Industrie manufacturièreMid-marketDuration: 12 semaines

How an industrial mid-market company recovered 3.2% margin in 12 weeks

Mechanical components manufacturer, 400 employees, France

Results

+3,2%

gross margin recovered

−3 sem.

reporting delay (M+3 → real-time)

12

data sources reconciled

1

unprofitable product line discontinued

Challenge

The CFO had been watching gross margin erode for 3 quarters without being able

to explain it. Monthly reporting arrived at M+3 weeks, too late to act.

Commercial discounts were neither tracked nor capped. Each department had

"its own" spreadsheet with different numbers. The executive team was flying blind.

Approach

  1. 1

    Week 1-2: Data maturity audit with the Maturity Auditor — mapping finance data flows, identifying 12 inconsistent sources

    Maturity AuditorValue Architect
  2. 2

    Week 3-4: Business case construction with the Value Architect — P&L impact modeling by lever (discounts, hidden costs, unprofitable projects)

    Maturity AuditorValue Architect
  3. 3

    Week 5-8: Margin dashboard deployment by client/project/product — ERP (SAP) + CRM (Salesforce) + accounting connectors, automatic drift alerts

    Maturity AuditorValue Architect
  4. 4

    Week 9-10: Leakage analysis — identification of 3 structurally unprofitable clients and 2 product lines below threshold

    Maturity AuditorValue Architect
  5. 5

    Week 11-12: Prioritized action plan presented to the executive team — renegotiation of 2 contracts, discount caps, discontinuation of 1 product line

    Maturity AuditorValue Architect

Testimonial

We knew we were losing margin, but we didn't know where. In 12 weeks, we had a clear dashboard and an action plan validated by the executive team. The project ROI was positive from the first quarter.

Directeur Administratif et FinancierETI industrielle, Auvergne-Rhône-Alpes

Agents involved

AGENT

Maturity Auditor

Scorecard + roadmap 90 jours pour cadrer la transformation data/AI.

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AGENT

Value Architect

Hiérarchiser et chiffrer les use cases data/AI pour le board.

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