EXECUTIVE INSIGHTS

Sharper questions forcomplex transformation.

Practical points of view for leaders who need to connect strategy with governance, SAP execution, operational readiness, and responsible AI.

Green is not ready: five questions before an SAP go-live

A status color reports activity. Readiness requires evidence that the business can execute its most important outcomes after cutover.

A program can be green because loads ran, defects are trending down, test scripts passed, and owners attended sign-off meetings. None of those facts independently prove that a plant can plan, buy, make, inspect, cost, stock, and deliver when the legacy system stops.

Ask for the operating chain, not the object list.

For every critical business outcome, leadership should see the connected master data, transactional conversion, configuration, interfaces, controls, people, and decisions that make it possible. A material that loaded is not ready if the relevant plant view, BOM, routing, production version, source, cost, quality state, or opening stock is missing.

THE FIVE QUESTIONS
  1. Which business outcomes must work on day one?
  2. What dependencies must be true for each outcome?
  3. What evidence proves those dependencies are ready?
  4. Which decisions remain open, who owns them, and by when?
  5. What is the consequence if the evidence does not improve before the next gate?

The executive view should combine readiness, trajectory, blockers, decisions, and consequence. That is a much higher bar than asking whether the data workstream is green—and it is the bar a go-live decision deserves.

SAP MDG is not data governance—and that distinction matters

Workflow can enforce a decision. It cannot decide who owns the standard, which variation is legitimate, or how the enterprise will measure value.

Organizations often begin governance by discussing data models, change requests, workflow, duplicate checks, and system architecture. Those are important design topics. They are not the operating model.

Governance starts before the platform.

The business must determine where enterprise harmonization creates value, what may remain local, who owns cross-functional outcomes, who can approve exceptions, and which controls belong inside the process. Only then can SAP MDG be designed as an effective enabling layer.

MDG should automate and evidence the governance model. It should not be asked to invent one.

A durable design connects domain councils, business ownership, stewardship, policy, quality measures, workflow, and escalation. That is how governance survives the transformation program and becomes part of normal operations.

AI readiness is an operating-model decision

The first question is not which model to use. It is whether the enterprise can trust, govern, and take responsibility for AI-enabled action.

A promising use case can stall even when the technology works. The underlying data may lack an accountable owner, common business meaning, acceptable quality, traceable lineage, or permission for the intended use. The process may also lack a human decision point and a clear owner for the outcome.

Evaluate the use case as a decision system.

For each use case, define the business decision, accountable owner, required inputs, authoritative sources, quality thresholds, allowed actions, human oversight, feedback loop, and measure of value. This reveals whether the problem is a model problem, a data problem, a process problem, or an accountability problem.

READINESS LENSES

Value · Ownership · Data trust · Process integration · Control · Adoption · Learning

AI readiness is therefore not a gate owned by the technology team. It is an enterprise operating-model choice—and the organizations that treat it that way will scale more confidently.

Choose one difficult decision. We will help make the evidence visible.

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