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Council Post: Want To Improve Your MA&D Process? Look To Data As The Foundation

Kevin is the CEO at Syniti, a global leader in enterprise data management.

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Many companies are going through mergers and acquisitions or divesting (MA&D) parts of their business. According to Bain & Company, total deal values reached record highs in 2021 with increasingly complex competition and record valuations. That momentum continues into 2022. Successful MA&D has always had its roots in data, from completing thorough due diligence to harmonizing datasets and realizing cost (and revenue) synergies. The advent of even more available data gives rise to new opportunities for using data and data strategy as part of the MA&D tool set. I doubt anyone would argue that data is a key competitive differentiator that can represent a significant portion of the value of a company, yet many companies still neglect to think about the quality of the data they are acquiring.

To take advantage of the opportunities data brings in MA&D, like realizing those synergies faster, negotiating more advantageous terms or getting better visibility into acquisition targets, you must be thinking about data quality, and you must think about it during the planning phase.

Sorting Through The Data

Determining the compatibility of each organization’s data must be part of any due diligence process. It starts with understanding what data is required to run an acquired business or, for a seller, understanding what data needs to be provisioned and shared. A common misconception about this process is that you’re just moving data from one place to another. In reality, the entire point is to extract value as quickly as possible.

Think of it like moving to a new house. You don’t just move everything; you take inventory of your belongings and decide what will be kept, what you’ll use, what you’ll discard, etc. You’ll think about how you’re going to move the things you’re keeping and where they will go, including whether any of the new rooms will require new furniture or renovations. All of this is critical to the success of that move (i.e., migrating the data).

Deciding to move, or in some cases construct, the data that matters to your business in a strategic way will help you derive value from your transformation efforts faster. Just like with a new house, it doesn’t pay to skimp on your foundation.

Watching What You’re Moving

You also need to focus on ensuring that proprietary data from the seller isn’t shared unless it’s part of the divestiture. The buyer’s concern is that the seller is giving them everything they really need to run the business—and that buyer is typically paying for a transitional service agreement (TSA), in which the seller is paid to run the business until the acquirer can take it over and run it themselves. Taking over a business and integrating it into the new company’s processes effectively impacts the time-to-value that the acquirer expects from making the investment. A slower time to take it over and integrate the business equals a slower realization of the value that drove the acquisition in the first place.

When Data Brings Challenges Versus Opportunities

The more complex the acquiring and selling companies are, the more complex the data will be—not only volume but different types of data, potentially all stored differently, so deduplication or load validation are common issues. Add to that the potential for legal challenges like personal data privacy or competitive sensitivity, and data management becomes more challenging than it first appeared. This is especially true in global integrations or carve-outs that typically take years to sequence across major markets.

Bringing together or separating the back-end systems that run the businesses begins with a transfer of data from one or more systems to a new system. Sometimes, systems are taken over and integrated with the acquirer’s primary systems and processes as a second stage. Combining systems also means reconciling duplicates and standardizing business processes and the data required to support those processes.

Combining two entirely distinct business systems and data languages is hard, as is the process of carving out a piece for sale and integration into a different organization. It’s complicated on a normal day; now think of the compounded pressure of a public MA&D transaction and the mounting demands on both sides to complete the transaction quickly and start adding value.

Bringing Data To The Forefront (Literally)

MA&D can be divided into three phases: preparation, separation/integration and realization. Normally, data management in some form comes up in the separation/integration phase and not that often in the preparation phase. I’d argue that’s at an organization’s own peril.

Consider an example of how data can uncover a potential pitfall before it causes major damage. Company A is keeping one line of business but is divesting another to a semi-competitor, Company B. During the prep phase, it’s revealed that there’s a shared component of raw material inventory across both companies. Who’s responsible for the inventory? It’s an important question because it has very real consequences on supply and inventory management. We often think of divestiture as a clean cut, but it’s very often intertwined below the surface, and the details are messy.

The sooner you dig into the data, the better—versus being literally a day away from execution. That way, you can ask these unforeseen questions that need to be answered to ensure a smooth transaction and realize value as soon as possible for both buyers and sellers.

Making Data Management Part Of The Foundation

Data is critical to every stage of a deal. Having the key goal of realizing time-to-value as quickly as possible means you have to think about data management from the get-go. While quality data brings strategic advantages, bad data or poor data management can cause significant challenges that will slow down your progress to the goal—or tank it all together.

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