The Store Inventory dashboard helps you optimize inventory at the store level, so you can meet customer demand and maximize sales. You can see how inventory stacks up by product, store, and region and determine if inventory levels are above or below average.
This dashboard is divided into three sections:
- Overview: See a snapshot of inventory levels in stores, by quantities, units, and dollars on hand.
- Drivers: Understand the factors that contribute to your inventory levels.
- Details: Dig in to granular information that helps you take action when inventory is high or low.
The Overview section allows you to get a sense of your inventory status. Use the following map of the screen to guide you.
Inventory by Product (Top 20)
This pie chart breaks down inventory levels for your top 20 products. Hover over a slice for an on-hand number or click to filter the dashboard by that product.
Inventory by State (Top 20)This pie chart breaks down inventory levels for the 20 states that have the highest on hand quantities. Hover over a slice for an on-hand number or click to filter the dashboard by state.
On Hand Totals
These tiles, which update with your filters, show the total units and dollar value of your on hands.
This table provides a sortable breakdown of your inventory by product and gives you a sense of how much supply you have on hand.
Weeks of Supply by Store
This heat map allows you to get a pulse on whether inventory is high or low at stores by state, so you can take steps to normalize your inventory levels. This metric is calculated by taking the on hand inventory and dividing it by the average number of units selling in a week. For example, if you have 100 units on hand and sell 50 units in a typical week, you have 2 weeks of supply. The average number of units selling per week is calculated using the time frame you specify in the Weeks of Supply Lookback Period drop-down menu at the top of the dashboard.
Note: Days where are there are no sales will be excluded from the the calculation. For example, if you select a two week lookback period, but there is only data for the second week, we will only use 1 week for the calculation.