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Data Advisory · Playbook · 3 min read

The 90-Day Data Transformation Roadmap

We deliver value incrementally to build momentum and ensure alignment. Our standard engagement follows a proven, week-by-week pattern.

Data transformation programmes fail at execution, not at strategy. The case for transformation usually writes itself — fragmented reporting, slow decisions, data the board doesn’t trust. The gap between approving the programme and delivering credible value by the twelve-week mark is where momentum is lost, sponsors disengage, and the budget gets recut.

Our 90-day shape exists because most enterprise data programmes try to do too much, too sequentially. They scope a twelve-month platform rebuild, deliver dashboards in month nine, and lose executive air cover in month four. The roadmap below inverts that — visible value in week two, foundation in weeks three to six, adoption in weeks seven to twelve — so the political capital that funded the programme is replenished, not exhausted, by quarter end.

The disciplines behind a credible 90-day programme

A 90-day window is short. What distinguishes programmes that compound from programmes that stall lies less in the framework and more in how three execution questions are answered.

Ship a visible artefact in week two, not week twelve.

The fortnight-one deliverable is not a strategy deck — it is a working dashboard that automates a real reporting pain point. The exact artefact doesn’t matter; that there is one matters enormously. The dashboard buys you the executive air cover you need to do the harder, less visible work in weeks three to six.

Earn the platform rebuild by proving the data is the constraint.

The foundation work in weeks three to six (warehouse schema, pipelines, data quality engine) is expensive and slow. Stakeholders need a reason to fund it. The week-two artefact is that reason — if the dashboard exposes data quality issues that block decisions, the platform rebuild becomes the obvious next step rather than an act of faith.

Make adoption a deliverable, not an afterthought.

Weeks seven to twelve are where most programmes treat training as documentation handover. We treat it as a measurable deliverable — pilot user groups, defined success metrics, ongoing office hours. A platform no one uses is a sunk cost; a platform that pilot users champion becomes the foundation for the next quarter’s expansion.

Underneath the three phases sits a more fundamental discipline: scope ruthlessly. The 90-day programme is not a 12-month programme run in fast-forward. It is a 90-day programme with a specific, defensible end state. The platform serves the business in the chosen scope. Expansion happens after the close, not during it.

The three phases

Weeks 1–2

Assessment & quick wins

We conduct stakeholder interviews across business, risk, and technology to map critical decision pathways and pain points, followed by a rapid assessment of your current data landscape and architecture.

Deliverable A high-impact dashboard that automates a critical Excel report, plus a prioritised 90-day execution roadmap to the target state.

Weeks 3–6

Foundation building

We implement the core data warehouse schema (e.g. a star schema), build robust data pipelines for two to three critical sources, and deploy an automated data quality rules engine.

Deliverable A single source of truth for the initial scope; the core semantic layer live, providing a governed foundation for BI.

Weeks 7–12

Scale & adoption

We accelerate the onboarding of more data sources, enable self-service analytics for pilot user groups with comprehensive training, and execute a change-management programme to drive adoption.

Deliverable The platform scaled, key users trained and empowered, and the solution demonstrably adopted by the business to make decisions.

A caveat

The playbook assumes the case for transformation is real. It does not test the prior question: should this be a 90-day programme at all? Some apparent transformation problems are actually data quality problems that a tight 30-day intervention would fix more cheaply. Others are governance problems that no amount of technology will solve. The Data Advisory pillar we run with clients includes the framing diagnostic that determines whether a 90-day programme is the right intervention.

Go deeper

Strategic Guide to Modern Data Platform Transformation

Our standalone playbook on modern data platform transformation — dbt architecture for regulated data, governance integration, semantic-layer design, and migration sequencing. Free, delivered by email.

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