What it measures
% of SKUs meeting minimum volume threshold
it measures the outcome of ranging decisions made weeks or months prior. A low score confirms that operational complexity and inventory holding costs have already been incurred for unproductive SKUs.
Business impact
- Increased 'chaos tax' from managing a long tail: frequent, small production runs, fragmented inventory, and excessive line changeovers that bleed factory capacity and inflate labor costs.
- A bloated inventory position from unproductive SKUs ties up cash and warehouse space, while increasing shelf-life pressure and the risk of write-offs on expired stock.
- Sustained low productivity places the business in the commercial red zone, triggering formal retailer range reviews that result in forced delistings and loss of shelf presence.
Formula
(SKUs above threshold / Total active SKUs) x 100Grain
One row per material per batch per storage location per day
Inside the Implementation Pack
A preview of what's actually built for this KPI — extracted from the real Implementation Pack, not a mockup.
This is the primary ratio the pack's other measures build on — trend, rank, and period-comparison variants, all on Fact_Inventory_Snapshot. It guards against missing dates and values with NOT ISBLANK checks.
Fact_Inventory_Snapshot— 6 mandatory columns — qty unrestricted, storage location key, ...Dim_Material— material_key + material_descriptionDim_Plant— key + nameDim_Storage_Location— key + nameDim_Date— Auto-generated calendar table — no customer data required
Full field-by-field data contract, in 4 SQL dialects (SQL Server, Snowflake, Databricks, BigQuery), ships in the pack.
| Target | 0.85 — performance considered compliant at or above this line |
| Warning | 0.7 — amber alert — triggers a review |
Both live in one Excel tab — change them, refresh the report, done. No DAX editing needed.
Everything you need to build Range Productivity in Power BI — dimensional model, DAX measures, SQL views, and a food-industry demo dataset.