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Retail sales, margin and inventory optimisation dashboard

I created a retail dashboard that goes beyond sales totals by showing margin, profit and stock risk together. It helps identify where revenue looks healthy but availability or profitability may be under pressure.

I used synthetic sales and inventory data to calculate revenue, gross profit, margin, stock value and risk flags. I compared categories by both profit and margin, then separated stock-out and excess-stock risk.

Commercial analyticsSynthetic data

Dataset type: Synthetic data. This label is shown clearly so the project is honest about whether the evidence is public, mock, synthetic or portfolio data.I separate source type from method because the reliability and limitations depend on where the data came from.

Retail sales, margin and inventory optimisation dashboard main dashboard preview

Why this matters

Build summary

Retail teams need to see sales, margin and stock risk together. Revenue alone can hide where the business is overstocked, understocked or selling at weaker margin.

I used synthetic sales and inventory data to calculate revenue, gross profit, margin, stock value and risk flags. I compared categories by both profit and margin, then separated stock-out and excess-stock risk.

Key numbers

£7.22M
revenue
37.5%
gross margin
297
stock-out risk items

What I wanted the report to help with

How I approached it

  • Make the main performance question easier to scan.
  • Separate headline totals from the detail that explains them.
  • Show enough context for a non-technical user to trust the next action.
  • Built revenue, gross profit and margin calculations.
  • Created category and store summaries.
  • Flagged stock-out and excess-stock risks separately.

Technical inspection notes

  • Separated revenue, gross profit, margin and stock value so strong sales do not hide poor profitability or availability risk.
  • Created stock-risk flags to identify both low-stock and excess-stock pressure.
  • Compared categories by margin and profit because each tells a different business story.
  • Kept the dataset labelled as synthetic so the method is clear without pretending it is live company data.

Dashboard snapshots

These snapshots show how the analysis was turned into decision-ready visuals.

Click any screenshot to inspect the dashboard evidence more closely.

Retail sales, margin and inventory optimisation dashboard snapshot
Retail overview: Shows revenue, margin and stock-risk headline measures.
Retail sales, margin and inventory optimisation dashboard snapshot
Margin by category: Helps separate high-revenue categories from profitable ones.
Retail sales, margin and inventory optimisation dashboard snapshot
Stock value by category: Shows where cash may be tied up in inventory.

What the analysis showed

  • The sample dataset showed £7.22M revenue.
  • Gross margin was 37.5%.
  • 297 items were flagged as stock-out risk.

What I would improve next

  • Add supplier lead time.
  • Add markdown and promotion effects.
  • Create action owners for high-risk stock groups.