Data strategy starts with the decisions information must improve

Data strategy starts with the decisions information must improve

Data has value only when it improves a decision, service or control. A strategy centered on platforms, catalogues or �single sources of truth� can produce technically sound assets that no operating owner uses. Begin with the decisions where better timeliness, quality or granularity would change an outcome, then build the data capability those decisions require.

Create a portfolio of decision and service use cases. For each, name the owner, action, frequency, required evidence and economic or risk value. Map the data products, sources and transformations needed, including latency, quality, privacy and access. This exposes shared foundations worth building once and specialist data that should remain close to its domain.

Assign domain ownership and common rules. Owners are accountable for meaning, quality, access and lifecycle; central governance supplies standards, interoperability and assurance. OECD�s 2026 Digital Government Outlook finds 94% of surveyed governments have data strategies and 92% metadata standards, but only 64% formal data-quality assessment standards�evidence that frameworks often outrun operating practice.

Fund reusable products, not endless extraction. Give high-value datasets service levels, versioning, lineage, support and usage measures. Automate quality checks at source and make exceptions visible to consumers. Govern sharing through purpose, proportional safeguards and transparent access decisions so trust enables reuse rather than blanket restriction.

Measure decisions improved, service performance, time to data, reuse, quality and avoided reconciliation�not storage volume or dashboard count. Retire products without demand and revisit assumptions as decisions change. Data strategy works when reliable information arrives within the operating cadence, ownership is clear and investment follows demonstrated enterprise value.