Category Management & Procurement · Case Study
A Power BI model that shows where category risk sits — tariff exposure, single-source concentration, and price erosion — and turns each exposure into a ranked, owner-ready action.
The Business Problem
A tariff announcement lands on a Tuesday. By Wednesday, leadership wants a single number: how much of our spend is exposed? Most procurement teams can't answer that in the meeting — not because the data doesn't exist, but because their analytics was built to report what they spent, not to reveal where they're exposed.
Three questions drive every category risk conversation:
Spend visibility is table stakes now. But a spend cube is a rear-view mirror: it tells you what you bought and from whom, not where the exposure sits. Those risks live inside the spend, so they get discovered the hard way — after the fact. Executives need to see where the risk is; category managers need to know what to act on now. Both should be looking at the same numbers.
| Spend visibility — what most teams have | Risk escalation — what you actually need | |
|---|---|---|
| The question it answers | What did we spend, and with whom? | Where are we exposed — and what's the next move? |
| Which way it looks | Backward — last quarter's invoices, already closed. | Forward — today's exposure and tomorrow's decision. |
| How it gets triggered | Someone asks, and you pull a report. | The risk surfaces itself and ranks by spend at stake. |
| What you leave with | A number to drop into a slide. | A prioritized action with an owner attached. |
The Solution
Built on spend, country-of-origin, sourcing, and price-variance data, the dashboard layers three risk lenses on top of clean, classified spend — each one invisible on a standard spend report:
A sub-category risk matrix scores each of these, a supplier Pareto shows where the exposure concentrates, and the point isn't the heatmap — it's the escalation. Every flagged item resolves to a single recommended move, ranked by the spend behind it.
| Category item | Spend at risk | Vendors | PPV | Risk | Recommended action |
|---|---|---|---|---|---|
| Specialty polymer, single grade | $$$ | 1 | +16% | High | Renegotiate |
| Precision casting, ductile iron | $$ | 2 | +11% | Medium | Dual-source |
| High-torque electric motor | $$ | 2 | +12% | High | Run RFQ |
| Recurring facilities service | $ | 3 | +7% | Low | Re-bid |
Illustrative action list — each exposure lands as one recommended move, ranked by the spend behind it. Sample data.
Live Dashboard
This is the live, interactive Power BI report. Filter by date, category, subsidiary, department, and sourcing status; drill from the sub-category risk matrix into the ranked action list; and trace unit price against PPV over time. Best experienced on a desktop screen.
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Why It Matters
A single spend total tells you almost nothing about where you're exposed. Breaking it down by risk lens, supplier, and SKU turns a category review into a short, ranked list of moves.
When a tariff or a supplier failure hits, the teams that move first aren't the ones with the most data — they're the ones whose analytics already told them where the exposure sat, and what to do about it. This project reflects my approach: understand the business pressure, build something actionable, and keep the path from data to decision short.
Next
If your analytics shows what you spent but not where you're exposed, that gap is worth a conversation. Tell me what your team is working through.