Deals fail because of data more than they succeed because of it. This is one of the most under-discussed dimensions of M&A, and one where CDOs can add enormous value.
Phase 1: Pre-Deal Data Due Diligence
Before the deal closes, the acquiring team needs to understand what data assets they're actually buying, and what data liabilities they're inheriting.
A thorough Data due diligence covers:
The standard M&A due diligence process often gives data 10% of the attention it deserves. For data-rich businesses, it should be 40-50%.
Phase 2: Data as a Valuation Driver
Data assets can dramatically affect acquisition price. The Microsoft-LinkedIn deal is canonical: LinkedIn's 2016 revenue was approximately $3B. Microsoft paid $26.2B, a 9x revenue multiple considered extraordinary at the time.
The justification: LinkedIn's data on 430M+ professionals was worth significantly more than the revenue line suggested. Microsoft was acquiring the largest professional behavioral dataset in the world, along with the network effects that made it self-reinforcing. The premium over book value was largely payment for data.
When Google acquired Fitbit for $2.1B in 2019, the strategic logic was primarily about health data, 100M+ users' biometric data over years, not Fitbit's declining hardware revenue.
Knowledge check
1. Why does the lesson argue that data due diligence deserves far more attention than the standard M&A process typically gives it, especially for data-rich businesses?
2. The Microsoft-LinkedIn and Google-Fitbit examples in the lesson primarily illustrate which concept?
3. According to the lesson, why is poor data quality in a target's CRM a serious risk during valuation?
4. Select ALL elements that a thorough pre-deal data due diligence should cover according to the lesson.
Select all the correct answers.
5. Select ALL statements that correctly reflect the lesson's view on post-merger data integration.
Select all the correct answers.
Phase 3: Post-Merger Data Integration
This is where deals most often go wrong.
McKinsey research shows 70% of M&A deals fail to deliver promised value. Data integration failures are among the most common causes. Two organizations with different data architectures, different definitions of "customer," and different Data qualityData qualityThe degree to which data is fit for purpose: accurate, complete, consistent, timely, valid and unique. Poor quality data undermines analytics, reporting and AI.View full definition → standards are told to share data on Day 1.
What typically happens:
The CDO should be embedded from early due diligence, not brought in after signing.
Before closing: Lead the Data due diligence. Flag Data qualityData qualityThe degree to which data is fit for purpose: accurate, complete, consistent, timely, valid and unique. Poor quality data undermines analytics, reporting and AI.View full definition → issues affecting valuation. Identify data compliance risks affecting deal structure.
During negotiation: Quantify the value of data assets you're acquiring. Push for data-specific representations and warranties in the purchase agreement.
After closing: Own the data integration workstream. Define "Day 1 data" (what must work immediately) vs. "Year 1 data" (what can wait). Build the Master Data ManagementMaster Data ManagementMaster Data Management (MDM) is the discipline of creating and maintaining a single, consistent, trusted version of an organization's core business entities like customers, products, and suppliers.View full definition → framework allowing the combined entity to operate with a single source of truth.
When Sprint merged with Nextel in 2005, analysts pointed to integration failures as a primary reason the deal ultimately failed. Customer data couldn't be reconciled across the two networks, leading to billing errors, service disruption, and massive churn, Nextel lost 80%+ of its customer base within 5 years.
A better Data due diligence and integration plan could have identified the incompatibility of billing systems before the deal closed, and either renegotiated the price or avoided the deal entirely. The CDO who wasn't invited to the due diligence process cost the acquirers billions.