Framework

The Buyer's Private Scorecard

This is the rubric a buyer's diligence team uses to grade your data. Six categories. Three ratings. And what they are actually thinking when they score you.

Most diligence prep advice tells you what to do. This tells you what the other side is looking for.

When a buyer's data team opens your data room, they are not browsing. They are scoring. Every sophisticated acquirer has an internal rubric, formal or informal, that grades the quality of what they find. The score drives how hard they negotiate, how much risk they price in, and whether they walk.

This scorecard is built from patterns across dozens of mid-market transactions. The categories, the rating criteria, and the buyer commentary reflect what actually happens in diligence, not what advisors tell you in pitch decks.

Grade yourself honestly. The buyer will.

01

Revenue Data Integrity

Critical Weight
Green

Revenue reconciles across CRM, ERP, and financial reporting within 1% variance. Methodology documented. Monthly cadence.

Yellow

Revenue reconciles with manual effort. Some definitions are informal. Reconciliation happens quarterly or ad-hoc.

Red

Revenue figures differ across systems with no documented methodology. Reconciliation requires multiple people and more than a week.

What the buyer is thinking

This is the first thing we check. If revenue does not tie out in the first 48 hours, we price in a 10-20% data quality risk adjustment.

02

Customer Master Data

Critical Weight
Green

Single source of truth for customer identity. Deduplication rules in place. Unique customer count defensible and auditable.

Yellow

Customer data exists but duplicates are known. Count depends on which system you query. Cleaning is possible but not done.

Red

No reliable customer count. Multiple systems with conflicting records. "It depends on how you define customer."

What the buyer is thinking

If you cannot tell us how many customers you have, we cannot model retention, LTV, or concentration risk. Everything downstream breaks.

03

KPI Definitions and Methodology

High Weight
Green

Top 10 KPIs documented in writing with calculation methodology, data sources, and named owner. Consistent across all reporting.

Yellow

Key metrics exist but definitions are institutional knowledge. Different teams may calculate slightly differently.

Red

No formal definitions. Metrics are calculated ad-hoc. Board deck numbers cannot be traced to source data.

What the buyer is thinking

We will ask for gross margin methodology in week one. If the answer is "let me check with the controller," we know governance does not exist.

04

Historical Data Availability

High Weight
Green

Monthly granularity for 36+ months. Segmentable by customer, product, geography. Accessible in structured format within 48 hours.

Yellow

Annual or quarterly data available. Monthly requires reconstruction. Some segments accessible, others require manual work.

Red

Historical data incomplete, inconsistent across periods, or trapped in legacy systems that no one can query.

What the buyer is thinking

We need cohort analysis and trend data to build our model. If historical data takes weeks to produce, we assume the worst about what it will show.

05

System Integration and Data Flow

Medium Weight
Green

Core systems connected via documented, monitored integrations. Data flows are automated and auditable. Error handling in place.

Yellow

Some integrations automated but fragile. Key data flows depend on scheduled exports or manual transfers. Limited monitoring.

Red

Systems are siloed. Data moves via email, spreadsheet, or manual entry. No integration documentation.

What the buyer is thinking

Manual data flows are a post-close cost we will factor into our offer. Every manual process is a person dependency we need to replace.

06

Data Governance and Ownership

Medium Weight
Green

Named data owners with authority. Change management process for metric definitions. Regular quality audits. Escalation paths documented.

Yellow

Informal ownership exists. Quality is managed reactively. No regular audit cadence. Governance is aspirational.

Red

No named owners. Data quality is nobody's job. Issues are discovered when reporting breaks.

What the buyer is thinking

Governance tells us whether data quality will hold after the deal closes. Without it, every metric is a snapshot that could degrade.

How to Read Your Score

Count your greens, yellows, and reds across all six categories.

  • 5-6 Greens. You are in the top 10% of mid-market companies. Your data room will accelerate the deal and may justify premium pricing.
  • 3-4 Greens, rest Yellow. You are ahead of most but the gaps are visible. A focused 60-90 day sprint closes them before a buyer finds them.
  • Majority Yellow. This is where most companies land. It is fixable but not fast. Start now if a transaction is within 18 months.
  • Any Red in Revenue or Customer Data. These are the two categories that kill deals or trigger significant price reductions. Address them first regardless of everything else.
  • 3+ Reds. A buyer will either walk or discount aggressively. The good news is that acknowledging it puts you ahead of most companies who discover this mid-diligence.
Next Step

Want to know exactly where you stand?

A Data Readiness Assessment produces a detailed version of this scorecard with your actual data, your specific gaps, and a prioritized action plan.

Contact Graeme Crawford