated with the situation by identifying the key stakeholders, problems, underlying factors, and timeline issues. Engage the reader by explaining the tension and complexity underlying the situation.
  • State your recommendation so that the reader can consider the rest of your report based on the solution being proposed; this will help to provide context for your analysis and other major report sections.
  • Remember: There should be no surprises when the reader gets to the actual recommendation section.

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Case Study Sample: Introduction

What Is The Purpose Of An Analysis Section?

The analysis section of your case study report is likely to be a very substantial part of your report. In this section you will examine the problem that you identified in the preceding section through a systematic and thorough application of your course and program content.

What Should Be Included?

The analysis section of a case study report should include the following:

  • Application of course and/or program content to: examine the problem being faced, and to prepare the reader for the justification and specifics of your Recommendation, Implementation Plan
  • References to related exhibits, which are appendices that appear at the end of the report in order to provide further elaboration or evidence regarding your analysis (e.g., graphs, figures, tables, financial documents)

How Should The Analysis Be Structured?

Be sure to check with your instructor to verify whether there is a specific format (e.g., SWOT, PEST) that should be followed. If no format is given, here are some general guidelines:

  • Begin with an examination of the problem, highlighting the most important parts. Avoid including unnecessary detail—focus only on the problem and its parts.
  • Apply course concepts or theories to the problem to provide insight into causes and effects, using headings to identify each section.
  • Conclude with a summary of what your analysis has revealed. Think of this final section as an answer to the question “So what?”

What Tips And Strategies Can I Employ to Write The Analysis Section?

The following is a list of tips and strategies for writing the analysis section of a case study report:

  • Use headings to subdivide the section.
  • Show your understanding of the course and/or program content by systematically applying what you have been learning to the specific problem.
  • Avoid using academic jargon. Instead, explain the concepts in your own words while referencing key sources.
  • Only include information that is directly relevant to the problem at hand. Avoid including course and program content that does not relate to the problem that you identified in the preceding section.
  • Be sure to discuss course and program concepts that will have an impact on your recommendation and implementation plan.
  • Use exhibits strategically to elaborate on ideas in the report; however, ensure that the exhibits expand on ideas you’ve already discussed. Avoid introducing exhibits that don’t tie into the main text.

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Case Study Sample: Analysis

Alternatives and Decision Criteria

What is the purpose of an alternatives and decision criteria section.

This section helps decision-makers consider all the possible ways they could address the problem by:

  • Presenting all viable, mutually exclusive solutions to the problem.
  • Outlining the criteria that will be systematically applied to determine the best solution to the problem.

What Are “Mutually Exclusive” Alternatives?

Alternatives are mutually exclusive if choosing one alternative rules out the others. Using mutually exclusive alternatives prevents a situation in which an organization has to implement multiple alternatives.

What Are “Decision Criteria”?

Key requirements that the recommendation will need to meet to successfully solve the problem.

The alternatives and decision criteria section of a case study report should include the following:

  • All viable, mutually exclusive alternatives
  • Decision criteria including:
  • Ranking of importance in terms of which decision criterion is the most important factor in order to be confident that the recommendation will solve the problem, second most important, etc.*
  • Weighting in terms of how important each of the decision criteria are in order to be confident that the recommendation will solve the problem.*
  • *Not all instructors or institutions will require ranking and weighting information as it is mostly determined in a subjective manner based on your analysis of the problem; nevertheless, it may assist in helping you to decide in a more systematic manner between two or more viable alternatives.

What Tips And Strategies Can I Employ to Write The Alternatives and Decision Section?

The following is a list of tips and strategies for writing the alternatives and decision section of a case study report:

  • Your instructor may make the alternatives section of a case study report optional; however, if you can think of at least one reasonable and viable alternative in addition to your recommendation, then this section should be included.
  • Be sure to list all reasonable and viable alternatives (including your recommendation).
  • Ensure that the alternatives listed are mutually exclusive.
  • In the decision criteria section, include the criteria that will be most effective for evaluating the alternative solutions to the problem being faced.
  • For a more systematic application of the decision criteria, assign importance and weighting to your decision criteria factors and then apply them to each of the alternatives.
  • Be sure to convincingly demonstrate that your recommendation is in fact the best choice compared with the other alternatives. Be explicit about how the criteria apply to the recommendations—do not assume that the reader will see the connection.

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Case Study Sample: Alternatives and Decision Criteria

Recommendations and Implementation Plan

What is the purpose of the recommendations and implementation plan section.

Although the reader will by now be well aware of your recommendation, in this section you will discuss all of the specifics of the recommendation for solving the problem. Moreover, you should also present a thorough and well thought-out implementation plan for executing the recommendation and ensuring its success.

The recommendations and implementation plan section of a case study report should include the following:

  • Detailed explanation of what your recommendation entails. What is it that will be done? What specific steps will be involved? What equipment or expertise will be needed?
  • Explanation of your implementation plan, including:
  • Who will be responsible for what part of the implementation plan?
  • When will the different parts of the recommendation be implemented? Short-, medium-, and long-term implementation plan?
  • What will the cost be of these required actions?
  • What will the impact of this recommendation be on other parts of the organization?
  • What could go wrong, and what contingency plans are in place?

What Tips And Strategies Can I Employ to Write The Recommendations And Implementation Plan?

The following is a list of tips and strategies for writing the recommendations and implementation plan of a case study report:

  • Be sure to include all of the details of your recommendation. You have already outlined your more general recommendation to the reader earlier in your report but now is your opportunity to provide the more specific details regarding your recommendation.
  • Include a well thought-out implementation plan that includes all of the specifics that an organization would actually require in order to realistically implement your recommendation. Try to put yourself in the mindset of the organizational members responsible for implementing your recommendation; what step-by-step specifics will they need to be aware of in order to take your recommendation and ensure that it is successfully implemented?
  • Including a contingency analysis of the possible problems that could arise from your recommendation. What might go wrong? How will you address these problems should they come up in order to still be able to successfully implement your recommendation?
  • Also be sure to consider the expected as well as the potentially unexpected impact of your recommendation on the people within the organization.
  • A good strategy would be to explain how the organizational leaders will evaluate whether your implementation plan has been successful and whether the recommendation has achieved the desired results. Be specific regarding the evaluation metrics that should be used (e.g., measures of customer satisfaction, measures of employee engagement, profitability analyses)

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Case Study Sample: Recommendations and Implementation Plan

Conclusion and References

What is the purpose of the conclusion.

The purpose of the conclusion section is to leave your reader with one or two last, powerful statements that will help to reinforce the recommendation that you are proposing.

Some instructors and institutions do not require a conclusion section, but if done effectively, it can end your case report on a strong note.

The conclusion section of a case study report should include the following:

  • A summary sentence that explains what we have learned from the report
  • One or two impactful and memorable statements to conclude your report (what is the most important thing that the organization should take away from the report?)

What Tips And Strategies Can I Employ to Write The Conclusion?

The following is a list of tips and strategies for writing the conclusion of a case study report:

  • Avoid an abrupt ending to your written case report. Provide a few sentences to help draw things to a natural close.
  • Persuasively summarize how your recommendation will solve the problem at hand.
  • Ensure that you yourself are persuaded and convinced by the concluding statement; for example, would you believe that this solution will work if you were the person reading your report?

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Case Study Sample: Conclusion and References

Citing Your Sources

What sources should you cite.

You should use in-text citations for any idea that is not your own. Moreover, these citations should be reflected in your references list, which you will be required to provide at the end of your case study report. Your institution will have their own plagiarism and academic misconduct policies, which you should familiarize yourself with; however, a best practice will be to be cautious and ensure that all of the following are appropriately cited and referenced throughout your work:

  • Ideas from sources other than your own thinking
  • Direct quotations, which you should use infrequently in your case study reports
  • Paraphrasing and/or summarizing the work of others
  • Course and/or program specific definitions, theories, models, etc.
  • Information from popular press articles
  • Data, financial documents, etc. from annual reports, company webpages

What Are The Common Citation Styles?

It is likely that your instructor will let you know what his/her preferences are in terms of a citation style; however, some of the most common citation styles include:

  • American Psychological Association (APA)
  • Chicago Manual of Style (Chicago)
  • Modern Language Association (MLA)

Key Takeaways and References

Key takeaways.

Now that you've completed this section, keep the following things in mind:

  • The key to most case study reports is logic. There is usually not just one desired correct response to a case study, but rather, there are more and less logical, practical, and reasonable responses. Incorporating sound and strong logic throughout your report is paramount.
  • Ensure that your report is written at a level that would appeal to a business audience rather than an academic one.
  • Lastly, can you confidently stand behind, advocate for, and answer questions regarding your case response? If so, then your work is likely in a good position!
  • The next steps for this set of modules will involve helping you to take all of the work that has gone into your written report in order to prepare a verbal presentation of your work.

American Psychological Association (2009). Publication manual of the American Psychological Association (6th ed.). Washington, DC: American Psychological Association.

Lipson, C. (2011). Cite right: A quick guide to citation styles—MLA, APA, Chicago, the sciences, professions, and more (2nd ed.). Chicago: The University Of Chicago Press.

Modern Language Association (2008). MLA style manual and guide to scholarly publishing (3rd ed.). New York: Modern Language Association of America.

Modern Language Association (2009). The MLA handbook for writers of research papers (7th ed.). New York: Modern Language Association of America.

University of Chicago Press Staff. (2010). The Chicago manual of style: The essential guide for writers, editors, and publishers (16th ed.). Chicago: The University Of Chicago Press.

University of Guelph. (2015). Case Study Report Outline Template .

University of Guelph. (2015). The Executive Summary. Example: Annotated Case Study Report . (Interactive Activity).

University of Guelph. (2015). The Executive Summary. Example: Annotated Case Study Report . (PDF).

University of Guelph. (2015). The Introduction. Example: Annotated Case Study Report . (Interactive Activity).

University of Guelph. (2015). The Introduction. Example: Annotated Case Study Report . (PDF).

University of Guelph. (2015). Analysis. Example: Annotated Case Study Report . (Interactive Activity).

University of Guelph. (2015). Analysis. Example: Annotated Case Study Report . (PDF).

University of Guelph. (2015). Alternatives and Decision Criteria. Example: Annotated Case Study Report . (Interactive Activity).

University of Guelph. (2015). Alternatives and Decision Criteria. Example: Annotated Case Study Report . (PDF).

University of Guelph. (2015). Recommendations and Implementation Plan. Example: Annotated Case Study Report . (Interactive Activity).

University of Guelph. (2015). Recommendations and Implementation Plan. Example: Annotated Case Study Report . (PDF).

University of Guelph. (2015). Conclusion and References. Example: Annotated Case Study Report . (Interactive Activity).

University of Guelph. (2015). Conclusion and References. Example: Annotated Case Study Report . (PDF).

Next Section Overview

In Section D: Reviewing and Presenting , we will explore understanding and meeting your instructor's expectations for the report and presentation.

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  • Knowledge Base

Methodology

  • 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 November 20, 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, other interesting articles.

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.

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decision criteria in case study examples

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

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

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.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

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.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

The aim is to gain as thorough an understanding as possible of the case and its context.

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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.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

  • Normal distribution
  • Degrees of freedom
  • Null hypothesis
  • Discourse analysis
  • Control groups
  • Mixed methods research
  • Non-probability sampling
  • Quantitative research
  • Ecological validity

Research bias

  • Rosenthal effect
  • Implicit bias
  • Cognitive bias
  • Selection bias
  • Negativity bias
  • Status quo bias

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Choose the Right Decision Criteria

Ali Cox

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During a recent Facilitating a Requirements Workshop class, my students and I had great discussion regarding decision criteria. While the discussion came out of a class centered on business analysis, the answer resonates with almost any industry. Since my students asked me for a quick write up to reference, I thought it might help others and wanted to share. First, let’s take a quick step back to the question that started our discussion.

How do we decide which alternative is the best when trying to help a group make a decision?

We should always employ decision criteria in making any decision. Let’s explore this by using an example of trying to decide which car to buy. What is important to us that will help us determine which car will best fit our situation? Is it style, comfort, noise, gas mileage, speed, manual/transmission, accessibility, price, payment terms available, reliability…?

You can think of this criteria as part of the user story around the decision being made. For example, this user story might apply to some: “I need the car to look cool so that I can impress women.” One that is much more realistic for me would be “I need the car to be reliable so that I don’t have to worry about breakdowns in traffic.” The criteria are going to help you determine that a successful decision has been made. In this example, success would be that we purchased the right car for our situation.

The decision criteria in a business setting are those variables or characteristics that are important to the organization making the decision. They should help evaluate the alternatives from which you are choosing. I use the word “variables” because you can disregard any characteristics that are constant among the alternatives. For example, if all of the cars I am evaluating get the same gas mileage, then disregard that characteristic as it will not help you choose between the alternatives.

The decision criteria should be measurable and should be within scope of the problem you are trying to solve. On criteria that seem immeasurable, you should at least be able to compare one to another. For example, the typical software characteristic “user friendly” is not measurable as stated. You could either list out what makes the application user friendly for your organization or you can try out the applications and have a rankings for the alternatives on relative “user friendliness” between them.

These are some typical decision criteria:

  • Ease of implementation
  • Ease of modification/scalability/flexibility
  • Employee morale
  • Risk levels
  • Cost savings
  • Increase in sales or market share
  • Return on investment
  • Similarity to existing organization products
  • Increase in customer satisfaction

When in a group decision-making situation, it is often helpful to have the group brainstorm the decision criteria. This helps ensure buy in of the decision itself because the criteria is measurable and not just a “well I feel like we should buy this product because I like it.” You might also weigh the criteria. For example, cost savings might have a higher weight than ease of use.

Following a structured decision making process will not only enable faster decision-making, it also improves the probability that you will get a consensus on the decision. Consensus is determined to exist when the entire group agrees to support the decision, even if they do not totally agree with it. When getting a group to make a decision, an open discussion with logical presentation of the decision criteria will drive the group toward consensus.

Take a look at our Decision Modeling Essentials Course for more on Decision Criteria! Management 3.0 also utilizes two great tools, Delegation Poker and Delegation Boards, to help facilitate decision making. Check out our Guide for Decision Making Using Delegation Poker and Boards for more more about what they are and how to use them.

– Ali

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Make milestones matter with ‘decision gates’—stage gates with real teeth

Stage gates often provide too little scrutiny into projects. Decision gates channel resources to the strongest business cases.

Too many projects get too little scrutiny under ordinary stage gates. To get serious about milestones, adopt decision gates that channel resources only to the most rigorous business cases .

In recent decades, companies have sought to bring rigor and transparency to the product-development process by holding stage-gate meetings over the course of a project. But at most organizations, stage gates fall far short of achieving their goals. Too often, stage-gate meetings are little more than reviews of product maturity, with limited focus on decision making. As a result, people see them merely as process formalities that lack teeth.

Because project leaders do not always convene the right stakeholders from across functions, the right people are often not present to make decisions affecting multiple stages of the product lifecycle. Given that funding is rarely delayed or halted at a traditional stage gate, participants have little incentive to prepare for decision-oriented discussions. The failure to conduct decision-oriented meetings invariably means that serious project issues do not become evident until late in the development process. Even when issues are identified, the process for escalating them is typically unclear, with limited follow-up.

To make stage gates the effective tool they were intended to be, companies should reinvent them as decision gates. Decision gates are no-turning-back moments at which the organization—and, more important, senior management—commits to major investment or design decisions that balance the product-level trade-offs among cost, time, and quality.

The project leader orchestrates the activities of cross-functional participants representing development, procurement, production, and service, each of which has clear responsibilities at a given decision gate. Preparation for meetings is thorough and guided by standard templates, and the meetings are meaningful but short. Based on the outcomes of the gates (or the inability to make a decision), clear next steps are articulated for all involved functions, and any issues are escalated as necessary.

Finally—and this is the biggest innovation with the highest impact in moving to decision gates—it is clear to everyone in the room that by signing off on the project they are, in effect, signing their name to a large check that commits the organization to spending significant money or resources. This commitment creates the incentive required to ensure both that the gate reviews are meaningful and that they provide the necessary transparency to actual project status.

Converting the typical stage-gate development process to a decision-gate process entails a fundamental mind-set shift. The entire product-development organization must become focused on developing and refining a rigorous business case in each phase of the project life cycle. This transition generally takes at least a year.

How decision gates work

Connecting the outcome of decision gates to the release of funding ensures that participants have an incentive to thoroughly prepare for meetings and that reviewers drill into the soundness of the business case before allowing the project to proceed to the next stage.

Prior to each decision gate meeting, all relevant functions should prepare the information required for making an investment or design decision. The fact base provided by a meticulous preparation process enables reviewers to apply substantive business judgment in assessing requests for funding at the gate.

During the decision-gate meeting, all functions should present a project status assessment and make a recommendation for how to proceed. Senior management should carefully consider the status assessment and decide on the next step. Most important, the gate decision should provide the basis for either releasing or blocking the budget for the next phase or other types of funding, such as money for hard tooling, building prototypes, or supplier development.

It is equally important to ensure that the decision taken at a gate is properly executed. Progress and design reviews should be initiated throughout the project-execution process, to enable the project team to monitor and address any gaps between the actual and planned output. This continuous monitoring ensures a strong focus on successful project execution and budget adherence.

Developing the gates

To develop decision gates, the company should identify five to ten critical management decisions over the life of a project, from the feasibility assessment through launch (Exhibit 1). These decisions should be articulated in decision-oriented terms, such as "approve product development plan" or "approve ramp-up of production," and considered separately for each product. The company should also articulate two to five decisions that will be repeated for each main component, including design choices and outsourcing decisions. Additionally, it should schedule one to three regular reviews of progress and system integrity over the project life cycle.

decision criteria in case study examples

For each decision gate, the organization must prepare detailed descriptions of responsibilities and the required preparation and follow-up. The project management office (PMO) specifies the inputs needed for each decision and prepares templates for submitting the required information. The PMO should also set each function's role in preparing for the subelements of the decision and identify the specific person responsible for collecting and presenting the relevant material. Responsibilities for the follow-up actions and decision execution should also be specified.

The company should establish decision-making criteria to test the business case at each decision-gate meeting. The overall evaluation should consider whether the business case is holding as expected and assess any risks and the related mitigation plans. In addition, the project leaders should consider criteria relating to cost, time, and quality and determine any deviations from targets (Exhibit 2).

decision criteria in case study examples

Operationalizing the process

To operationalize the decision-gate process, the organization must put in place multiple enablers, including IT systems, skills and capabilities, project staffing, and a review architecture. IT systems at the company level can be used to enable tasks such as data management and project tracking. Many organizations will need to build more advanced skills and capabilities in topics such as cost estimation and design robustness. Organizations should apply resource-planning techniques that ensure the right level and composition of staffing for each project on the basis of its complexity. They must also set out a cadence of meetings at which the cross-functional project team and department heads can review progress and identify issues in between the decision-gate meetings.

Innovation in product development is supported by a parallel flow of technology development within the organization. This flow of new technology must be defined and integrated into the decision-gate process. Only technologies that have matured should be included in the product development flow at the concept-approval or prototype stage.

In operationalizing decision gates, it is critical to recognize that organizations cannot establish a one-size-fits-all process for the full range of development projects. Because projects vary in terms of their timeline and resource intensity, the organization needs to ensure the decision-gate process is scalable. Customization can be facilitated by identifying a set of archetypes for development projects, ranging from simplest to most complex. For example, project timelines will be significantly shorter for projects that entail refreshing a product model, whereas they will be longer for projects that involve major redesigns or new product development.

A mature decision-gate process ensures rigor and transparency for projects across the product life cycle and delivers robust outcomes for cost, time, and quality. By providing incentives for project teams to prepare meticulously for gate meetings and forcing project leaders to make tangible decisions, the process sends a clear signal that the product development organization has zero tolerance for mediocrity

About the authors: Nitesh Gupta is a partner in McKinsey’s Delhi office, Sander Smits is a partner in the Amsterdam office, and Florian Weig is a senior partner in Munich office.

This article was originally published in Development Excellence: The engine to drive product success (McKinsey & Co., 2016), under the title, "Using decision gates to give project milestones real teeth."

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What is a decision matrix? Templates, examples, and types

decision criteria in case study examples

In the dynamic world of business, daily operations bombard entrepreneurs, business stakeholders, and product managers with a deluge of decisions. These choices, big or small, carve the trajectory of business growth. They range from prioritizing everyday tasks to assessing opportunities, creating processes, and far beyond. Often, the complexity weighs heavily on an organization’s success or failure.

What Is A Decision Matrix? Templates, Examples, And Types

One tool that can help you navigate this maze is the decision matrix.

Often, the plethora of choices business leaders must make generates decision fatigue, clouding objectivity and escalating subjectivity. The decision matrix comes to the rescue by distilling choices down to their core attributes, offering a simplified, objective perspective for comparison.

In this guide, we’ll show you how using a decision matrix can help you rise above the chaos, prioritize alternatives, and make insightful decisions with confidence and clarity.

What is a decision matrix?

A decision matrix, also known as a decision-making or weighted decision matrix, facilitates the evaluation and prioritization of multiple alternatives against diverse criteria. This universal tool finds use in varied domains, from business strategy and project management to product development.

At the heart of a decision matrix is a straightforward grid. This grid catalogues options as rows, while the criteria for assessment form the columns.

Let’s look at an example. Here, the options are three different software features:

  • User analytics
  • Mobile responsiveness
  • API development

The criteria for evaluating these options are customer need, development cost (where a lower cost is better, so it’s scored in reverse), and business value.

Each of these criteria is scored on a scale from 1 to 5. The total score is the sum of these scores for each option. This can provide an objective framework to decide which feature to focus on developing next:

Each intersection between an option and a criterion then houses a score that reflects how well that option fulfills the criterion. The total score for an option, calculated by aggregating these individual scores, acts as a crucial guidepost in making informed decisions. In essence, an option with a higher total score often indicates a more promising choice.

The charm of the decision matrix lies in its logical rigor. Instead of basing decisions on intuitions or assumptions, this tool fosters a methodical analysis, ultimately promoting more insightful choices. Here are some of the notable benefits:

  • Transparency  — The decision matrix fosters impartiality by evaluating various options against a predefined set of criteria, adding a layer of transparency to the decision-making process
  • Clarity  — By dissecting options based on their advantages and disadvantages, the decision matrix illuminates the path to informed decisions, bringing clarity and structure to the process
  • Logical reasoning  — The tool provides a framework to juxtapose different options, scrutinizing the strengths and weaknesses of each, facilitating decisions rooted in logic and reason
  • Prioritization  — A decision matrix enables effortless prioritization by quantifying the relative importance of each criterion for every option
  • Improved communication  — Decision matrices aid in articulating the rationale behind decisions. By showcasing the logical evaluation process, it paves the way for easy communication with stakeholders and helps garner their approval

The decision matrix proves particularly potent in product management. It equips product managers to assess and balance customer needs, market trends, business objectives, and goals, thereby making informed, data-driven decisions.

6 types of decision matrices

Decision matrices emerge in diverse forms, each tailored for specific scenarios and decision-making processes. Some of the more prevalent variants are:

  • Simple decision matrix
  • Eisenhower matrix
  • Analytical hierarchy process (AHP)
  • Weighted decision matrix
  • Pugh matrix
  • Decision tree

1. Simple decision matrix

The simple decision matrix serves as the basic blueprint. It contrasts options against chosen criteria, enabling decision-makers to assign scores based on a predetermined scale:

Simple Decision Matrix Example

Typically, these scores are numerical, offering a straightforward method for comparison.

decision criteria in case study examples

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decision criteria in case study examples

2. Eisenhower matrix

The Eisenhower Matrix, also known as the Eisenhower Decision Matrix, Eisenhower Box, and Urgent-Important Matrix, is a time and task management tool that helps individuals prioritize their tasks by considering two factors: urgency and importance.

To use the Eisenhower Matrix, first identify all the tasks you need to complete. Then, based on the urgency and importance of each one, place it in one of the four quadrants of the matrix:

Eisenhower Matrix

3. Analytical hierarchy process (AHP)

The AHP takes decision-making to a new level of complexity. Rather than merely contrasting options against criteria, the AHP introduces the concept of sub-criteria, granting a deeper level of analysis:

Analytic Hierarchy Process Example

Additionally, the AHP uses pairwise comparisons, allowing stakeholders to judge the relative importance of each goal. In this process, the AHP does not dictate a ‘correct’ decision. Instead, it illuminates the path to the decision that best aligns with the established goals.

Such a tool proves invaluable in strategic decision-making contexts, such as succession planning or resource allocation.

4. Weighted decision matrix

This variation of a decision matrix introduces a sense of importance to each criterion. By assigning weights and scores to individual criteria, the weighted decision matrix helps discern the priority option:

Weighted Decision Matrix Example

A weighted decision matrix can be deployed in various scenarios, such as when evaluating product features or backlogs against criteria like time, effort, impact, and reach.

5. Pugh matrix

The Pugh matrix adds an element of reference to the decision-making process. It operates by selecting a benchmark option, then evaluates all other alternatives in comparison to this reference point:

Pugh Decision Matrix Example

The Pugh matrix thus provides a relative analysis, facilitating informed decision-making.

6. Decision tree

When decision-making involves sequential dependencies, decision trees come into play. This tool graphically represents potential decisions and their outcomes in a tree-like structure. Every node in the tree depicts a decision point, and the branches signify different possible actions:

Decision Tree Example

By offering a visual exploration of decision paths, decision trees greatly simplify the decision-making process.

How to create a decision matrix (7 steps)

Building a decision matrix is a process that necessitates attention to detail and an understanding of the objectives at hand. The following steps serve as a road map for constructing an effective decision matrix:

  • Define the objective — Clearly outline the decision that needs to be made. This could be selecting a vendor, prioritizing product features, or any other decision that requires a comprehensive evaluation
  • Identify the criteria — Establish the measurable criteria that align with the decision objective. These criteria form the basis for evaluating the options at hand
  • Assign weights — Allocate weights to each criterion to reflect its relative importance. This step helps differentiate the significance of each criterion and guides the scoring process
  • Define the rating scale — Determine a scale to measure each option’s suitability against each criterion. This scale could be quantitative (such as 1-5) or qualitative (like poor, fair, good, and excellent)
  • Evaluate options — Measure each option against each criterion and assign a score on the predetermined scale. Be sure to involve relevant stakeholders in this step to ensure a well-rounded evaluation
  • Compute the scores — Multiply each criterion’s weight by the respective score given to each option. Then, sum these values to derive the total score for each option
  • Make the decision — Review the total scores and select the option with the highest score. Remember, the decision matrix is a guide, not a dictator. It should inform and influence the decision, not solely determine it

Mastering the art of the decision matrix can be transformative. It can elevate an organization’s decision-making process from chaotic and ambiguous to structured and insightful. So, embrace this tool, navigate the decision labyrinth with ease, and accelerate towards your business goals.

Decision matrix templates

The templates below are designed to help you get started creating a decision matrix for your product or business:

Simple decision matrix template

Weighted decision matrix template, pugh matrix template.

You can fill out the following decision matrix template by following the instructions outlined above:

Fill out the score for each option based on each criterion, then multiply that score by the weight of the criterion to get the weighted score. Sum these up for each option to get the total weighted score:

Use one option as a reference and fill out whether each other option is better, the same, or worse than the reference based on each criterion. This provides a relative comparison between options:

Challenges in using a decision matrix

While decision matrices offer considerable benefits, it’s crucial to remember that no tool is flawless. Recognizing potential pitfalls and challenges can help users mitigate their impact.

Here are some challenges associated with using decision matrices:

  • Subjectivity — Although decision matrices provide a structured approach, the scoring system inherently contains some level of subjectivity. Different stakeholders may assign different scores to the same option based on their perspective
  • Complexity — Decision matrices can become complex, especially when dealing with a large number of criteria or options. This complexity could lead to confusion and increase the time needed for the decision-making process
  • Overemphasis on quantification — Not all decisions can be adequately quantified or measured. Sometimes, the nuances of certain criteria may be overlooked when reduced to numbers. This is particularly relevant for considerations that involve emotions, values, or personal preferences

Despite these challenges, decision matrices can still provide a robust structure for decision-making. Here’s how you can manage the mentioned obstacles:

  • Tackle subjectivity — Involve multiple stakeholders in the scoring process to create a more balanced and comprehensive evaluation. You can also use a consensus method for scoring, or average out individual scores to reduce bias
  • Manage complexity — Make sure the criteria chosen are specific, measurable, and relevant to the decision at hand. Keep the number of options and criteria manageable. Remember, the goal is to assist the decision-making process, not to overwhelm it
  • Balance quantitative and qualitative analysis — Use a decision matrix in conjunction with other decision-making tools. For instance, a SWOT analysis could help explore qualitative factors, while a decision matrix quantifies and prioritizes options. These tools can complement each other, providing a holistic view of the situation

Examples of use cases in product management

Product management involves making numerous impactful decisions. A decision matrix can aid product managers in various critical areas, including backlog/feature prioritization, vendor selection, roadmap planning, A/B testing, go-to-market (GTM) strategy, risk mitigation, and more. Here’s how:

  • Feature prioritization — A decision matrix can help you evaluate and compare features based on criteria such as impact, technical feasibility, effort, demand, and strategic fit
  • Market opportunity analysis — Using a decision matrix enables you to assess and compare multiple market opportunities and facilitate priority setting
  • Vendor selection — A decision matrix help you can evaluate vendors on criteria like pricing, support, reliability, capacity, scalability, and alignment with the company’s values, assisting in selecting the most suitable and reliable vendors
  • Roadmap planning — Evaluating factors such as customer value, business goals, technical feasibility, resource requirements, market trends, tech debt, bugs, and feedback can aid in determining which initiatives and features to include in the roadmap
  • GTM strategy — A decision matrix can help you determine the best market entry strategy for new products and features by evaluating criteria like size, competition, customer segment, regulatory requirements, and available resources
  • Risk assessment — A decision matrix can assist in assessing risks based on complexity, legal/regulatory compliance, financial issues, and market conditions. This allows the product team to anticipate high-risk areas and devise mitigation strategies
  • A/B testing and experimentation — A decision matrix can guide the product team in deciding which variation of an experiment performed better , thus informing future iterations or decisions

These examples demonstrate the practical applications of a decision matrix, enabling product managers to leverage data throughout the product lifecycle.

Tips and best practices

As a product manager, every decision you make is a step forward in your product’s journey, and you want to make sure each step counts. By embracing a few best practices, you’ll ensure your decision matrix is not just a rote process but a powerful tool, enabling you to make strategic, data-driven decisions.

Here are some tips and tactics for product managers when using a decision matrix:

  • Criteria and weights — Identify key criteria relevant to the decision and reduce any unnecessary ones. Keep the criteria specific and limited in number, adhering to the KISS principle (keep it simple, stupid)
  • Seek inputs from stakeholders — Involving stakeholders provides multiple perspectives, diverse insights, and a more comprehensive assessment of options
  • Validate assumptions — Verify the accuracy of the criteria to ensure the reliability of the decision matrix. This step reduces bias and improves the integrity of the decision-making process
  • Analyze results — Consider the context and other factors before selecting the highest-scoring option. Conduct a sensitivity analysis by adjusting weights across the criteria to identify the factors most impacting the decision
  • Review and revise — Update the decision matrix as factors and criteria change. Add new criteria as necessary. Remember, flexibility is key
  • Trust your judgment — Use the decision matrix as a guide, but don’t disregard your instincts and expertise. Sometimes, intuition can play a critical role in decision-making

A decision matrix encourages objectivity over subjectivity in comparing options and identifying optimal solutions. While every tool has limitations, a product team can enhance decision-making by combining a decision matrix with other frameworks and tools, such as SWOT, RICE, and 2×2 prioritization.

The decision matrix approach allows for consideration of additional factors and contexts in decision-making. In essence, a decision matrix provides a systematic framework that, in conjunction with other tools, improves clarity and enables product teams to make informed, well-considered decisions.

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How To Make Recommendation in Case Study (With Examples)

How To Make Recommendation in Case Study (With Examples)

After analyzing your case study’s problem and suggesting possible courses of action , you’re now ready to conclude it on a high note. 

But first, you need to write your recommendation to address the problem. In this article, we will guide you on how to make a recommendation in a case study. 

Table of Contents

What is recommendation in case study, what is the purpose of recommendation in the case study, 1. review your case study’s problem, 2. assess your case study’s alternative courses of action, 3. pick your case study’s best alternative course of action, 4. explain in detail why you recommend your preferred course of action, examples of recommendations in case study, tips and warnings.

example of recommendation in case study 1

The Recommendation details your most preferred solution for your case study’s problem.

After identifying and analyzing the problem, your next step is to suggest potential solutions. You did this in the Alternative Courses of Action (ACA) section. Once you’re done writing your ACAs, you need to pick which among these ACAs is the best. The chosen course of action will be the one you’re writing in the recommendation section. 

The Recommendation portion also provides a thorough justification for selecting your most preferred solution. 

Notice how a recommendation in a case study differs from a recommendation in a research paper . In the latter, the recommendation tells your reader some potential studies that can be performed in the future to support your findings or to explore factors that you’re unable to cover. 

example of recommendation in case study 2

Your main goal in writing a case study is not only to understand the case at hand but also to think of a feasible solution. However, there are multiple ways to approach an issue. Since it’s impossible to implement all these solutions at once, you only need to pick the best one. 

The Recommendation portion tells the readers which among the potential solutions is best to implement given the constraints of an organization or business. This section allows you to introduce, defend, and explain this optimal solution. 

How To Write Recommendation in Case Study

example of recommendation in case study 3

You cannot recommend a solution if you are unable to grasp your case study’s issue. Make sure that you’re aware of the problem as well as the viewpoint from which you want to analyze it . 

example of recommendation in case study 4

Once you’ve fully grasped your case study’s problem, it’s time to suggest some feasible solutions to address it. A separate section of your manuscript called the Alternative Courses of Action (ACA) is dedicated to discussing these potential solutions. 

Afterward, you need to evaluate each ACA by identifying its respective advantages and disadvantages. 

example of recommendation in case study 5

After evaluating each proposed ACA, pick the one you’ll recommend to address the problem. All alternatives have their pros and cons so you must use your discretion in picking the best among these ACAs.

To help you decide which ACA to pick, here are some factors to consider:

  • Realistic : The organization must have sufficient knowledge, expertise, resources, and manpower to execute the recommended solution. 
  • Economical: The recommended solution must be cost-effective.
  • Legal: The recommended solution must adhere to applicable laws.
  • Ethical: The recommended solution must not have moral repercussions. 
  • Timely: The recommended solution can be executed within the expected timeframe. 

You may also use a decision matrix to assist you in picking the best ACA 1 .  This matrix allows you to rank the ACAs based on your criteria. Please refer to our examples in the next section for an example of a Recommendation formed using a decision matrix. 

example of recommendation in case study 6

Provide your justifications for why you recommend your preferred solution. You can also explain why other alternatives are not chosen 2 .  

example of recommendation in case study 7

To help you understand how to make recommendations in a case study, let’s take a look at some examples below.

Case Study Problem : Lemongate Hotel is facing an overwhelming increase in the number of reservations due to a sudden implementation of a Local Government policy that boosts the city’s tourism. Although Lemongate Hotel has a sufficient area to accommodate the influx of tourists, the management is wary of the potential decline in the hotel’s quality of service while striving to meet the sudden increase in reservations. 

Alternative Courses of Action:

  • ACA 1: Relax hiring qualifications to employ more hotel employees to ensure that sufficient human resources can provide quality hotel service
  • ACA 2: Increase hotel reservation fees and other costs as a response to the influx of tourists demanding hotel accommodation
  • ACA 3: Reduce privileges and hotel services enjoyed by each customer so that hotel employees will not be overwhelmed by the increase in accommodations.

Recommendation: 

Upon analysis of the problem, it is recommended to implement ACA 1. Among all suggested ACAs, this option is the easiest to execute with the minimal cost required. It will not also impact potential profits and customers’ satisfaction with hotel service.

Meanwhile, implementing ACA 2 might discourage customers from making reservations due to higher fees and look for other hotels as substitutes. It is also not recommended to do ACA 3 because reducing hotel services and privileges offered to customers might harm the hotel’s public reputation in the long run. 

The first paragraph of our sample recommendation specifies what ACA is best to implement and why.

Meanwhile, the succeeding paragraphs explain that ACA 2 and ACA 3 are not optimal solutions due to some of their limitations and potential negative impacts on the organization. 

Example 2 (with Decision Matrix)

Case Study: Last week, Pristine Footwear released its newest sneakers model for women – “Flightless.” However, the management noticed that “Flightless” had a mediocre sales performance in the previous week. For this reason, “Flightless” might be pulled out in the next few months.  The management must decide on the fate of “Flightless” with Pristine Footwear’s financial performance in mind. 

  • ACA 1: Revamp “Flightless” marketing by hiring celebrities/social media influencers to promote the product
  • ACA 2: Improve the “Flightless” current model by tweaking some features to fit current style trends
  • ACA 3: Sell “Flightless” at a lower price to encourage more customers
  • ACA 4: Stop production of “Flightless” after a couple of weeks to cut losses

Decision Matrix

Recommendation

Based on the decision matrix above 3 , the best course of action that Pristine Wear, Inc. must employ is ACA 3 or selling “Flightless” shoes at lower prices to encourage more customers. This solution can be implemented immediately without the need for an excessive amount of financial resources. Since lower prices entice customers to purchase more, “Flightless” sales might perform better given a reduction in its price.

In this example, the recommendation was formed with the help of a decision matrix. Each ACA was given a score of between 1 – 4 for each criterion. Note that the criterion used depends on the priorities of an organization, so there’s no standardized way to make this matrix. 

Meanwhile, the recommendation we’ve made here consists of only one paragraph. Although the matrix already revealed that ACA 3 tops the selection, we still provided a clear explanation of why it is the best. 

  • Recommend with persuasion 4 . You may use data and statistics to back up your claim. Another option is to show that your preferred solution fits your theoretical knowledge about the case. For instance, if your recommendation involves reducing prices to entice customers to buy higher quantities of your products, you may invoke the “law of demand” 5 as a theoretical foundation of your recommendation. 
  • Be prepared to make an implementation plan. Some case study formats require an implementation plan integrated with your recommendation. Basically, the implementation plan provides a thorough guide on how to execute your chosen solution (e.g., a step-by-step plan with a schedule).
  • Manalili, K. (2021 – 2022). Selection of Best Applicant (Unpublished master’s thesis). Bulacan Agricultural State College. Retrieved September 23, 2022, from https://www.studocu.com/ph/document/bulacan-agricultural-state-college/business-administration/case-study-human-rights/19062233.
  • How to Analyze a Case Study. (n.d.). Retrieved September 23, 2022, from https://wps.prenhall.com/bp_laudon_essbus_7/48/12303/3149605.cw/content/index.html
  • Nguyen, C. (2022, April 13). How to Use a Decision Matrix to Assist Business Decision Making. Retrieved September 23, 2022, from https://venngage.com/blog/decision-matrix/
  • Case Study Analysis: Examples + How-to Guide & Writing Tips. (n.d.). Retrieved September 23, 2022, from https://custom-writing.org/blog/great-case-study-analysis
  • Hayes, A. (2022, January O8). Law of demand. Retrieved September 23, 2022, from https://www.investopedia.com/terms/l/lawofdemand.asp

Written by Jewel Kyle Fabula

in Career and Education , Juander How

Last Updated September 23, 2022 07:23 PM

decision criteria in case study examples

Jewel Kyle Fabula

Jewel Kyle Fabula is a Bachelor of Science in Economics student at the University of the Philippines Diliman. His passion for learning mathematics developed as he competed in some mathematics competitions during his Junior High School years. He loves cats, playing video games, and listening to music.

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  • 7 quick and easy steps to creating a de ...

7 quick and easy steps to creating a decision matrix, with examples

Julia Martins contributor headshot

Decisions, decisions, decisions. Making good decisions can help you steer your team in the right direction and hit your goals—but how do you know which decision is the right one? When faced with two seemingly equal choices, do you flip a coin? Roll the dice? Ask a Magic 8-Ball for help? 

Decision-making is a critical part of good business planning—but it can be tricky to know which option is the right one. The key is making a quick decision without being hasty, and making the right decision without losing velocity.

What is a decision matrix?

A decision matrix is a tool to evaluate and select the best option between different choices. This tool is particularly useful if you are deciding between more than one option and there are several factors you need to consider in order to make your final decision. 

You may have heard a decision matrix called by another term—even though they’re all talking about the same thing. Some other names for decision matrix include:

Pugh matrix

Grid analysis

Multi-attribute utility theory

Problem selection matrix

Decision grid

When to use a decision matrix

You don’t always need to use a decision matrix. This process is powerful—and relatively easy—but it’s most effective when you’re deciding between several comparable options. If the evaluation criteria aren’t the same between your different choices, then a decision matrix likely isn’t the best decision-making tool. For example, a decision matrix won’t help you decide what direction your team should take for the next year because the things you’re deciding between aren’t comparable.

Use a decision matrix if you are:

Comparing multiple, similar options

Narrowing down various options into one final decision

Weighing a variety of important factors 

Hoping to approach the decision from a logical viewpoint, instead of an emotional or intuitive one

If a decision matrix isn’t right for your current situation, learn about other decision-making approaches below.

How to create a decision matrix in 7 steps

A decision matrix can help you evaluate the best option between different choices, based on several important factors and their relative importance. There are seven steps to creating a decision matrix:

1. Identify your alternatives

Decision matrices are a helpful tool to decide the best option between a set of similar choices. Before you can build your matrix, identify the options you’re deciding between.

For example, let’s say your team is launching a new brand campaign this summer. You need to decide on a vendor to create the visuals and videos for the design. Right now, you’ve identified three design agencies, though they each have their pros and cons.

2. Identify important considerations

The second step to building a decision matrix is to identify the important considerations that factor into your decision. This set of criteria helps you identify the best decision and avoid subjectivity.

Continuing our example, your team has decided that the important criteria to factor in when selecting a design agency are: cost, experience, communication, and past customer reviews.

3. Create your decision matrix

A decision matrix is a grid where you can compare important considerations between the various options. 

Naturally, we build our decision matrices in Asana. Asana is a work management tool that can help you organize and execute work across your organization and provide the clarity teams need to hit their goals faster. 

For example, here’s what your decision matrix skeleton looks like in Asana if you’re deciding between three agencies and factoring in cost, experience, communication, and customer reviews:

[Inline illustration] Empty decision matrix to decide between three design agencies (example)

4. Fill in your decision matrix

Now, rate each consideration on a predetermined scale. If there isn’t a large variation between the options, use a scale of 1-3, where three is the best. For more options, use a scale of 1-5, where five is the best. 

This is where the advantages of a decision matrix really start to shine. For example, let’s say you’re deciding between three agencies and you have four important criteria, but you don’t make a decision matrix. Here’s how each agency stacks up: 

Agency 1 is really cost effective but they don’t have a ton of experience. Their communication and customer reviews seem average. 

Agency 2 isn’t very cost effective, but they aren’t the most expensive agency. They have a good amount of experience, and they have great customer reviews, but their communication so far has been a bit lacking.

Agency 3 is the most expensive, but they also have the most experience. Their communication so far has been average and their customer reviews are pretty good. 

These three descriptions are all relatively similar—it’s hard to decide which is better based on a short paragraph, especially because each agency has its own pros and cons. Alternatively, here’s what the three agencies and their four considerations look like on a decision matrix when ranked from 1-5, with five being the best:

[Inline illustration] Decision matrix to decide between three design agencies with initial scores input (example)

5. Add weight

Sometimes, there are certain considerations that are more important than others. In such a case, use a weighted decision matrix to identify the best option for you. 

To continue our example, imagine you absolutely can’t go over your budget, so cost is a critical factor in your decision-making process. Customer reviews are also important, since they give you a baseline sense of how effective each agency has been in the past. 

To add weight to a decision matrix, assign a number (between 1-3 or 1-5, depending on how many options you have) to each consideration. Later in the decision-making process, you’ll multiply the weighting factor by each consideration.

Here’s what that looks like in our example: 

[Inline illustration] Decision matrix to decide between three design agencies with weight (example)

6. Multiply the weighted score

Once you’ve applied your rating scale and assigned a weight to each consideration, multiply the weight by each consideration. This ensures that the more important considerations are being given more weight, which will ultimately help you select the best agency.

To continue our example, here’s what it looks like when you apply the weighted scores to each consideration for each agency:

[Inline illustration] Decision matrix to decide between three design agencies with weight multiplied by each number (example)

7. Calculate the total score

Now that you’ve multiplied the weighted score, add up all of the considerations for each agency. At this point, you should have a clear, numbers-based answer to which decision is the best one.

For example, this is what the finished decision matrix looks like: 

[Inline illustration] Finished decision matrix to decide between three design agencies (example)

As you can see, Agency 2 has the highest score, so that is the agency you should go with. Even though Agency 1 was cheaper, the average cost of Agency 2, combined with their years of experience and stellar customer reviews make them the best option for your team. All that’s left is to contact the agency and move forward with the brand campaign. 

Decision matrix example

You can use decision matrices for a variety of business decisions, as long as you’re weighing the best option between different choices. These decisions don’t always have to be business-critical, either. You can use this model to quickly make a simple decision as well. 

For example, create a decision matrix to decide which chair you’re going to buy for your work from home setup. You like four different chairs, and your important considerations are comfort, cost, and reviews. 

[Inline illustration] Finished decision matrix to decide between office chairs (example)

Decision-making alternatives

If the decision matrix method isn’t quite right for your choices, try: 

Eisenhower matrix

An Eisenhower matrix is a 2x2 grid to help you prioritize tasks by urgency and importance. This matrix is helpful if you are juggling a variety of non-similar tasks and need to decide which tasks or initiatives to work on first. 

In the upper left-hand corner, list urgent and important work: These tasks are a top priority. Do them now, or as soon as possible.

In the upper right-hand corner, list less urgent but important work: To ensure you get to these tasks, schedule them into your calendar, or capture the due date in a project management tool .

In the lower left-hand corner, list urgent and not important work: These tasks need to get done, but there is probably a better person for the job. Delegate this work if possible.

In the lower right-hand corner, list less urgent and not important work: Defer these tasks, or don’t do them. Clarifying your priorities and letting team members know that you can’t work on something right now is one way to reduce burnout .

Stakeholder analysis map and RACI chart

One of the most important decisions you have to make during the project planning process is to decide which stakeholders should be included, consulted, or informed. For this decision, create a stakeholder analysis map . This map helps you categorize stakeholders based on their relative influence and interest. 

There are four categories in a stakeholder analysis map:

High influence and high interest: Involve these stakeholders in the project planning and decision-making process. 

High influence and low interest: Let these stakeholders know about the project and monitor their interest in case they want to become more involved.

Low influence and high interest: Keep these stakeholders informed about the project. Add them to your project status updates so they can stay in the loop.

Low influence and low interest: Touch base with these stakeholders at regular checkpoints, but don’t worry too much about keeping them informed.

Once you’ve figured out your key stakeholders, you can also create a RACI chart . RACI is an acronym that stands for Responsible, Accountable, Consulted, and Informed. RACI charts can help you decide who the main decision-maker is for each task or initiative. 

Team brainstorming session

Sometimes the best way to make a decision is to host a good old fashioned team brainstorm. Hold a whiteboard brainstorming session or share ideas in a project management tool. 

At Asana, we like to use Kanban boards for dynamic brainstorming sessions. To start, the brainstorm facilitator creates a Board where team members can add ideas, thoughts, or feedback. Then, once everyone has added their ideas, each team member goes through and “likes” individual suggestions. Then, the team discusses the tasks with the most likes as a group to decide what to move forward on.

Say goodbye to coin flips for decision making

Making quick decisions is an important part of good project planning and project management . Whether you use a decision matrix to make a complex decision or a simple one, these tools can help you consider different factors and make the best decision for your team. 

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Project portfolio management 101

What Is Comparative Analysis and How to Conduct It? (+ Examples)

Appinio Research · 30.10.2023 · 34min read

What Is Comparative Analysis and How to Conduct It Examples

Have you ever faced a complex decision, wondering how to make the best choice among multiple options? In a world filled with data and possibilities, the art of comparative analysis holds the key to unlocking clarity amidst the chaos.

In this guide, we'll demystify the power of comparative analysis, revealing its practical applications, methodologies, and best practices. Whether you're a business leader, researcher, or simply someone seeking to make more informed decisions, join us as we explore the intricacies of comparative analysis and equip you with the tools to chart your course with confidence.

What is Comparative Analysis?

Comparative analysis is a systematic approach used to evaluate and compare two or more entities, variables, or options to identify similarities, differences, and patterns. It involves assessing the strengths, weaknesses, opportunities, and threats associated with each entity or option to make informed decisions.

The primary purpose of comparative analysis is to provide a structured framework for decision-making by:

  • Facilitating Informed Choices: Comparative analysis equips decision-makers with data-driven insights, enabling them to make well-informed choices among multiple options.
  • Identifying Trends and Patterns: It helps identify recurring trends, patterns, and relationships among entities or variables, shedding light on underlying factors influencing outcomes.
  • Supporting Problem Solving: Comparative analysis aids in solving complex problems by systematically breaking them down into manageable components and evaluating potential solutions.
  • Enhancing Transparency: By comparing multiple options, comparative analysis promotes transparency in decision-making processes, allowing stakeholders to understand the rationale behind choices.
  • Mitigating Risks : It helps assess the risks associated with each option, allowing organizations to develop risk mitigation strategies and make risk-aware decisions.
  • Optimizing Resource Allocation: Comparative analysis assists in allocating resources efficiently by identifying areas where resources can be optimized for maximum impact.
  • Driving Continuous Improvement: By comparing current performance with historical data or benchmarks, organizations can identify improvement areas and implement growth strategies.

Importance of Comparative Analysis in Decision-Making

  • Data-Driven Decision-Making: Comparative analysis relies on empirical data and objective evaluation, reducing the influence of biases and subjective judgments in decision-making. It ensures decisions are based on facts and evidence.
  • Objective Assessment: It provides an objective and structured framework for evaluating options, allowing decision-makers to focus on key criteria and avoid making decisions solely based on intuition or preferences.
  • Risk Assessment: Comparative analysis helps assess and quantify risks associated with different options. This risk awareness enables organizations to make proactive risk management decisions.
  • Prioritization: By ranking options based on predefined criteria, comparative analysis enables decision-makers to prioritize actions or investments, directing resources to areas with the most significant impact.
  • Strategic Planning: It is integral to strategic planning, helping organizations align their decisions with overarching goals and objectives. Comparative analysis ensures decisions are consistent with long-term strategies.
  • Resource Allocation: Organizations often have limited resources. Comparative analysis assists in allocating these resources effectively, ensuring they are directed toward initiatives with the highest potential returns.
  • Continuous Improvement: Comparative analysis supports a culture of continuous improvement by identifying areas for enhancement and guiding iterative decision-making processes.
  • Stakeholder Communication: It enhances transparency in decision-making, making it easier to communicate decisions to stakeholders. Stakeholders can better understand the rationale behind choices when supported by comparative analysis.
  • Competitive Advantage: In business and competitive environments , comparative analysis can provide a competitive edge by identifying opportunities to outperform competitors or address weaknesses.
  • Informed Innovation: When evaluating new products , technologies, or strategies, comparative analysis guides the selection of the most promising options, reducing the risk of investing in unsuccessful ventures.

In summary, comparative analysis is a valuable tool that empowers decision-makers across various domains to make informed, data-driven choices, manage risks, allocate resources effectively, and drive continuous improvement. Its structured approach enhances decision quality and transparency, contributing to the success and competitiveness of organizations and research endeavors.

How to Prepare for Comparative Analysis?

1. define objectives and scope.

Before you begin your comparative analysis, clearly defining your objectives and the scope of your analysis is essential. This step lays the foundation for the entire process. Here's how to approach it:

  • Identify Your Goals: Start by asking yourself what you aim to achieve with your comparative analysis. Are you trying to choose between two products for your business? Are you evaluating potential investment opportunities? Knowing your objectives will help you stay focused throughout the analysis.
  • Define Scope: Determine the boundaries of your comparison. What will you include, and what will you exclude? For example, if you're analyzing market entry strategies for a new product, specify whether you're looking at a specific geographic region or a particular target audience.
  • Stakeholder Alignment: Ensure that all stakeholders involved in the analysis understand and agree on the objectives and scope. This alignment will prevent misunderstandings and ensure the analysis meets everyone's expectations.

2. Gather Relevant Data and Information

The quality of your comparative analysis heavily depends on the data and information you gather. Here's how to approach this crucial step:

  • Data Sources: Identify where you'll obtain the necessary data. Will you rely on primary sources , such as surveys and interviews, to collect original data? Or will you use secondary sources, like published research and industry reports, to access existing data? Consider the advantages and disadvantages of each source.
  • Data Collection Plan: Develop a plan for collecting data. This should include details about the methods you'll use, the timeline for data collection, and who will be responsible for gathering the data.
  • Data Relevance: Ensure that the data you collect is directly relevant to your objectives. Irrelevant or extraneous data can lead to confusion and distract from the core analysis.

3. Select Appropriate Criteria for Comparison

Choosing the right criteria for comparison is critical to a successful comparative analysis. Here's how to go about it:

  • Relevance to Objectives: Your chosen criteria should align closely with your analysis objectives. For example, if you're comparing job candidates, your criteria might include skills, experience, and cultural fit.
  • Measurability: Consider whether you can quantify the criteria. Measurable criteria are easier to analyze. If you're comparing marketing campaigns, you might measure criteria like click-through rates, conversion rates, and return on investment.
  • Weighting Criteria: Not all criteria are equally important. You'll need to assign weights to each criterion based on its relative importance. Weighting helps ensure that the most critical factors have a more significant impact on the final decision.

4. Establish a Clear Framework

Once you have your objectives, data, and criteria in place, it's time to establish a clear framework for your comparative analysis. This framework will guide your process and ensure consistency. Here's how to do it:

  • Comparative Matrix: Consider using a comparative matrix or spreadsheet to organize your data. Each row in the matrix represents an option or entity you're comparing, and each column corresponds to a criterion. This visual representation makes it easy to compare and contrast data.
  • Timeline: Determine the time frame for your analysis. Is it a one-time comparison, or will you conduct ongoing analyses? Having a defined timeline helps you manage the analysis process efficiently.
  • Define Metrics: Specify the metrics or scoring system you'll use to evaluate each criterion. For example, if you're comparing potential office locations, you might use a scoring system from 1 to 5 for factors like cost, accessibility, and amenities.

With your objectives, data, criteria, and framework established, you're ready to move on to the next phase of comparative analysis: data collection and organization.

Comparative Analysis Data Collection

Data collection and organization are critical steps in the comparative analysis process. We'll explore how to gather and structure the data you need for a successful analysis.

1. Utilize Primary Data Sources

Primary data sources involve gathering original data directly from the source. This approach offers unique advantages, allowing you to tailor your data collection to your specific research needs.

Some popular primary data sources include:

  • Surveys and Questionnaires: Design surveys or questionnaires and distribute them to collect specific information from individuals or groups. This method is ideal for obtaining firsthand insights, such as customer preferences or employee feedback.
  • Interviews: Conduct structured interviews with relevant stakeholders or experts. Interviews provide an opportunity to delve deeper into subjects and gather qualitative data, making them valuable for in-depth analysis.
  • Observations: Directly observe and record data from real-world events or settings. Observational data can be instrumental in fields like anthropology, ethnography, and environmental studies.
  • Experiments: In controlled environments, experiments allow you to manipulate variables and measure their effects. This method is common in scientific research and product testing.

When using primary data sources, consider factors like sample size, survey design, and data collection methods to ensure the reliability and validity of your data.

2. Harness Secondary Data Sources

Secondary data sources involve using existing data collected by others. These sources can provide a wealth of information and save time and resources compared to primary data collection.

Here are common types of secondary data sources:

  • Public Records: Government publications, census data, and official reports offer valuable information on demographics, economic trends, and public policies. They are often free and readily accessible.
  • Academic Journals: Scholarly articles provide in-depth research findings across various disciplines. They are helpful for accessing peer-reviewed studies and staying current with academic discourse.
  • Industry Reports: Industry-specific reports and market research publications offer insights into market trends, consumer behavior, and competitive landscapes. They are essential for businesses making strategic decisions.
  • Online Databases: Online platforms like Statista , PubMed , and Google Scholar provide a vast repository of data and research articles. They offer search capabilities and access to a wide range of data sets.

When using secondary data sources, critically assess the credibility, relevance, and timeliness of the data. Ensure that it aligns with your research objectives.

3. Ensure and Validate Data Quality

Data quality is paramount in comparative analysis. Poor-quality data can lead to inaccurate conclusions and flawed decision-making. Here's how to ensure data validation and reliability:

  • Cross-Verification: Whenever possible, cross-verify data from multiple sources. Consistency among different sources enhances the reliability of the data.
  • Sample Size: Ensure that your data sample size is statistically significant for meaningful analysis. A small sample may not accurately represent the population.
  • Data Integrity: Check for data integrity issues, such as missing values, outliers, or duplicate entries. Address these issues before analysis to maintain data quality.
  • Data Source Reliability: Assess the reliability and credibility of the data sources themselves. Consider factors like the reputation of the institution or organization providing the data.

4. Organize Data Effectively

Structuring your data for comparison is a critical step in the analysis process. Organized data makes it easier to draw insights and make informed decisions. Here's how to structure data effectively:

  • Data Cleaning: Before analysis, clean your data to remove inconsistencies, errors, and irrelevant information. Data cleaning may involve data transformation, imputation of missing values, and removing outliers.
  • Normalization: Standardize data to ensure fair comparisons. Normalization adjusts data to a standard scale, making comparing variables with different units or ranges possible.
  • Variable Labeling: Clearly label variables and data points for easy identification. Proper labeling enhances the transparency and understandability of your analysis.
  • Data Organization: Organize data into a format that suits your analysis methods. For quantitative analysis, this might mean creating a matrix, while qualitative analysis may involve categorizing data into themes.

By paying careful attention to data collection, validation, and organization, you'll set the stage for a robust and insightful comparative analysis. Next, we'll explore various methodologies you can employ in your analysis, ranging from qualitative approaches to quantitative methods and examples.

Comparative Analysis Methods

When it comes to comparative analysis, various methodologies are available, each suited to different research goals and data types. In this section, we'll explore five prominent methodologies in detail.

Qualitative Comparative Analysis (QCA)

Qualitative Comparative Analysis (QCA) is a methodology often used when dealing with complex, non-linear relationships among variables. It seeks to identify patterns and configurations among factors that lead to specific outcomes.

  • Case-by-Case Analysis: QCA involves evaluating individual cases (e.g., organizations, regions, or events) rather than analyzing aggregate data. Each case's unique characteristics are considered.
  • Boolean Logic: QCA employs Boolean algebra to analyze data. Variables are categorized as either present or absent, allowing for the examination of different combinations and logical relationships.
  • Necessary and Sufficient Conditions: QCA aims to identify necessary and sufficient conditions for a specific outcome to occur. It helps answer questions like, "What conditions are necessary for a successful product launch?"
  • Fuzzy Set Theory: In some cases, QCA may use fuzzy set theory to account for degrees of membership in a category, allowing for more nuanced analysis.

QCA is particularly useful in fields such as sociology, political science, and organizational studies, where understanding complex interactions is essential.

Quantitative Comparative Analysis

Quantitative Comparative Analysis involves the use of numerical data and statistical techniques to compare and analyze variables. It's suitable for situations where data is quantitative, and relationships can be expressed numerically.

  • Statistical Tools: Quantitative comparative analysis relies on statistical methods like regression analysis, correlation, and hypothesis testing. These tools help identify relationships, dependencies, and trends within datasets.
  • Data Measurement: Ensure that variables are measured consistently using appropriate scales (e.g., ordinal, interval, ratio) for meaningful analysis. Variables may include numerical values like revenue, customer satisfaction scores, or product performance metrics.
  • Data Visualization: Create visual representations of data using charts, graphs, and plots. Visualization aids in understanding complex relationships and presenting findings effectively.
  • Statistical Significance: Assess the statistical significance of relationships. Statistical significance indicates whether observed differences or relationships are likely to be real rather than due to chance.

Quantitative comparative analysis is commonly applied in economics, social sciences, and market research to draw empirical conclusions from numerical data.

Case Studies

Case studies involve in-depth examinations of specific instances or cases to gain insights into real-world scenarios. Comparative case studies allow researchers to compare and contrast multiple cases to identify patterns, differences, and lessons.

  • Narrative Analysis: Case studies often involve narrative analysis, where researchers construct detailed narratives of each case, including context, events, and outcomes.
  • Contextual Understanding: In comparative case studies, it's crucial to consider the context within which each case operates. Understanding the context helps interpret findings accurately.
  • Cross-Case Analysis: Researchers conduct cross-case analysis to identify commonalities and differences across cases. This process can lead to the discovery of factors that influence outcomes.
  • Triangulation: To enhance the validity of findings, researchers may use multiple data sources and methods to triangulate information and ensure reliability.

Case studies are prevalent in fields like psychology, business, and sociology, where deep insights into specific situations are valuable.

SWOT Analysis

SWOT Analysis is a strategic tool used to assess the Strengths, Weaknesses, Opportunities, and Threats associated with a particular entity or situation. While it's commonly used in business, it can be adapted for various comparative analyses.

  • Internal and External Factors: SWOT Analysis examines both internal factors (Strengths and Weaknesses), such as organizational capabilities, and external factors (Opportunities and Threats), such as market conditions and competition.
  • Strategic Planning: The insights from SWOT Analysis inform strategic decision-making. By identifying strengths and opportunities, organizations can leverage their advantages. Likewise, addressing weaknesses and threats helps mitigate risks.
  • Visual Representation: SWOT Analysis is often presented as a matrix or a 2x2 grid, making it visually accessible and easy to communicate to stakeholders.
  • Continuous Monitoring: SWOT Analysis is not a one-time exercise. Organizations use it periodically to adapt to changing circumstances and make informed decisions.

SWOT Analysis is versatile and can be applied in business, healthcare, education, and any context where a structured assessment of factors is needed.

Benchmarking

Benchmarking involves comparing an entity's performance, processes, or practices to those of industry leaders or best-in-class organizations. It's a powerful tool for continuous improvement and competitive analysis.

  • Identify Performance Gaps: Benchmarking helps identify areas where an entity lags behind its peers or industry standards. These performance gaps highlight opportunities for improvement.
  • Data Collection: Gather data on key performance metrics from both internal and external sources. This data collection phase is crucial for meaningful comparisons.
  • Comparative Analysis: Compare your organization's performance data with that of benchmark organizations. This analysis can reveal where you excel and where adjustments are needed.
  • Continuous Improvement: Benchmarking is a dynamic process that encourages continuous improvement. Organizations use benchmarking findings to set performance goals and refine their strategies.

Benchmarking is widely used in business, manufacturing, healthcare, and customer service to drive excellence and competitiveness.

Each of these methodologies brings a unique perspective to comparative analysis, allowing you to choose the one that best aligns with your research objectives and the nature of your data. The choice between qualitative and quantitative methods, or a combination of both, depends on the complexity of the analysis and the questions you seek to answer.

How to Conduct Comparative Analysis?

Once you've prepared your data and chosen an appropriate methodology, it's time to dive into the process of conducting a comparative analysis. We will guide you through the essential steps to extract meaningful insights from your data.

What Is Comparative Analysis and How to Conduct It Examples

1. Identify Key Variables and Metrics

Identifying key variables and metrics is the first crucial step in conducting a comparative analysis. These are the factors or indicators you'll use to assess and compare your options.

  • Relevance to Objectives: Ensure the chosen variables and metrics align closely with your analysis objectives. When comparing marketing strategies, relevant metrics might include customer acquisition cost, conversion rate, and retention.
  • Quantitative vs. Qualitative : Decide whether your analysis will focus on quantitative data (numbers) or qualitative data (descriptive information). In some cases, a combination of both may be appropriate.
  • Data Availability: Consider the availability of data. Ensure you can access reliable and up-to-date data for all selected variables and metrics.
  • KPIs: Key Performance Indicators (KPIs) are often used as the primary metrics in comparative analysis. These are metrics that directly relate to your goals and objectives.

2. Visualize Data for Clarity

Data visualization techniques play a vital role in making complex information more accessible and understandable. Effective data visualization allows you to convey insights and patterns to stakeholders. Consider the following approaches:

  • Charts and Graphs: Use various types of charts, such as bar charts, line graphs, and pie charts, to represent data. For example, a line graph can illustrate trends over time, while a bar chart can compare values across categories.
  • Heatmaps: Heatmaps are particularly useful for visualizing large datasets and identifying patterns through color-coding. They can reveal correlations, concentrations, and outliers.
  • Scatter Plots: Scatter plots help visualize relationships between two variables. They are especially useful for identifying trends, clusters, or outliers.
  • Dashboards: Create interactive dashboards that allow users to explore data and customize views. Dashboards are valuable for ongoing analysis and reporting.
  • Infographics: For presentations and reports, consider using infographics to summarize key findings in a visually engaging format.

Effective data visualization not only enhances understanding but also aids in decision-making by providing clear insights at a glance.

3. Establish Clear Comparative Frameworks

A well-structured comparative framework provides a systematic approach to your analysis. It ensures consistency and enables you to make meaningful comparisons. Here's how to create one:

  • Comparison Matrices: Consider using matrices or spreadsheets to organize your data. Each row represents an option or entity, and each column corresponds to a variable or metric. This matrix format allows for side-by-side comparisons.
  • Decision Trees: In complex decision-making scenarios, decision trees help map out possible outcomes based on different criteria and variables. They visualize the decision-making process.
  • Scenario Analysis: Explore different scenarios by altering variables or criteria to understand how changes impact outcomes. Scenario analysis is valuable for risk assessment and planning.
  • Checklists: Develop checklists or scoring sheets to systematically evaluate each option against predefined criteria. Checklists ensure that no essential factors are overlooked.

A well-structured comparative framework simplifies the analysis process, making it easier to draw meaningful conclusions and make informed decisions.

4. Evaluate and Score Criteria

Evaluating and scoring criteria is a critical step in comparative analysis, as it quantifies the performance of each option against the chosen criteria.

  • Scoring System: Define a scoring system that assigns values to each criterion for every option. Common scoring systems include numerical scales, percentage scores, or qualitative ratings (e.g., high, medium, low).
  • Consistency: Ensure consistency in scoring by defining clear guidelines for each score. Provide examples or descriptions to help evaluators understand what each score represents.
  • Data Collection: Collect data or information relevant to each criterion for all options. This may involve quantitative data (e.g., sales figures) or qualitative data (e.g., customer feedback).
  • Aggregation: Aggregate the scores for each option to obtain an overall evaluation. This can be done by summing the individual criterion scores or applying weighted averages.
  • Normalization: If your criteria have different measurement scales or units, consider normalizing the scores to create a level playing field for comparison.

5. Assign Importance to Criteria

Not all criteria are equally important in a comparative analysis. Weighting criteria allows you to reflect their relative significance in the final decision-making process.

  • Relative Importance: Assess the importance of each criterion in achieving your objectives. Criteria directly aligned with your goals may receive higher weights.
  • Weighting Methods: Choose a weighting method that suits your analysis. Common methods include expert judgment, analytic hierarchy process (AHP), or data-driven approaches based on historical performance.
  • Impact Analysis: Consider how changes in the weights assigned to criteria would affect the final outcome. This sensitivity analysis helps you understand the robustness of your decisions.
  • Stakeholder Input: Involve relevant stakeholders or decision-makers in the weighting process. Their input can provide valuable insights and ensure alignment with organizational goals.
  • Transparency: Clearly document the rationale behind the assigned weights to maintain transparency in your analysis.

By weighting criteria, you ensure that the most critical factors have a more significant influence on the final evaluation, aligning the analysis more closely with your objectives and priorities.

With these steps in place, you're well-prepared to conduct a comprehensive comparative analysis. The next phase involves interpreting your findings, drawing conclusions, and making informed decisions based on the insights you've gained.

Comparative Analysis Interpretation

Interpreting the results of your comparative analysis is a crucial phase that transforms data into actionable insights. We'll delve into various aspects of interpretation and how to make sense of your findings.

  • Contextual Understanding: Before diving into the data, consider the broader context of your analysis. Understand the industry trends, market conditions, and any external factors that may have influenced your results.
  • Drawing Conclusions: Summarize your findings clearly and concisely. Identify trends, patterns, and significant differences among the options or variables you've compared.
  • Quantitative vs. Qualitative Analysis: Depending on the nature of your data and analysis, you may need to balance both quantitative and qualitative interpretations. Qualitative insights can provide context and nuance to quantitative findings.
  • Comparative Visualization: Visual aids such as charts, graphs, and tables can help convey your conclusions effectively. Choose visual representations that align with the nature of your data and the key points you want to emphasize.
  • Outliers and Anomalies: Identify and explain any outliers or anomalies in your data. Understanding these exceptions can provide valuable insights into unusual cases or factors affecting your analysis.
  • Cross-Validation: Validate your conclusions by comparing them with external benchmarks, industry standards, or expert opinions. Cross-validation helps ensure the reliability of your findings.
  • Implications for Decision-Making: Discuss how your analysis informs decision-making. Clearly articulate the practical implications of your findings and their relevance to your initial objectives.
  • Actionable Insights: Emphasize actionable insights that can guide future strategies, policies, or actions. Make recommendations based on your analysis, highlighting the steps needed to capitalize on strengths or address weaknesses.
  • Continuous Improvement: Encourage a culture of continuous improvement by using your analysis as a feedback mechanism. Suggest ways to monitor and adapt strategies over time based on evolving circumstances.

Comparative Analysis Applications

Comparative analysis is a versatile methodology that finds application in various fields and scenarios. Let's explore some of the most common and impactful applications.

Business Decision-Making

Comparative analysis is widely employed in business to inform strategic decisions and drive success. Key applications include:

Market Research and Competitive Analysis

  • Objective: To assess market opportunities and evaluate competitors.
  • Methods: Analyzing market trends, customer preferences, competitor strengths and weaknesses, and market share.
  • Outcome: Informed product development, pricing strategies, and market entry decisions.

Product Comparison and Benchmarking

  • Objective: To compare the performance and features of products or services.
  • Methods: Evaluating product specifications, customer reviews, and pricing.
  • Outcome: Identifying strengths and weaknesses, improving product quality, and setting competitive pricing.

Financial Analysis

  • Objective: To evaluate financial performance and make investment decisions.
  • Methods: Comparing financial statements, ratios, and performance indicators of companies.
  • Outcome: Informed investment choices, risk assessment, and portfolio management.

Healthcare and Medical Research

In the healthcare and medical research fields, comparative analysis is instrumental in understanding diseases, treatment options, and healthcare systems.

Clinical Trials and Drug Development opment

  • Objective: To compare the effectiveness of different treatments or drugs.
  • Methods: Analyzing clinical trial data, patient outcomes, and side effects.
  • Outcome: Informed decisions about drug approvals, treatment protocols, and patient care.

Health Outcomes Research

  • Objective: To assess the impact of healthcare interventions.
  • Methods: Comparing patient health outcomes before and after treatment or between different treatment approaches.
  • Outcome: Improved healthcare guidelines, cost-effectiveness analysis, and patient care plans.

Healthcare Systems Evaluation

  • Objective: To assess the performance of healthcare systems.
  • Methods: Comparing healthcare delivery models, patient satisfaction, and healthcare costs.
  • Outcome: Informed healthcare policy decisions, resource allocation, and system improvements.

Social Sciences and Policy Analysis

Comparative analysis is a fundamental tool in social sciences and policy analysis, aiding in understanding complex societal issues.

Educational Research

  • Objective: To compare educational systems and practices.
  • Methods: Analyzing student performance, curriculum effectiveness, and teaching methods.
  • Outcome: Informed educational policies, curriculum development, and school improvement strategies.

Political Science

  • Objective: To study political systems, elections, and governance.
  • Methods: Comparing election outcomes, policy impacts, and government structures.
  • Outcome: Insights into political behavior, policy effectiveness, and governance reforms.

Social Welfare and Poverty Analysis

  • Objective: To evaluate the impact of social programs and policies.
  • Methods: Comparing the well-being of individuals or communities with and without access to social assistance.
  • Outcome: Informed policymaking, poverty reduction strategies, and social program improvements.

Environmental Science and Sustainability

Comparative analysis plays a pivotal role in understanding environmental issues and promoting sustainability.

Environmental Impact Assessment

  • Objective: To assess the environmental consequences of projects or policies.
  • Methods: Comparing ecological data, resource use, and pollution levels.
  • Outcome: Informed environmental mitigation strategies, sustainable development plans, and regulatory decisions.

Climate Change Analysis

  • Objective: To study climate patterns and their impacts.
  • Methods: Comparing historical climate data, temperature trends, and greenhouse gas emissions.
  • Outcome: Insights into climate change causes, adaptation strategies, and policy recommendations.

Ecosystem Health Assessment

  • Objective: To evaluate the health and resilience of ecosystems.
  • Methods: Comparing biodiversity, habitat conditions, and ecosystem services.
  • Outcome: Conservation efforts, restoration plans, and ecological sustainability measures.

Technology and Innovation

Comparative analysis is crucial in the fast-paced world of technology and innovation.

Product Development and Innovation

  • Objective: To assess the competitiveness and innovation potential of products or technologies.
  • Methods: Comparing research and development investments, technology features, and market demand.
  • Outcome: Informed innovation strategies, product roadmaps, and patent decisions.

User Experience and Usability Testing

  • Objective: To evaluate the user-friendliness of software applications or digital products.
  • Methods: Comparing user feedback, usability metrics, and user interface designs.
  • Outcome: Improved user experiences, interface redesigns, and product enhancements.

Technology Adoption and Market Entry

  • Objective: To analyze market readiness and risks for new technologies.
  • Methods: Comparing market conditions, regulatory landscapes, and potential barriers.
  • Outcome: Informed market entry strategies, risk assessments, and investment decisions.

These diverse applications of comparative analysis highlight its flexibility and importance in decision-making across various domains. Whether in business, healthcare, social sciences, environmental studies, or technology, comparative analysis empowers researchers and decision-makers to make informed choices and drive positive outcomes.

Comparative Analysis Best Practices

Successful comparative analysis relies on following best practices and avoiding common pitfalls. Implementing these practices enhances the effectiveness and reliability of your analysis.

  • Clearly Defined Objectives: Start with well-defined objectives that outline what you aim to achieve through the analysis. Clear objectives provide focus and direction.
  • Data Quality Assurance: Ensure data quality by validating, cleaning, and normalizing your data. Poor-quality data can lead to inaccurate conclusions.
  • Transparent Methodologies: Clearly explain the methodologies and techniques you've used for analysis. Transparency builds trust and allows others to assess the validity of your approach.
  • Consistent Criteria: Maintain consistency in your criteria and metrics across all options or variables. Inconsistent criteria can lead to biased results.
  • Sensitivity Analysis: Conduct sensitivity analysis by varying key parameters, such as weights or assumptions, to assess the robustness of your conclusions.
  • Stakeholder Involvement: Involve relevant stakeholders throughout the analysis process. Their input can provide valuable perspectives and ensure alignment with organizational goals.
  • Critical Evaluation of Assumptions: Identify and critically evaluate any assumptions made during the analysis. Assumptions should be explicit and justifiable.
  • Holistic View: Take a holistic view of the analysis by considering both short-term and long-term implications. Avoid focusing solely on immediate outcomes.
  • Documentation: Maintain thorough documentation of your analysis, including data sources, calculations, and decision criteria. Documentation supports transparency and facilitates reproducibility.
  • Continuous Learning: Stay updated with the latest analytical techniques, tools, and industry trends. Continuous learning helps you adapt your analysis to changing circumstances.
  • Peer Review: Seek peer review or expert feedback on your analysis. External perspectives can identify blind spots and enhance the quality of your work.
  • Ethical Considerations: Address ethical considerations, such as privacy and data protection, especially when dealing with sensitive or personal data.

By adhering to these best practices, you'll not only improve the rigor of your comparative analysis but also ensure that your findings are reliable, actionable, and aligned with your objectives.

Comparative Analysis Examples

To illustrate the practical application and benefits of comparative analysis, let's explore several real-world examples across different domains. These examples showcase how organizations and researchers leverage comparative analysis to make informed decisions, solve complex problems, and drive improvements:

Retail Industry - Price Competitiveness Analysis

Objective: A retail chain aims to assess its price competitiveness against competitors in the same market.

Methodology:

  • Collect pricing data for a range of products offered by the retail chain and its competitors.
  • Organize the data into a comparative framework, categorizing products by type and price range.
  • Calculate price differentials, averages, and percentiles for each product category.
  • Analyze the findings to identify areas where the retail chain's prices are higher or lower than competitors.

Outcome: The analysis reveals that the retail chain's prices are consistently lower in certain product categories but higher in others. This insight informs pricing strategies, allowing the retailer to adjust prices to remain competitive in the market.

Healthcare - Comparative Effectiveness Research

Objective: Researchers aim to compare the effectiveness of two different treatment methods for a specific medical condition.

  • Recruit patients with the medical condition and randomly assign them to two treatment groups.
  • Collect data on treatment outcomes, including symptom relief, side effects, and recovery times.
  • Analyze the data using statistical methods to compare the treatment groups.
  • Consider factors like patient demographics and baseline health status as potential confounding variables.

Outcome: The comparative analysis reveals that one treatment method is statistically more effective than the other in relieving symptoms and has fewer side effects. This information guides medical professionals in recommending the more effective treatment to patients.

Environmental Science - Carbon Emission Analysis

Objective: An environmental organization seeks to compare carbon emissions from various transportation modes in a metropolitan area.

  • Collect data on the number of vehicles, their types (e.g., cars, buses, bicycles), and fuel consumption for each mode of transportation.
  • Calculate the total carbon emissions for each mode based on fuel consumption and emission factors.
  • Create visualizations such as bar charts and pie charts to represent the emissions from each transportation mode.
  • Consider factors like travel distance, occupancy rates, and the availability of alternative fuels.

Outcome: The comparative analysis reveals that public transportation generates significantly lower carbon emissions per passenger mile compared to individual car travel. This information supports advocacy for increased public transit usage to reduce carbon footprint.

Technology Industry - Feature Comparison for Software Development Tools

Objective: A software development team needs to choose the most suitable development tool for an upcoming project.

  • Create a list of essential features and capabilities required for the project.
  • Research and compile information on available development tools in the market.
  • Develop a comparative matrix or scoring system to evaluate each tool's features against the project requirements.
  • Assign weights to features based on their importance to the project.

Outcome: The comparative analysis highlights that Tool A excels in essential features critical to the project, such as version control integration and debugging capabilities. The development team selects Tool A as the preferred choice for the project.

Educational Research - Comparative Study of Teaching Methods

Objective: A school district aims to improve student performance by comparing the effectiveness of traditional classroom teaching with online learning.

  • Randomly assign students to two groups: one taught using traditional methods and the other through online courses.
  • Administer pre- and post-course assessments to measure knowledge gain.
  • Collect feedback from students and teachers on the learning experiences.
  • Analyze assessment scores and feedback to compare the effectiveness and satisfaction levels of both teaching methods.

Outcome: The comparative analysis reveals that online learning leads to similar knowledge gains as traditional classroom teaching. However, students report higher satisfaction and flexibility with the online approach. The school district considers incorporating online elements into its curriculum.

These examples illustrate the diverse applications of comparative analysis across industries and research domains. Whether optimizing pricing strategies in retail, evaluating treatment effectiveness in healthcare, assessing environmental impacts, choosing the right software tool, or improving educational methods, comparative analysis empowers decision-makers with valuable insights for informed choices and positive outcomes.

Comparative analysis is your compass in the world of decision-making. It helps you see the bigger picture, spot opportunities, and navigate challenges. By defining your objectives, gathering data, applying methodologies, and following best practices, you can harness the power of Comparative Analysis to make informed choices and drive positive outcomes.

Remember, Comparative analysis is not just a tool; it's a mindset that empowers you to transform data into insights and uncertainty into clarity. So, whether you're steering a business, conducting research, or facing life's choices, embrace Comparative Analysis as your trusted guide on the journey to better decisions. With it, you can chart your course, make impactful choices, and set sail toward success.

How to Conduct Comparative Analysis in Minutes?

Are you ready to revolutionize your approach to market research and comparative analysis? Appinio , a real-time market research platform, empowers you to harness the power of real-time consumer insights for swift, data-driven decisions. Here's why you should choose Appinio:

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A Review of Mathematical Multi-Criteria Decision Models with A case study

Profile image of Dr. Uday S Kashid

2019, IJRAR- International Journal of Research and Analytical Reviews, Vol.6, Special Issue, pp.111-124

Multi-Criteria Decision Making/Analysis (MCDM/MCDA) is a Core of Decision Theory, as an important field of Operational Research (OR) in Mathematics. Multi-Criteria Decision model is a technique that permits Decision Makers (DM) to make the best decision in the presence of multiple, potentially conflicting criteria. These MCDM methods have attracted much attention from Decision makers, academics, researchers and practitioners. Multi-Criteria Decision model is used to solve areas problems such as sciences, engineering, technology, economics, military strategies, business, supplier selection, Sports entity and many more. This MCDM is a Method of evaluating conflict real world situations, based on different quantitative, qualitative, criteria under risky, certain, uncertain environments. In this paper we have discussed the some well noted and discussed the results of Multi-Criteria Decision Making (MCDM) techniques with their classifications and characteristics. Moreover, we have compared few MCDM methods with a case study on IPL 2018. The main objective of this paper is multifold: First, to finds the applicability of MCDM methods in different situations by evaluating their relative strengths and weaknesses. Second, comparisons of MCDM methods using a case study. Our study concluded with an observation that the different Multi-Criteria Decision methods present different ranking for the same problem with same multiple attributes and same multiple alternatives although same decision maker. However, this paper does not claim that any method is better than other methods across all possible circumstances, but rather it emphasizes the importance of investigating different Multi-Criteria Decision-Making techniques to rank the decisions of each method and the importance of finding the most appropriate method for ranking the decisions in consideration of the decision-making conditions.

Related Papers

Hashan Hasalanka

 Multi-Criteria Decision Making (MCDM) methods have evolved to accommodate various types of applications. Dozens of methods have been developed, with even small variations to existing methods causing the creation of new branches of research. This paper performs a literature review of common Multi-Criteria Decision Making methods, examines the advantages and disadvantages of the identified methods, and explains how their common applications relate to their relative strengths and weaknesses. The analysis of MCDM methods performed in this paper provides a clear guide for how MCDM methods should be used in particular situations.

decision criteria in case study examples

International Journal for Research in Applied Science and Engineering Technology

girish bhole

Susmita Bandyopadhyay

This paper has proposed a novel Multi-Criteria Decision Analysis (MCDA) technique that considers relationships among the criteria, relationships among the alternatives, relationships among the criteria and the alternatives, the uncertainty or dilemma that the decision makers face in their decision making, the entropy among the criteria. The dilemma of the decision makers has been captured through the use of Hesitant Fuzzy Elements; the information content among the criteria has been captured by applying the concept of entropy through the application of a technique called IDOCRIW. A kind of sensitivity analysis has been performed to verify the effectiveness of the proposed technique. The proposed method has also been compared with four different types of already existing MCDA techniques, AHP, MAUT, MACBETH and MOORA. Both the sensitivity analysis and the comparison with other methods establish the effectiveness of the proposed technique.

ebeydullah hudawerdı

Multi Criteria Decision Making (MCDM) provides strong decision making in domains where selection of best alternative is highly complex. This survey paper reviews the main streams of consideration in multi criteria decision making theory and practice in detail. The main purpose is to identify various applications and the approaches, and to suggest approaches which are most robustly and effectively useable to identify best alternative. This survey work also addresses the problem in fuzzy multi criteria decision making techniques. Multi criteria decision making have been applied in many domains. MCDM method helps to choose the best alternatives where many criteria have come into existence, the best one can be obtained by analyzing the different scope for the criteria, weights for the criteria and the choose the optimum ones using any multi criteria decision making techniques. This survey provides the comprehensive developments of various methods of FMCDM and its applications.

Journal of Air Transport Management

Slavica Dožić

This special issue idea came to life with Prof. Ilker Topcu hosting the 25th International Conference on Multiple Criteria Decision Making in Istanbul from 16 to 21 June 2019 (https://mcdm2019.org/about/). International Society on Multiple Criteria Decision Making (MCDM) brings together academicians, professionals, researchers, students and policymakers at a bi-annual conference since 1975. MCDM 201

İbrahim Yüksek

  • Mathematics

Antonio Jiménez

Over the last few decades, Multi-criteria Decision Analysis (MCDA) techniques have been successfully applied to complex decision-making problems in a wide range of fields, such as economics, finance, logistics, environmental restoration, health or industrial organization, to name but a few, and imprecision and uncertainty have been incorporated into the decision-making process and applied to group decision-making contexts. [...]

Technological and Economic Development of Economy

zenonas turskis

The main research activities in economics during the last five years have significantly increased. The main research fields are operation research and sustainable development. The philosophy of decision making in economics is to assess and select the most preferable solution, implement it and to gain the biggest profit. Preferences are used in a lot of problem situations both in individual and organizational decision making processes. A number of effective decision making methods that support decisions under conditions of multiple criteria have appeared in the last decade. This paper presents a panorama of decision making methods in economics and summarizes the most important results and applications over the last five years. This paper considers decision making in light of the recent developments of multiple criteria decision making methods (because classical methods are overviewed in a lot of earlier publications). Authors of different approaches, pioneering studies and works are ...

Scientia Iranica

Zenonas Turskis

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How Machine Learning Will Transform Supply Chain Management

  • Narendra Agrawal,
  • Morris A. Cohen,
  • Rohan Deshpande,
  • Vinayak Deshpande

decision criteria in case study examples

Businesses need better planning to make their supply chains more agile and resilient. After explaining the shortcomings of traditional planning systems, the authors describe their new approach, optimal machine learning (OML), which has proved effective in a range of industries. A central feature is its decision-support engine that can process a vast amount of historical and current supply-and-demand data, take into account a company’s priorities, and rapidly produce recommendations for ideal production quantities, shipping arrangements, and so on. The authors explain the underpinnings of OML and provide concrete examples of how two large companies implemented it and improved their supply chains’ performance.

It does a better job of using data and forecasts to make decisions.

Idea in Brief

The problem.

Flawed planning methods make it extremely difficult for companies to protect themselves against supply chain disruptions.

A new approach, called optimal machine learning (OML), can enable better decisions, without the mystery surrounding the planning recommendations produced by current machine-learning models.

The Elements

OML relies on a decision-support engine that connects input data directly to supply chain decisions and takes into account a firm’s performance priorities. Other features are a “digital twin” representation of the entire supply chain and a data storage system that integrates information throughout the supply chain and allows for quick data access and updating.

The Covid-19 pandemic, the Russia-Ukraine conflict, trade wars, and other events in recent years have disrupted supply chains and highlighted the critical need for businesses to improve planning in order to be more agile and resilient. Yet companies struggle with this challenge. One major cause is flawed forecasting, which results in delivery delays, inventory levels that are woefully out of sync with demand, and disappointing financial performance. Those consequences are hardly surprising. After all, how can inventory and production decisions be made effectively when demand forecasts are widely off?

  • Narendra Agrawal is the Benjamin and Mae Swig Professor of Information Systems and Analytics at Santa Clara University’s Leavey School of Business.
  • Morris A. Cohen is the Panasonic Professor Emeritus of Manufacturing & Logistics at the University of Pennsylvania’s Wharton School. He is also the founder of AD3 Analytics, a start-up that developed the OML methodology for supply chain management.
  • Rohan Deshpande is a machine learning scientist at Cerebras Systems and a former chief technology officer at AD3 Analytics.
  • Vinayak Deshpande is the Mann Family Distinguished Professor of Operations at the University of North Carolina’s Kenan-Flagler Business School.

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IMAGES

  1. A Sample Case Study of Decision Making

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  2. Case study solving technique

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  3. Selection criteria for Case study

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  4. PPT

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  5. How to Use a Decision Matrix to Make Tough Choices

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  6. Case Study- Decison Making

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COMMENTS

  1. 100 Examples of Decision Criteria

    The following are common examples of decision criteria both business and personal decisions. Business Decision criteria that are used by businesses to make decisions such as which projects to invest in at a point in time. Personal

  2. How to Write Decision Criteria (With Tips and Examples)

    1. Establish your goals The objectives and goals of your team typically guide any decision you make in the workplace. These goals can influence strategic plans and priorities.

  3. What are Decision Criteria? (Explained With Examples)

    Table of content What are Decision Criteria? (Explained With Examples) Decision criteria are essential factors that individuals or organizations consider when making a decision. They serve as the basis for evaluating different options and ultimately choosing the best course of action.

  4. Do Your Students Know How to Analyze a Case—Really?

    Step 1: Problem definition. What is the major challenge, problem, opportunity, or decision that has to be made? If there is more than one problem, choose the most important one. Often when solving the key problem, other issues will surface and be addressed.

  5. Case Study Methodology of Qualitative Research: Key Attributes and

    This article attempts to look into the various dimensions of a case study research strategy, the different epistemological strands which determine the particular case study type and approach adopted in the field, discusses the factors which can enhance the effectiveness of a case study research, and the debate surrounding the role of a case stud...

  6. Planning Qualitative Research: Design and Decision Making for New

    For example, Nogueiras, Iborra, and Kunnen (2019) used a case study to investigate the process of transformative learning for students in a counseling master's degree program. The case study method is particularly useful for researching educational interventions because it provides a rich description of all the interrelated factors.

  7. A Quick Guide to Case Study with Examples

    Step 4: Choose the Precise Case to Use in your Study. You need to select a specific case or multiple cases related to your research. It would help if you treated each case individually while using multiple cases. The outcomes of each case can be used as contributors to the outcomes of the entire study.

  8. Decision-Making and Criteria

    Common examples of decision-making criteria include costs, schedules, popular opinions, demonstrated needs, and degrees of quality. Here are some examples: If you are recommending a tablet computer for use by employees, your requirements are likely to involve size, cost, hard-disk storage, display quality, durability, and battery life.

  9. Case Study Method: A Step-by-Step Guide for Business Researchers

    Rather than discussing case study in general, a targeted step-by-step plan with real-time research examples to conduct a case study is given. Introduction In recent years, a great increase in the number of students working on their final dissertation across business and management disciplines has been noticed ( Lee & Saunders, 2017 ).

  10. Write Online: Case Study Report Writing Guide

    Next Section Overview. Section D: Reviewing and Presenting , we will explore understanding and meeting your instructor's expectations for the report and presentation. Understand the parts of a case study report including the executive summary, introduction, analysis, criteria, recommendations, conclusion, and references.

  11. Decision Criteria: Definition, Importance and Categories

    For example, if you're purchasing computers, you can specify different criteria, such as configuration, specifications, warranty period and price.

  12. PDF A Case-Study Approach to Managerial Decision Making

    A review of current management texts suggests that non-programmed decision-making processes share the following steps: (1) definition of the problem; (2) identification of alternatives; (3) analysis of alternatives; (4) selec-tion and implementation of preferred alternative; (5) monitoring and revision (Arnold, Heyne, & Buser, 2005; Certo & Cert...

  13. What Is a Case Study?

    Revised on November 20, 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 ...

  14. Decision Criteria

    The three types of decision criteria include economic, technical, and personal criteria. Decision Criteria Explained Decision criteria provides space for the involvement of various factors before making a decision. Also, it helps the managers and senior executives to make an ethical and logical decision.

  15. Choose the Right Decision Criteria

    These are some typical decision criteria: Ease of implementation Cost Ease of modification/scalability/flexibility Employee morale Risk levels Cost savings

  16. Make milestones matter with 'decision gates'—stage gates with real

    The company should establish decision-making criteria to test the business case at each decision-gate meeting. The overall evaluation should consider whether the business case is holding as expected and assess any risks and the related mitigation plans. ... For example, project timelines will be significantly shorter for projects that entail ...

  17. What is a decision matrix? Templates, examples, and types

    A decision matrix encourages objectivity over subjectivity in comparing options and identifying optimal solutions. While every tool has limitations, a product team can enhance decision-making by combining a decision matrix with other frameworks and tools, such as SWOT, RICE, and 2×2 prioritization.

  18. How To Make Recommendation in Case Study (With Examples)

    1. Review Your Case Study's Problem 2. Assess Your Case Study's Alternative Courses of Action 3. Pick Your Case Study's Best Alternative Course of Action 4. Explain in Detail Why You Recommend Your Preferred Course of Action Examples of Recommendations in Case Study Tips and Warnings References What Is Recommendation in Case Study?

  19. 7 quick and easy steps to creating a decision matrix, with examples

    2. Identify important considerations. The second step to building a decision matrix is to identify the important considerations that factor into your decision. This set of criteria helps you identify the best decision and avoid subjectivity. Continuing our example, your team has decided that the important criteria to factor in when selecting a ...

  20. What is a Decision Tree & How to Make One (+ Template)

    Market Research What Is Comparative Analysis and How to Conduct It? (+ Examples) Appinio Research · 30.10.2023 · 34min read Content Have you ever faced a complex decision, wondering how to make the best choice among multiple options?

  21. Alternatives and decision criteria 1 1

    IV. ALTERNATIVES AND DECISION CRITERIA. Alternatives. Carbon Capture and Storage Technology (CCS) is one of the innovative machines that can capture and store present Carbon Dioxide (CO2) in the atmosphere. However, a large amount of money is needed to have this CCS because this technology is expensive.

  22. A Review of Mathematical Multi-Criteria Decision Models with A case study

    Multi-Criteria Decision Making/Analysis (MCDM/MCDA) is a Core of Decision Theory, as an important field of Operational Research (OR) in Mathematics. Multi-Criteria Decision model is a technique that permits Decision Makers (DM) to make the best ... 9 Extremely Important 2,4,6,8 Intermediate value between adjacent For our case study example as ...

  23. Effective Decision-Making; Theory And Case Study in Digital ...

    Some useful points to analyze such as : 1/ What is the problem or opportunity; 2/ Why the problem arises; 3/ What objective to be achieved; 4/ Who will be impacted with the decision, and 5/ What...

  24. How Machine Learning Will Transform Supply Chain Management

    The Problem. Flawed planning methods make it extremely difficult for companies to protect themselves against supply chain disruptions. A Remedy. A new approach, called optimal machine learning ...