A case study is a detailed analysis of a particular situation, event or problem. It requires the application of critical thinking, analytical skills, and problem-solving abilities. A well-conducted case study can provide valuable insights into the workings of a particular organization or industry. In this article, we will discuss some tips to analyse and solve a case study effectively to draw the best conclusion out of it.

Read the case study thoroughly

The first step in analysing a case study is to read it thoroughly. It is essential to understand the problem or situation, the context, and the key players involved. Reading the case study multiple times can help you to identify critical information and make sense of the data presented.

Identify the key issues and problems

After reading the case study, the next step is to identify the key issues and problems that need to be addressed. This involves breaking down the problem into smaller components and analysing each one in detail. It is essential to consider all the relevant factors that contribute to the problem.

Gather required data for the case assessment

Once you have identified the key issues, it is essential to conduct research to gather additional information. This can include gathering data from different sources, researching industry trends, or conducting interviews with key players. The goal is to gather as much relevant information as possible to help you make informed decisions.

Develop a hypothesis

Based on the research and analysis, it is essential to develop a hypothesis that can help you to understand the problem better. This involves developing a theory or explanation of what is causing the problem and how it can be resolved.

Test the hypothesis by using right tool

Once you have developed a hypothesis, it is essential to test it. This involves analysing the data and information you have gathered to see if it supports your theory. If the data does not support your hypothesis, you may need to revise it and test again.

Develop a plan of action

After testing the hypothesis, the next step is to develop a plan of action. This involves identifying the steps that need to be taken to address the problem and achieve the desired outcome. The plan of action should be based on the data and information gathered during the analysis phase.

Implement the plan

Once you have developed a plan of action, it is essential to implement it. This involves taking the necessary steps to address the problem and achieve the desired outcome. The plan should be implemented carefully and monitored closely to ensure that it is effective.

Evaluate the results

After implementing the plan of action, it is essential to evaluate the results. This involves analysing the data and information gathered during the implementation phase to see if the desired outcome was achieved. If the plan was successful, it can be used as a model for future problem-solving.

Let’s dig down the above methodology by diving in to the below case study


Retail Store Case Study


ABC Retail Store is a small, independent clothing and accessory store located in a busy shopping district. The store’s owner, Sarah, was looking for ways to increase sales and improve the store’s profitability. As part of this effort, she decided to use Tableau to gain insights into the store’s sales data.


The main objectives of this project were to:

  • Visualize the store’s sales data to identify trends and patterns.
  • Analyse the data to identify opportunities for growth.
  • Present the findings in a clear and concise manner to the store’s management team.


To achieve these objectives, the following steps were taken:

  1. The sales data for the past year was extracted from the store’s point-of-sale system and imported into Tableau.
  2. Dashboards were created in Tableau to visualize the sales data in various ways, such as sales by day of the week, sales by product category, and sales by location within the store.
  3. Filters were applied to the dashboards to allow the management team to drill down into the data and explore different aspects of the sales data.
  4. The findings were presented to the management team in the form of Tableau dashboards and accompanying analyses.

The sales data was divided into various categories, such as product type (e.g., dresses, jeans, t-shirts), colour, size, and price range. The data was also broken down by day of the week and by location within the store to allow for analysis of trends and patterns.

In order to visualize the sales data, several different chart types were used in the Tableau dashboards. Line charts were used to show sales over time, bar charts were used to compare sales by day of the week and by location, and scatter plots were used to show the relationship between price and sales volume.

The dashboards were designed to be interactive, allowing the management team to easily filter and drill down into the data to explore specific trends and patterns. For example, they could select a specific day of the week to see how sales differed on different days, or they could select a specific product category to see how it performed compared to other categories.


The Tableau dashboards and analyses provided the following insights into the sales data:

  1. Sales were highest on weekends, with Saturday being the busiest day of the week. This was likely due to the fact that more people are shopping on weekends and the store is located in a busy shopping district.
  2. Sales of clothing items, such as dresses and jeans, were consistently higher than sales of accessory items, such as bags and scarves. This could be due to the fact that clothing items are more essential for customers and are purchased more frequently.
  3. Sales were highest in the store’s front area, which is where the store’s newest and most popular items are displayed. This suggests that the store’s visual merchandising efforts are effective in driving sales.
  4. There were some fluctuations in sales over the course of the year, with some months being busier than others. This could be due to a variety of factors such as holidays, weather, or economic conditions.


Based on the findings, the following recommendations were made to the store’s management team:

  1. Focus marketing efforts on the weekends, particularly on Saturdays, to capitalize on the high foot traffic and sales during these times. This could involve increasing advertising and promotions on the weekends, or hosting in-store events or sales to draw more customers.
  2. Consider introducing new accessory items to the store to diversify the product mix and potentially increase sales. This could involve researching consumer needs and preferences, conducting market research to identify potential product opportunities, and testing new products to see how they perform in the store.
  3. Utilize the store’s front area as a key selling space by keeping it well-stocked with the store’s newest and most popular items. This could also involve experimenting with different visual merchandising techniques to see which ones are most effective at driving sales.
  4. Monitor the sales data on an ongoing basis using Tableau to identify any changes in trends and make adjustments to the store’s marketing and inventory management strategies as needed. This could involve creating regular reports or dashboards to track sales data, setting up alerts to notify the management team of significant changes, and conducting regular analysis of the data to identify opportunities for improvement.

The Tableau retail store project was successful in providing insights into the sales data of ABC Retail Store. By visualizing and analysing the data, the management team was able to identify trends and opportunities for growth. The use of Tableau allowed for easy exploration of the data and the ability to quickly identify key trends.

The recommendations made as a result of this project have the potential to improve the store’s sales and profitability. By focusing on weekends, introducing new products, utilizing the store’s front area as a key selling space, and continuously monitoring the sales data, the store can better understand their customers and adapt their marketing and inventory management strategies to meet their needs.

Overall, the Tableau retail store project was a valuable investment for ABC Retail Store, and the use of this tool will likely continue to provide benefits for the business in the future.

Now we can finally conclude that analysing and solving a case study requires careful research, critical thinking, and problem-solving abilities. Remember that the key to success is to gather as much relevant information as possible, develop a hypothesis, test it, develop a plan of action, implement it, and evaluate the results.