Putting data governance at the heart of M&A strategy

Andy Baillie at Semarchy explains that effective data governance is crucial for driving value in mergers and acquisitions

Despite offering significant growth opportunities, a staggering 70-90% of mergers and acquisitions (M&A) deals fall short, often because data governance is overlooked. Proper data management can have a decisive impact on reducing these risks.

A key challenge in these transactions is merging complex data systems, which requires careful planning and execution to avoid disruptions and maximise value. That’s why a comprehensive approach to data governance and Master Data Management (MDM) is crucial.

Post-merger data governance planning

When it comes to post-merger integration, failing to plan is like planning to fail. Merging diverse data sources can lead to fragmentation, causing inconsistencies, duplication, and access issues across the organisation. This can severely impact your ability to make informed decisions and operate efficiently.

Regulatory compliance, especially with sensitive data like personally identifiable information (PII), is critical — mishandling this data can result in hefty penalties and damage to your reputation. In today’s data-driven world, maintaining trust amongst employees, customers, and other stakeholders is paramount, and a single misstep in data handling can have long-lasting consequences.

Poor data migration practices may also lead to loss or corruption of critical data, affecting your business operations and decision-making. Imagine losing vital customer records or financial data during the merger process — it could be catastrophic for your newly combined organisation.

System incompatibilities can cause operational hiccups, reduce productivity, and frustrate employees. When staff can’t access the information they need or systems don’t communicate effectively, it can lead to inefficiencies and errors that undermine the very synergies you’re aiming to achieve through the merger.

What’s more, delays in data integration often extend timelines, postponing the benefits you expect from the merger. The longer it takes to fully integrate your data systems, the longer you’ll wait to see the full value of your M&A activity.

It’s worth noting that addressing these data issues after the fact is usually more expensive than planning ahead. Reactive data management can lead to costly fixes, lost opportunities, and potential compliance issues that could have been avoided with proper foresight.

A data governance framework for M&A

To ensure solid data management during the M&A process, it’s wise to set up a transition team early on. This team should include members from legal, IT, finance, tax, and HR to provide comprehensive oversight and cover all necessary data governance aspects.

The transition team and other stakeholders should promote data-driven practices by considering the following:

1. Data governance strategy 

Develop a detailed data governance strategy and framework to manage data assets consistently across the merged entity. This isn’t just about technology — it’s about establishing clear policies, procedures, and responsibilities for data management.

Underpinning this should be a comprehensive data catalogue and inventory of all data assets and tech infrastructure to give you a clear picture of available resources, highlighting any redundancies and areas needing attention. This step is crucial for understanding what you’re working with and identifying potential integration challenges early on.

2. Due diligence and risk assessment 

Conduct thorough due diligence and risk assessment. This includes understanding data-related laws and regulations in all jurisdictions involved to inform your compliance strategy and prevent potential penalties or reputational harm.

It’s also essential to evaluate the scope, ownership, and transferability of acquired data. Are there any limitations on data use or transfer? Securing data privacy and security warranties from the seller can provide a safety net against undisclosed liabilities and aid in cooperative data handling post-closure.

3. Master Data Management and data integration 

Put in place effective Master Data Management (MDM) and data integration strategies. Decisions on data, applications, and device migration should reflect each data asset’s business goals and value. This might involve choosing between methods like big bang, phased, or parallel migration, depending on your specific needs and risk tolerance.

Using MDM solutions helps create a single, reliable source of truth for critical data domains, improving decision-making and data quality. This is particularly important when merging organisations with different data structures and definitions.

4. Data quality and compliance 

Set up relevant data quality metrics based on system requirements to monitor and maintain data quality throughout the integration process and beyond. This ongoing monitoring is crucial for maintaining the integrity of your data assets and ensuring that the merged organisation can rely on its data for critical business decisions.

Properly manage the PII and other sensitive data in both merging entities to ensure compliance with data protection regulations, such as GDPR, while retaining customer trust. This involves implementing appropriate safeguards, processes, and documentation to protect sensitive information.

5. Change management and continuous improvement 

Implement effective change management and continuous improvement processes. A strong strategy, including clear communication, ample training, and ongoing support, helps staff navigate new data governance systems and practices effectively.

Regular reviews of data management strategies and post-merger assessments contribute to refining ongoing operations and effectively preparing for future M&A engagements. Remember, data governance isn’t a one-time effort — it’s an ongoing process that requires continuous attention and improvement.

The value of Master Data Management

The transition team should prioritise data governance and MDM throughout the M&A process to realise the full value of the merged assets. Let’s look at a real-world example to illustrate this point.

M&A happens frequently within Dentsu International, a global media and digital marketing communications company. The firm used a robust MDM solution to effectively consolidate data in its complex, multi-brand environment, offering a single source of truth for customers, suppliers, and reference data.

Dentsu’s approach involved using an Intelligent Data Hub to manage the many systems containing disparate data across various local, regional, and global systems. This strategy allowed the company to engage business stakeholders and improve business processes, showing the importance of a comprehensive data management, quality, enrichment, and governance solution in M&A scenarios.

By implementing this solution, Dentsu was able to streamline its operations, improve data quality, and enhance decision-making across their newly merged organisation. 

Pursuing M&A success

Effective data governance is vital for M&A success, influencing everything from operational efficiency to regulatory compliance. By prioritising data management from the start, you’ll have a better chance of success. Following best practices helps reduce risks and speeds up the realisation of synergies.

Using a structured approach to data governance can turn potential hurdles into opportunities for improvement. For instance, the process of consolidating data systems might reveal insights about customer behaviour or operational inefficiencies that weren’t visible before.

By putting data management first, the merged entity sets itself up for long-term success, creating a solid foundation for data-driven decision-making and innovation to gain an edge over competitors. This could mean faster product development, more personalised customer experiences, or more efficient supply chain management — all powered by high-quality, well-governed data.

Andy Baillie is VP, UK and Ireland at MDM specialists Semarchy

Main image courtesy of iStockPhoto.com and champpixs