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Case 15/Supply Chain Analytics/FMCG / Retail

Procurement Intelligence Engine — FMCG

Vendor scoring, bid analytics and negotiation recommendations across $200M+ of annual spend.

The challenge

What was breaking

Procurement teams spent 40+ hours per negotiation cross-referencing vendor history, past bids, SLA performance and market benchmarks — entering deals without intelligence-backed leverage.

The solution

Procurement Intelligence Engine

An engine that scores vendors on price stability, SLA adherence and risk, clusters historical bids and recommends target prices with scenario modelling.

  • Vendor intelligence scoring
  • Bid analytics with clustering and trend detection
  • Negotiation recommendation engine
  • What-if scenario modelling
Solution design

How it works

4 stages
  1. 01

    Score

    Price stability, SLA adherence and risk profile scored per vendor.

  2. 02

    Analyse

    Historical bids clustered with price spread and trend detection.

  3. 03

    Recommend

    Target ranges, leverage points and what-if scenarios surfaced.

  4. 04

    Apply

    Insights used live across negotiations and supplier-mix decisions.

Business impact

Before vs. after

MetricBeforeAfterImprovement
Prep time2–3 days15 minutes95% faster
Price advantage~2–3% below ask8–12% below ask4–9% gain
Supplier risk events12/year3/year75% reduction
Spend coverageBaseline$200M+Enterprise-wide
Key outcomes

What changed

  • Negotiation prep down from days to 15 minutes
  • Better price leverage via insight-backed strategy
  • Optimised supplier mix with risk scoring
  • Applied across 50+ negotiations
Capabilities

Inside the build

Vendor intelligence scoring
Bid analytics with clustering and trend detection
Negotiation recommendation engine
What-if scenario modelling
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Could this work for your team?

We adapt these blueprints to your domain, data and governance constraints — typically delivering a working prototype in weeks.

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