Adidas US Commercial Performance Dashboard

Business problem

Revenue reporting on its own does not show where profit is made or lost. The scenario for this exercise was a commercial team that wants one view of sales, operating profit and margin across regions, retailers and products, so that high-volume segments can be separated from high-profit ones.

Dataset

A public transaction-level sales table from January 2020 to December 2021, with product, retailer and geography fields.

Limitations:

• The provenance of the dataset is not verified, so the figures are practice data and not evidence about the real company.
• Two years of data is a short window for judging seasonality.

Analytical workflow

1. Standardise column formats and remove duplicates and null records.
2. Define measures: Total Sales, Operating Profit, Units Sold, Price per Unit and Operating Margin %.
3. Build the dashboard: KPI cards, monthly sales area chart, state map, retailer and product bar charts and a regional donut, with cross-filtering and global filters for region and date.

Business insights

• Revenue is concentrated in a small group of retailers, which would create dependency risk in a real business.
• Revenue and profit do not line up by product. Men’s Athletic Footwear ranks third in revenue (about $154M) but its margin does not match its sales rank.
• The West region contributes roughly 30% of sales, so growth is geographically uneven.
• Q4 looks weaker than expected for a retail seasonal pattern.

Ideas a commercial team could investigate: shifting focus toward higher-margin channels, earlier Q4 campaigns, and regional expansion. They are hypotheses from this dataset and were not tested.

Methodology and technical decisions

• Margin as the primary measure. Operating margin is tracked next to sales so volume does not hide profitability.
• Drill-down path. The design lets a user go from KPIs to an anomaly and then from region to retailer to product, so a question can be traced to a cause.
• Chart choices follow the question: an area chart for seasonality, a map for geographic concentration, and ranked bars for comparison.

Results and limitations

The dashboard totals are about $900M in sales and $332M in operating profit, a 42% margin. The README’s decision rules and recommendations are examples of how a team might use the dashboard. No recommendation was implemented and no benefit was measured. The report is a .pbix file with a PDF export, not a live published dashboard.