Business Intelligence Rollout Lessons Learned
This is a practical guide to building a lessons learned for a business intelligence rollout project — what went well and badly, captured to improve future projects, adapted to the realities of deploying BI dashboards and self-service analytics.
What a Lessons Learned is
A lessons learned is what went well and badly, captured to improve future projects. For the full concept and how it works in general, see Lessons Learned. On a business intelligence rollout project it plays the same role, tuned to this kind of work.
Why it matters for a Business Intelligence Rollout project
Business Intelligence Rollout projects live or die on deploying BI dashboards and self-service analytics. A well-built lessons learned gives the team a shared, explicit reference for exactly that — reducing ambiguity, aligning stakeholders, and making problems visible early enough to act. Skipping it, or doing it generically, is how business intelligence rollout projects drift into avoidable delay and cost.
What to include
- What happened
- Impact
- Root cause
- Recommendation
Business Intelligence Rollout-specific considerations
Tailor the lessons learned to the risks that most often derail business intelligence rollout projects:
- Data trust and quality
- Dashboard sprawl
- User adoption
Example
On a real business intelligence rollout project, the lessons learned would be shaped by deploying BI dashboards and self-service analytics. In particular, it should explicitly account for the project’s biggest risks — data trust and quality, dashboard sprawl, user adoption — rather than treating them as afterthoughts.