CPG Sales Dashboard: The Metrics Your Weekly Review Needs

CPG Consulting · September 14, 2026 · 3 min read

A useful CPG sales dashboard helps the team decide where to act next. It connects retail sales to distribution, velocity, availability, and contribution instead of placing unrelated charts on a page. Whether you build it in Excel, Google Sheets, or Power BI, start with the questions your weekly commercial meeting must answer.

Separate the three views of sales

Brand shipments show what customers ordered. Distributor depletions show movement from the distributor to its customers. Retail point-of-sale data shows shopper purchases. Each describes a different step, with different timing. Display them separately and reconcile the differences rather than adding them together as total sales.

Build a focused first page

• Retail dollars and units: current period, comparable prior period, and variance.
• Distribution: authorized, live, or selling stores, with the definition visible.
• Velocity: units or dollars per store per week by comparable item and retailer.
• Availability: in-stock measures or clearly labeled proxies where supplied.
• Inventory: on-hand stock and expected coverage using a consistent demand basis.
• Economics: net revenue and contribution when reliable cost data is available.

Add a short action table with the retailer, issue, owner, due date, and next measurement. A dashboard that ends with “sales are down” leaves the actual analysis to another meeting.

Make the data grain explicit

A practical retail fact table contains one row per retailer, store, SKU, and week when that detail is available. Maintain a product mapping table for UPC, pack size, brand, and shipping case conversions. Keep shipment and retail tables separate if they have different grains; joining them directly can multiply rows and inflate totals.

Record the source, reporting period, and last refresh date. Map each retailer's week-ending convention before building comparisons. An apparently missing week can be a calendar alignment issue rather than a sales issue.

Calculate weighted metrics correctly

Apply the same discipline to percentage changes. Calculate the combined change from combined sales, not the average of each retailer's percentage. Keep retail and ecommerce channels separate when store-based metrics are not comparable.

Choose the tool around the workflow

A spreadsheet can work well when sources are few and the refresh is manageable. A more structured BI model becomes useful when multiple people need consistent definitions, repeatable refreshes, and retailer-level filtering. The tool does not repair mismatched product codes or missing inventory data; those need explicit rules either way.

What should you verify before sharing?

Reconcile totals to the source reports, test one SKU through the entire model, inspect duplicate keys, and confirm filters affect the intended charts. Use a known example to validate velocity and case conversions. Label estimates so they cannot be mistaken for reported actuals.

For the diagnostic discussion behind the charts, read demand versus distribution. For planning inputs, see the retail forecast guide.