The 90-day data roadmap: turn your assessment into results

Multi-year data strategies fail when they lose sponsorship before showing value. A quarter matches budgeting and leadership cycles, forces prioritisation, and creates a natural checkpoint to reassess and re-plan.

A roadmap is only as good as the evidence under it. Start from a scored assessment of data maturity, and of AI readiness if AI is on the agenda, with current and target states agreed by data and business leaders. See data maturity assessment.

• Confirm the target state and the business outcomes it serves.
• Rank gaps by impact and effort; pick the top three. Name an accountable owner for each.
• Identify gating blockers (governance ownership, data access, platform limits) and put them first.
• Choose one quick win that a business stakeholder will notice, such as a trusted metric, an automated report or a fixed pipeline.
• Check capacity honestly: do you have the skills to deliver, or do you need to hire?

• Deliver the quick win end to end and publicise it.
• Make progress on the structural fixes: define critical data elements, automate quality checks, agree definitions for key metrics, set up deployment paths.
• Stand up the governance basics needed for the next phase.
• Start hiring or contracting for skills gaps that would otherwise stall the plan.

• Move fixes from project to process: owners, monitoring, documentation.
• Measure outcomes against the baseline: adoption, quality, time to insight, use cases shipped.
• Reassess using the same framework, compare dimension by dimension, and set the next quarter's roadmap.
• Report to leadership in the same language as the original assessment.

A roadmap that fits on one page. Every item has an owner, a measure and a date. Blockers are called out explicitly. Skills gaps are named and funded rather than assumed.

Too many priorities; actions without owners; tools bought before foundations are ready; no reassessment, so progress becomes a matter of opinion.

A software company's assessment shows three priority gaps: untrusted revenue metrics, a fragile ingestion layer and no data owner for customer data. Their roadmap names an analytics engineering lead to define and test revenue metrics in days 1–60, as the visible quick win for finance. A platform lead stabilises ingestion with monitoring and alerting. The COO names a customer-data owner in week two. Because nobody in-house has analytics engineering experience, they hire for it in the first month. At day 90 they reassess, see governance and foundations move, and fund the next quarter on evidence.

Review it fortnightly with owners, update status in the same document leadership sees, and resist adding priorities mid-quarter. New ideas go into the next cycle's backlog.

carbon.iq Pro ($19 a month) generates an Intelligence Roadmap from your assessment results. It prioritises gaps across data maturity, Team, AI Readiness and Technology Stack. The AI Advisor answers questions grounded in your scores, and the Report Builder exports the roadmap straight into Google Workspace or Microsoft 365, ready for your leadership team. Pro is $19 a month (charged as R300). Build your roadmap with carbon.iq →