Data integration drives successful mergers

Successful M&A transactions don’t fall out of the sky fully formed. Instead, they depend on multiple entities efficiently converging into one, no easy task given the separate people, customers, data, information systems, and processes.

Therefore, one of the items highest on a typical post-merger to-do list should be consolidated reporting. Further, without foresight and effective change management guiding the way, something as crucial as consolidated reporting could slip through the integration cracks.

To avoid such miscues, the parties should focus on creating a framework to lead the post-merger efforts, ideally well before a deal closes. Such a framework should focus on four main areas:

  • Establishing communication channels across teams;
  • Creating and appointing particular people to a steering committee, integration teams, and a project management office;
  • Engaging with experienced third parties to assist and guide the integration;
  • Defining the desired end-state – assigning post-merger integration targets, goals, and relevant metrics.

Creating fast, reliable systems for critical functions like consolidated reporting, identifying and generating operational key performance indicators (KPIs), or staying on top of debt covenants suddenly becomes infinitely more difficult without that framework in place. Fortunately, a sound data integration strategy addresses many, perhaps even most, of these common integration pitfalls.

Key to value-driving efficiencies

It’s far too easy for a deal to fail without a data integration game plan because of disparate data and disconnected systems. However, choosing the right approach to data integration depends on several variables, including available resources, timelines, and complexity, to name just a few. Still, most transactions are best served by one or a combination of three solutions: in-house teams, automation tools, and outside specialists.

In-house teams

Thanks to the self-sufficiency involved and potential implementation cost savings, a “do it yourself” approach to data integration is usually appealing. However, such a strategy requires specific in-house expertise to identify the right tools, implement them, and then integrate the tools into the combined organization’s processes. Along the way, entities risk losing key people and critical insights when timelines compress, patience thins, and stress levels rise.

Automation tools

Assuming the parties identify and implement the best automation tools for their needs, the result is scalable, transparent, and reliable. As importantly, automation provides real-time business intelligence to leadership, usually through an app or web-based data dashboard on a mobile device.

Outside specialists

Many organizations now turn to specialists to identify, implement, and maintain the proper data integration tools for specific needs and goals. Business leaders don’t have to worry about choosing the wrong tools or relying on in-house teams for critical roles.

Instead, the right specialists familiarize themselves with even the most complex data environments and particular integration needs and establish a roadmap to get to that ideal future state. Of course, implementation costs with a third party could be higher than a “do it yourself” approach. Any decision should include budgetary restraints, in-house capabilities, and operational complexities.

However, an effective PMI game plan isn’t simply about hitting the ground running. It should also focus on long-term strategizing, including using the best data management tools and finance transformation initiatives for the combined entity – ERP, CRM, and robotic process automation, to name three.


Adapted from: “Data Integration Drives Successful Mergers”, by Stacy Galligan, managing director of business advisory firm Embark, published on CFO News on 16 May 2022.

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