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Data Management: The Foundation for Successful M&A Activity

Posted on by darion

Author: Andy Baillie, below, Vice President, UK & Ireland, Master Data Management (MDM) specialist Semarchy

Merger and acquisition (M&A) activity is expected to increase in the rest of 2024 – and with that, there is a renewed focus on effective data management strategies. And for good reason. Because while M&A offers huge growth opportunities, as much as 70-90% of deals fail, and skipping data management is often a key factor.

Proper data management can mitigate these risks and increase the chances of M&A success. Not surprisingly, the opposite is also true: poor post-merger data management planning can have serious and far-reaching consequences. In particular, combining different data sources without proper planning can lead to fragmentation, causing inconsistencies, duplication, and access issues across the enterprise. As a result, it will be much more difficult for you to make and execute important decisions.

Risks of poor planning

I have already mentioned several risks that poor data management poses in the context of post-merger integration – from fragmentation to an increased risk of unclear thinking and ineffective actions.

But when you look at it holistically, there are a number of risks to avoid. Take, for example, the idea of ​​data being lost or corrupted during a migration. This will certainly impact how you manage your business operations – both in the short term and likely in the long term as well. Just imagine losing important customer data or financial data during a merger to understand how serious this could be for your newly merged company.

Much of this also falls under regulatory compliance, especially when it comes to personally identifiable information (PII). Mishandling it – or losing it altogether, as I mentioned – can result in hefty fines, reputational damage and, again, long-term consequences.

There are also smaller, but no less important, considerations. If there are system incompatibilities, for example, you will encounter operational roadblocks and reduced productivity – as well as frustrated teams of employees. You also risk losing the benefits of the merger if there are delays in data integration.

The result? Each of these risks can lead to expensive, reactive fixes. However, by taking a proactive approach and addressing these potential data issues as part of your planning, your chances of a smooth, successful merge are much greater.

A Framework for Effective Data Management in Mergers and Acquisitions

To address these challenges, a comprehensive approach to data governance and master data management (MDM) must be developed. Here is a basic framework for how to do it, step by step.

  1. Build a Transition Team

Establish a team early in the process, including members from legal, IT, finance, tax, and HR, to provide comprehensive oversight of all aspects of data management. This team should be responsible for promoting data-driven practices throughout the M&A process.

  1. Develop a data management strategy

Create a detailed strategy and framework for coherent governance of data assets across the combined enterprise. This includes establishing clear data governance policies, procedures, and responsibilities, and developing a data catalog and inventory of all data assets and technical infrastructure to provide a clearer overall picture.

  1. Establish solid MDM and data integration strategies

Align your MDM strategy with your business goals and the value of each data asset. Consider different migration methods—such as big bang, phased, or parallel—depending on your specific needs and risk tolerance. Using MDM solutions, you can create a single, reliable source of truth for critical data domains such as customer, employee, and product data, improving decision-making and data quality.

  1. Conduct due diligence and risk assessment

You need a clear understanding of data laws and regulations in all jurisdictions to design a tight governance, risk and compliance strategy and prevent any potential damage to your company’s reputation. Assess the scope, ownership and portability of the acquired data and secure data privacy and security guarantees from the vendor as a safety net against any liabilities that have not been disclosed.

  1. Prioritize data quality and compliance

Data integrity must be maintained throughout the integration process and beyond, so appropriate data quality metrics based on system requirements must be in place. This ongoing vigilance is essential to ensuring data reliability for the new combined enterprise. Compliance with data protection regulations such as GDPR must also be ensured, while maintaining customer trust through proper management of personal data. This means protecting sensitive information through the use of appropriate security measures, processes, and documentation.

  1. Implement change management and continuous improvement

Clear communication, comprehensive training, and ongoing support for staff are key. You should also regularly review your data management strategy and conduct post-merger assessments to improve operations and prepare for future M&A engagements.

Real-world application

The value of solid data management and MDM in M&A is exemplified by Dentsu International, a global digital marketing media and communications company. Faced with frequent M&A activity, Dentsu implemented a comprehensive MDM solution to consolidate data across its complex, multi-brand environment.

By leveraging an integrated data platform to manage data across local, regional and global systems, Dentsu was able to create a single source of truth for customer, supplier and reference data. The benefits of this were seen across the business, including streamlining operations, improving data quality and improving decision-making, demonstrating the importance of comprehensive data management and strategy in M&A scenarios.

The Path to Merger & Acquisition Success

Effective data management is critical to M&A success, impacting operational efficiency and compliance. As we have seen, prioritizing data management reduces risk and accelerates the realization of synergies.

A structured approach can reveal hidden information, leading to innovation and competitive advantage, and help make critical decisions for the business post-merger.

Organizations that embrace data governance principles are better positioned to create value, adapt to market changes, and respond to customer needs. As M&A activity increases, companies that prioritize data governance will turn challenges into opportunities for growth and innovation.