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Situation

  • Large global manufacturing organization
  • SAP ECC landscape
  • 200+ integrations
  • Thousands of reports
  • No enterprise architecture capability
  • Growing AI ambitions
  • Significant operational complexity
  • Executive concern around future ERP decisions

Challenge

Despite years of successful delivery:

  • Architecture had evolved organically
  • Reporting was tightly coupled to operational systems
  • Enterprise data strategy was absent
  • AI initiatives were moving faster than platform maturity
  • Technical debt was becoming a business risk

Approach

Within weeks, dataMaven:

  • Interviewed executive leadership
  • Reverse-engineered the enterprise architecture
  • Mapped data flows
  • Assessed governance
  • Assessed master data management
  • Assessed analytics
  • Built an enterprise capability model
  • Produced an executive-ready transformation roadmap

Outcome

The executive team gained:

  • A shared understanding of current state
  • Enterprise architecture principles
  • A data strategy
  • An AI-readiness roadmap
  • A modernization roadmap
  • An executive decision framework
  • A target operating model
  • Transformation sequencing

Key insight

The greatest obstacle to AI was not AI technology — it was the absence of an enterprise data foundation.

Engagement snapshot

Global manufacturing
Industry
20,000+
Employees
40+
Factories
50+
Countries
200+
Integrations assessed
Thousands
Reports reviewed
Executive leadership
Stakeholders

Deliverables

  • Enterprise Architecture Assessment
  • Enterprise Data Assessment
  • AI Readiness Strategy
  • Executive Roadmap
  • Transformation Plan

What changed — week by week

Week 1Executive interviews
Week 2Architecture discovery
Week 3Current-state blueprint
Week 4Enterprise data assessment
Week 5Executive roadmap
Week 6Transformation strategy
This engagement is how we approach AI readiness.AI Readiness

Facing a complex landscape — or an ambitious build — and a decision you need to make with confidence? That’s the work.

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