Disconnected Data: The #1 Risk in Your Next M&A Deal

Mergers and acquisitions (M&A) are high-stakes deals, promising synergies, growth, and expanded market reach—but only if everything goes according to plan. HBR reports that as many as 70 to 90 percent of acquisition deals fail. Data is often a leading cause: Beneath the surface of strategic alignment goals and rosy financial projections lies the threat of disconnected data. Since data brings crucial value to every business, failing to resolve fragmented and inconsistent data can derail a promising merger before it blossoms.

During M&A, the role of data is amplified. Massive data volumes and increasingly stringent global data privacy and security regulations create a complex M&A landscape where the risks of disconnected data can be obscured until they cause issues. Ignoring data silos and complexities isn’t an option—it’s the number one risk threatening the success of M&A transactions.

In this post, we’ll explore how siloed data impacts M&A, where data catalogs and master data management can overcome challenges, and how data intelligence can accelerate time to value for M&A transactions.

Key takeaways

• Disconnected data threatens M&A success due to inconsistent information, wasted effort, and a lack of comprehensive insights. 

• Data catalogs form the foundation of an M&A strategy built on data intelligence, visibility, and understanding of data assets across entities. 

• MDM best follows a data catalog to ensure data integration, accuracy, and consistency post-merge for better decision-making and value realization.

Key M&A challenges caused by data fragmentation

Siloed data is synonymous with data fragmentation. The pockets of information housed in disparate systems, data warehouses, and cloud storage that operate independently block the seamless connection and sharing of essential data. 

Few organizations intentionally create these data silos. Instead, they sprout organically over time due to hasty technological expansions, departmental autonomy, maverick IT, and the ease and ubiquity of cloud-based SaaS solutions. The rush to deploy AI innovations on all sides of M&A transactions also contributes to disconnected and untraceable data usage. Even more, conflicting and shifting data management strategies and integration challenges can exacerbate data silos, further disconnecting data from value.

In the context of M&A, data silos hurt both sides of the equation. When entities have data isolated in different systems with varying formats and governing policies, the challenges are compounded. 

How disconnected data undermines M&A success

When merging organizations face data fragmentation, the consequences ripple throughout the integration process. Inconsistent and low-quality data across customers, products, and financials makes creating a unified business view nearly impossible. These discrepancies generate conflicting results, slowing analysis and undermining decision-making confidence.

The financial impact is equally concerning as teams across merging entities manage duplicate or overlapping information. This redundancy inflates storage costs, complicates data maintenance, and diverts critical resources from integration priorities. More troubling still is how these inefficiencies mask true operational costs while distracting from core M&A objectives.

Perhaps most damaging is the strategic blindness that results from incomplete data visibility. Without comprehensive insights into customer behaviors, operational performance, and workforce productivity, potential synergies remain obscured. This creates an "iceberg effect" where numerous opportunities and challenges lurk unseen, sometimes with disastrous consequences.

The ultimate casualty becomes the M&A timeline itself. When workers cannot create unified customer experiences, when customers encounter disruptions and inaccuracies, and when partners find working with the combined entity unnecessarily difficult, the promised benefits of the merger materialize slowly—if at all. These internal and external frustrations directly impact growth potential and could have been avoided with proper data integration planning.

Addressing these data fragmentation challenges requires a structured approach to data management during M&A integration. By developing a comprehensive data strategy before finalizing the deal, organizations can identify potential pitfalls early and implement solutions that preserve both data integrity and business momentum throughout the transition.

Data-driven M&A success: Data catalog first, MDM second

To effectively mitigate the risks disconnected data brings to M&A, acquirers and acquireees require a robust data intelligence strategy. A key decision is sequencing data management tools, technologies, and processes. Those deploying data catalogs before master data management (MDM) create a foundation to accelerate downstream data management success.

A data catalog provides a repository of data assets and related information. Workers can find, understand, trust, and use data appropriately with that information. Data catalogs store metadata that describes data to help users discover the source, context, structure, and purpose of the data, which lets them evaluate its fitness for the purpose at hand. 

For M&A transactions, from due diligence through value realization, a data catalog provides significant benefits such as:

• Faster resource identification: A catalog creates a central repository where decision-makers from both entities can search, discover, and map data assets. It shows sources, owners, experts, and lineage to streamline data consolidation.

• Better quality assessment: A data catalog helps to prioritize high-quality data for integration and identify what can be omitted. It stores compliance and data quality policies, tracks metrics, and surfaces issues requiring remediation before integration.

• Unified governance approach: A centralized repository of regulations and usage policies enables data leaders to align rules and procedures for post-merger compliance. This increases accessibility, encourages collaboration, and sets clear expectations for data management under the newly formed entity.

Beginning with MDM forces organizations to analyze data structures and make assumptions with incomplete information, resulting in frustration and rework. The solid foundation of data intelligence grounded by and within a data catalog is a crucial prerequisite for enabling MDM efforts.

Master data management for post-merger M&A data accuracy

While data catalogs provide a clear view of a data landscape, MDM then ensures data-driven confidence once a merger is underway—and long after. 

MDM ensures that consistent, reliable data is used across an organization, even as that information is processed, combined, and analyzed pre- and post-merger. The crux of MDM is approaching “master” data, such as product, financial, and customer information, as the authoritative source of truth. With sound MDM practices, all teams and applications use consistent, reliable, and trustworthy information. M&A transactions benefit from MDM as data is integrated and business policies and processes are combined from disparate sources.

Furthermore, MDM prevents data duplication by identifying and merging redundant data, so critical data has a single, accurate version. MDM also drives consistency by enforcing data rules so information follows standard formats that reduce errors and misinterpretations.

Case studies: How a data catalog supports smarter M&A

The challenges of disconnected data in M&A aren't just theoretical. Real organizations have successfully navigated complex integrations using data catalogs as their foundation. Their experiences demonstrate how data intelligence becomes a competitive advantage during mergers and acquisitions.

Global science company unifies siloed systems

A global science company that grew through numerous acquisitions faced severe operational inefficiencies due to distributed technology landscapes and siloed ERP systems across divisions. When implementing a Databricks Lakehouse Platform to consolidate enterprise data, they quickly encountered inconsistent data sets, conflicting rules, and data lacking context—leading to distrust in the migrated information.

By deploying Alation as their governance platform, the company:

• Created a unified repository for terminology and business rules

• Made data searchable and discoverable across previously isolated divisions

• Guided users to trusted data sources while connecting them with data owners

• Used the catalog to bridge knowledge gaps through 4,000+ knowledge-sharing articles

"Data governance is the capability that gets people out of their data silos and unlocks enterprise value out of division data," noted a member of their Center of Excellence. With a data catalog establishing the foundation, users no longer needed expertise in every ERP system to derive value from the organization's collective data assets.

Learn more in this white paper: 10 Reasons to Choose Alation for Your Databricks Lakehouse.

CURO Financial Technologies expedites post-merger integration

When CURO Financial Technologies acquired Heights Finance Corporation in 2021, they faced the dual challenge of cataloging legacy data while rapidly integrating Heights' information—all against tight regulatory deadlines. Without proper documentation, the teams struggled with databases spanning nearly 30 years of business evolution.

CURO's Director of Data Governance Will Brantley noted the fundamental problem: "The challenge wasn't that we had nothing to document. The issue was having information in databases dating back to brands that we no longer have."

The implementation of a data catalog allowed CURO to:

• Transform an existing basic data dictionary into a comprehensive catalog using APIs

• Document data sources as they were being built rather than retroactively

• Create a centralized location for terms, acronyms, and definitions that bridged knowledge gaps between the merged companies

• Save significant time during audits and compliance reviews by quickly locating sensitive data

The results extended beyond technical achievements. One new employee at CURO emphasized how the catalog eliminated the overwhelming nature of post-merger onboarding: "I never had to reach out with questions—I'd just go right into Alation."

Realizing the full potential of M&A through data intelligence

Disconnected data remains the hidden obstacle that can derail even the most strategically sound merger or acquisition. As these case studies demonstrate, organizations that prioritize data intelligence through a foundation of data catalogs followed by master data management create the conditions for successful integrations and faster value realization.

By establishing visibility into combined data landscapes, enforcing consistent data governance, and building trust in shared information assets, companies can transform what is typically seen as a merger risk into a competitive advantage. When data flows seamlessly across previously siloed organizations, the true synergies promised in M&A planning can finally materialize—turning data from a liability into the strategic asset that drives post-merger success.

Curious to learn how a data catalog can support your vision for M&A? Book a demo today.