Master-data stewardship navigator

Win statement

Enable data stewards and business-data owners to use Master-data stewardship navigator to reduce friction in the work, with a visible source, an exception path, and a human owner for the decision.

Description

Key benefits

• ·Turns files, forms, and records into usable information without pretending extraction is perfect.
• ·Creates a visible exception path for low-confidence or missing information.
• ·Improves searchability, traceability, and handoff quality.
• ·Reduces repeated manual re-entry.

Potential impact

These are pilot hypotheses, not promised outcomes. Validate them against a real baseline, quality sample, and user feedback.

Success metrics

Services needed

A product or mission application needs custom code, a model choice, complex tools, multi-step or multi-agent orchestration, multimodal input, evaluation, observability, network control, or a scalable managed runtime. Move to Copilot Studio when a low-code workflow and connected conversational experience can solve the problem. Move to Microsoft 365 Copilot (Premium) when the work is best handled by a licensed employee inside familiar Microsoft 365 surfaces.

Data sources

• ·Approved document repositories, forms, images, and structured systems of record
• ·Metadata, retention schedules, and classification policies
• ·Human-validated sample sets for testing accuracy and exceptions

Implementation considerations

• ·Name one accountable business owner, one technical owner, and one content or data owner before the pilot starts.
• ·Define what the agent may advise, what it may do, and what must remain a human decision.
• ·Use representative test cases, including incomplete, conflicting, and out-of-scope inputs.
• ·Design the exception path before measuring straight-through success.
• ·Measure user effort, quality, and rework together. A high interaction count alone does not show value.
• ·Select prompt, workflow, or hosted-agent architecture based on the control actually required. Do not choose hosted agents merely because they are more technical.
• ·Define model evaluation thresholds, tracing, identity, tool permissions, network requirements, and operational support before production release.
• ·Treat model and tool behavior as a product with release controls, monitoring, rollback, and a named response owner.
• ·Category-specific focus: Content & data.

Human review · A named qualified person reviews exceptions, low-confidence output, and any recommendation or action with material consequence.

Executive FAQ

Next actions

• 01Observe 5-10 real examples of master-data stewardship navigator and map the current work, delay, handoff, and exception path.
• 02Name the accountable decision owner, source owner, technical owner, and pilot audience.
• 03Choose the smallest approved content set, data set, and action set that can prove or disprove the value hypothesis.
• 04Create a representative test pack, including success, ambiguity, bad input, and escalation cases.
• 05Run a time-boxed pilot with a measured baseline and a structured user-feedback loop.
• 06Review quality, rework, safety, adoption, and value together. Expand only when the work is demonstrably better.

Estimated timeline

12-20 weeks after discovery

1. Discovery, architecture, and data readiness2-4 weeks

   Define the job, risk boundary, architecture, source data, tools, evaluations, and operating model.

2. Proof of concept3-5 weeks

   Build an instrumented, limited-scope proof of concept using representative data and test sets.

3. Pilot and hardening4-6 weeks

   Add identity, observability, safety controls, exception paths, and user testing in a controlled pilot.

4. Production release3-5 weeks

   Complete release readiness, support design, evaluation thresholds, training, and controlled scale-up.

Provenance

Inferred candidate · Microsoft Foundry (Azure)

Candidate. Discovery and validation required before any build commitment.