Pre-Engagement: Discovery & Readiness Assessment

Before launching a governance program, assess the client's current state, pain points, and organizational readiness. This phase determines whether the organization is ready for governance and identifies the business case.

🎯 Objectives

✓ Understand the client's data landscape, pain points, and strategic goals
✓ Assess organizational maturity using a standard maturity model
✓ Identify executive sponsors and key stakeholders
✓ Build the business case for Data Governance investment
✓ Determine the scope and approach (enterprise-wide vs. phased domain)

Stakeholder Interviews

Conduct 1-on-1 interviews with 15-25 key stakeholders across business and IT. Focus on data pain points, decision-making processes, regulatory pressures, and data-related business failures. Use a standardized questionnaire to enable comparison.

💡 Consultant Tips

● Always interview both business and IT leaders — governance fails if either side is excluded
● Ask about specific incidents where bad data caused problems (cost, delays, compliance issues)
● Listen for phrases like 'nobody owns that data' or 'we don't trust those numbers' — these indicate governance gaps
● Document quotes that can be used in the business case presentation

Data Maturity Assessment

Use a maturity model (CMMI-based or DAMA's DMM) to score the organization across key dimensions: People, Process, Technology, and Data. Score each on a 1-5 scale. Most organizations starting governance will score Level 1 (Ad Hoc) to Level 2 (Repeatable).

💡 Consultant Tips

● Use DAMA's Data Management Maturity (DMM) model — it maps directly to DMBOK2 knowledge areas
● Don't just score overall — score each knowledge area separately to identify specific gaps
● Present the maturity assessment visually (spider/radar chart) to executives for impact
● Be honest about scores — inflating them undermines the business case

Data Landscape Mapping

Create a high-level inventory of key data systems, data flows, data domains, and known quality issues. This doesn't need to be exhaustive — focus on the top 10-15 critical systems and the major data domains (Customer, Product, Financial, Employee, etc.).

💡 Consultant Tips

● Talk to DBAs and data engineers — they know where the real data problems are
● Map both 'system of record' and 'system of reference' for each data domain
● Identify where the same data entity (e.g., Customer) exists in multiple systems — these are your integration pain points
● Note any regulatory or compliance requirements (GDPR, HIPAA, SOX) that create urgency

Business Case Development

Quantify the cost of poor data governance: regulatory fines risked, revenue lost from bad customer data, hours spent on manual reconciliation, failed reporting deadlines. Frame governance as risk reduction + value creation, not just overhead.

💡 Consultant Tips

● Use the '1-10-100 Rule': It costs $1 to prevent a data error, $10 to correct it, $100 to deal with its downstream consequences
● Find 2-3 specific, quantifiable pain points the client already recognizes
● Frame the investment in terms of ROI, not cost — 'For every $1 invested in governance, organizations typically see $5-10 in reduced rework and improved decision-making'
● Get the CFO or COO on board early — their support is often more impactful than the CIO's

📦 Phase Deliverables

☐ Data Maturity Assessment Report (with radar chart)

☐ Stakeholder Interview Summary (themes and pain points)

☐ High-Level Data Landscape Map

☐ Business Case Presentation (with ROI estimates)

☐ Governance Readiness Assessment (go/no-go recommendation)

☐ Preliminary Scope and Approach Recommendation

← Back to Data Governance Implementation