Starbucks has never been on my radar. Before I quit drinking coffee, I always made my own version of French Press coffee every morning, but with that said, I do know more then a handful of people who love their Starbucks every morning.  It wasn’t until sometime in 2024 that Starbucks started making the news for the wrong reasons. Sales started declining and it was a really, BIG deal.  

Why do a large Tableau project on Starbucks? Starbucks is a great American brand, and I was curious to see if I could find and share any interesting insights on the company’s current dilemma.  Why a company’s sales would decline is a complex question involving a variety of factors including: customer preferences, competition, decline in quality of product/customer experience, pricing/product mix strategy, business drivers etc. but I share insights with the limited data I have.  The objective of this project is to give more insight into Starbucks’s declining sales and profits.

For this dashboard, I used Microsoft Excel to scrape all the financial data from Starbuck’s financial statements going as far back as 2017.  I went back as far as Starbuck’s 2017 Income Statement to get a feel for what the numbers looked like prior to COVID-19. My goal was to find any patterns or trends that were out of the ordinary. For example, I had to go back and research Starbuck’s 2018 income statement to find out that Net Income increased in 2018 due to ‘gains from the acquisition of our East China joint venture and the sale of our Tazo brand’. In this project, I am looking for trends and patterns versus one-time events as mentioned above.  The process of collecting data was the most time-consuming part of the data prep by far as some financial data tables did not format properly and had to be manually entered.

As much as I wanted to import the data into Python, I ended up doing all the data manipulation/modeling data in Excel. I did this for two reasons (1) It was just a more efficient workflow process to keep everything in Excel before importing spreadsheets into Tableau. (2) I wanted to visually seethe income statement in Excel as this is the norm in the FP&A industry.  Just for reference, the data scraped from each of Starbuck’s financial statements was less than a hundred rows of data.

In Excel, the main function I used to manipulate the data was the TRANSPOSE function. I also did things like creating new columns with calculated cells etc. Some of the data tables I scraped from the financial statements were very sparse; it was easier to copy and paste instead of using a more sophisticated method of aggregating the data.

The most complex part of the data prep was modeling the data correctly in Excel to make creating dashboards in Tableau a smoother process. In a way, I was essentially making my own datasets. There were a couple of times when working in Tableau, I had to go back into Excel to correctly model the data.

The most interesting insight I gained from this project was learning that the International segment is Starbuck’s worst performing segment, in respect to net sales. More specifically, Starbucks saw its International licensed stores have the steeping sales decline from 2023 to 2024. Internationally speaking, Starbucks has the largest number of company operated stores in China.  I googled “largest coffee shop in China” and found out that Luckin’ Coffee has recently surpassed Starbucks as the largest coffee shop in China. Coincidence? Starbucks is facing a fierce competitor in China that it has never seen in the United States. I can attest to this as I was thinking of doing a competitor analysis of other US publicly traded coffee shops, such as Black Rifle Coffee Company, Dutch Bros etc. but I decided against doing a competitor analysis for the mere fact that all the other US publicly traded coffee shops in the US hold a fraction of the market share when compared to Starbucks.

This is going to be the longest section of this article and for good reason. I spent about 6 weeks working on this project a little bit everyday most days. I started with scraping/collecting financial data from Starbuck’s income statements (2017- 2024), modeling the data in Excel, designing the layout of the dashboard in Figma to build the dashboard in Tableau.

In creating this dashboard, I started out by displaying the total net sales, profits etc. for the entire company in a chronological order as you would see these items in an income statement before breaking down net sales by segment. I have to give credit to Brittany Rosen for here article herein Medium showing how to make Comparison Bar Charts, a more visually appealing way to do this in my opinion.  I subsequently created the Average Net Sales Growth Rate bar chart to add more context to the YoY Net Sales Growth metric. It was in this bar chart that I created one of two calculated fields that I am most proud of. It took a little bit of tinkering to make the average net sales metric.  The other calculated field I figured out how to write was a calculated field to specify the color of bars in bar graphs based on certain criteria; this can be seen throughout the entire Starbucks visualization.

I created the ‘Operational Expense as a % of Net Sales’chart to help identify any possible instance where operational expense might beincreasing due to inflation and therefore would be reducing profit margins. Onthis chart, I wanted to add custom shapes but didn’t know what to add so I wentwith the stock shapes Tableau gives you.

I learned how to make a waterfall chart (bottom left) to visually show what net sales, operating expenses and operating profit appear like together in one chart. Like the Comparison Bar Chart, this is a visualization I had to refer to a tutorial because of the advanced logic / calculated fields involved in the building process. Unlike the Comparison Bar Chart, this type of bar chart has more practical usage and is often associated with larger consulting firms.  Despite this, this is the bar chart I thought about not including in the dashboard because it doesn’t quite flow with the story arc but decided to keep it at the last minute.

In my opinion, the Store Type Bar Chart (bottom right) ends the sales decline story arc in a cliffhanger. We found out which segment / store type had the greatest YoY sales decline, but this chart brings up many more questions.

Starbuck’s 2024 financial statement states that China’s ‘competitive environment’ as one factor in Starbuck’s lower than expected performance. China is Starbuck’s largest market outside the United States, so a decline in this market will have a significant impact overall for the company.  It is just not China though, The Americas Company Owned stores also showed a significant decline in Net Sales as well.

It would be interesting to see in more detail what specific cities/states/regions of the United States had a greater sales decline than others etc. To answer those questions, you would probably want net sales store data to perform YoY same store analysis.