Inventory Capital Exposure

A Power BI model that identifies where capital is tied up in inventory, flags stale stock, and uses ABC analysis to prioritize SKU-level actions that improve net working capital.

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The Business Problem

Improving net working capital through inventory visibility.

Three questions drive every working capital conversation:

Where is our capital tied up?
What SKUs can we focus on to reduce capital and holding costs?
What SKUs can we focus on to reduce DIO and increase inventory turns?

Executives need to see where things stand and where the risk is. Plant teams need to know what to prioritize and act on now. Both should be looking at the same numbers.

Over time, trend lines on capital tied up, DIO, and turns show whether that's moving in the right direction.

The Solution

A ranked view of where the money sits.

Built on inventory transactions, cost, and classification data, the dashboard answers:

Where is capital tied up, and how much is stale?
How does that split across ABC classes and individual SKUs?
Which SKUs make up 80% of value, and which are tail spend?

Each SKU shows its value, days on hand, and ABC class side by side — enough to spot priority items and set aside tail spend that doesn't need attention.

Live Dashboard

Test it yourself.

This is the live, interactive Power BI report. Explore where capital is tied up, drill from ABC class down to individual SKUs, and check coverage age. Best experienced on a desktop screen.

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How It Was Built

Built independently, end-to-end.

Power BI — front-end: value by class, coverage-age bands, SKU drill-through
SQL — ETL joining transactions, cost/class attributes, and PO history
Claude — generated the synthetic dataset behind this demo

Power BI SQL Claude Working Capital ABC Analysis Aging Risk

Data Sources

Product cost & classification: unit cost, category, ABC/XYZ class per SKU

Inventory transactions: daily on-hand and demand, used for days-of-supply coverage

Purchase orders: order and receipt history for cost validation

Demo built on a synthetic dataset generated with Claude. Figures are representative, not client data.

Why It Matters

A ranked list, not a lump-sum number.

A single inventory total tells you almost nothing about where to act. Breaking it down by class and SKU turns a working capital review into a short, ranked list.

This project reflects my approach: understand the business pressure, build something actionable, and keep the path from data to decision short.

Facing a similar challenge? Let's talk.

Working capital visibility, excess inventory, or another analytics problem — I'd love to hear what your team is working through.

Send me an email Back to all work