An enterprise BI assessment should review stakeholder questions, current reports, source systems, KPI definitions, data quality, platform maturity, workflows and adoption risks. The output should be a prioritized first delivery path.
Checklist
- Stakeholders and recurring decisions that are slow, disputed or unsupported.
- Existing reports people trust, reports people challenge and spreadsheets that quietly run important processes.
- ERP, CRM, finance, operational databases, APIs and files, including owner, refresh pattern and known quality issues.
- Metrics that create debate, especially KPIs with multiple formulas.
- Planning, approval, correction and maintenance workflows around reports.
- AI readiness across curated definitions, permissions and reliable context.
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List the recurring decisions that are slow, disputed or unsupported. Separate executive, finance, operations, sales, logistics and other domain needs instead of treating BI as one generic dashboard request.
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Identify the reports people trust, the reports people challenge and the spreadsheets that quietly run important processes.
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Map ERP, CRM, finance, operational databases, APIs and files. For each key source, note owner, refresh pattern and known quality issues.
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Document the metrics that create debate. If the same KPI has multiple formulas, the first delivery should often fix definitions before adding new visuals.
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Look for planning, approval, correction and maintenance processes around the reports. These often need Power Apps or structured workflow, not another export.
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AI on enterprise data needs curated definitions, permissions and reliable context. The assessment should show what is ready and what would be risky.
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