Illustrative examples
Newtown Analytics does not yet have authorized client case studies to publish. The examples below use hypothetical data to show how our analysis approach works — they are not results from any client engagement.
Finding hidden excess inventory
Scenario: a hypothetical $50M consumer brand has growing inventory alongside declining inventory productivity. Leadership can see the trend in the aggregate numbers but isn't sure which products are driving it.
Inventory turns
2.6x
vs. 3.4x prior year
Weeks of supply
16.8
company average
Excess inventory
$4.1M
estimated, at cost
Weeks of supply by inventory category
Gold indicates categories carrying materially more weeks of supply than the business average — the concentration where working-capital opportunity is typically found.
SKU-level analysis segments inventory by category and behavior rather than looking at the business in aggregate. In this hypothetical scenario, a small number of categories — tail and discontinued products, in particular — carry a disproportionate share of weeks of supply. That concentration is typically where working-capital opportunity is found: identifying which specific SKUs to reduce, liquidate, or stop replenishing, without touching the core assortment that drives sales.
Understanding forecast bias
Scenario: a hypothetical business consistently overrides its statistical forecast with a more optimistic commercial view — and wants to understand how much that override is contributing to forecast error.
Comparing the statistical forecast, the commercial forecast, and actual demand side by side makes bias visible rather than anecdotal. In this hypothetical example, the commercial forecast consistently runs above both the statistical forecast and actual demand — a pattern that, at the SKU level, often points to specific products or categories where overrides should be governed more tightly.
Connecting S&OP to working capital
Scenario: a hypothetical executive team wants their S&OP meeting to connect demand, supply, and inventory decisions directly to their impact on revenue and working capital — rather than reviewing each in isolation.
Demand
+8%
vs. prior quarter, hypothetical
Supply
94%
on-time fill, hypothetical
Inventory
17.2 wks
weeks of supply, hypothetical
Revenue
$62M
quarterly, hypothetical
Working Capital
$3.4M
opportunity identified, hypothetical
Illustrative working-capital view
Illustrative proportions — not derived from client data.
When a single executive view ties demand and supply decisions to their working capital consequence, S&OP meetings shift from status updates to decisions — because everyone in the room can see the same trade-off at the same time.
Interested in what this kind of analysis could show for your business?
An Inventory & Forecasting Health Check applies this same approach to your own data.