In theory, a merger and acquisition (M&A) deal brings two businesses together with shared goals and values. The reality is rarely so perfect – as you’ll know if you’ve ever been involved in one or are currently going through the process. Despite all of the due diligence that takes place in the run-up to signing on the dotted line, it’s after the ink has dried that the real work begins: integration.
You’re bringing together two cultures, two groups of people, two sets of systems, technologies and processes, and two very different data landscapes – and it’s here where, according to research, one in every two mergers goes awry.
No matter how much preparation went into the pre merger and acquisition process, it’s impossible to eradicate every headache as you roll out your integration. Yet while Data Management is often one of these headaches, it needn’t be – and if you get your post merger and acquisition Data Management right, it can even help to streamline other aspects of the process.
Here, we share our insight into how to avoid the headache and make Data Management a positive force after M&A – but first things first. What is M&A integration, and why is data such an important part of it?
What is Merger & Acquisition integration?
Post merger and acquisition Integration (or PMI as it’s known) is the process of bringing two merged businesses together in practical, not just official, terms. That means enabling both businesses to share processes, systems, culture and vision, not just a business name or title of ownership.
The main objective of PMI is to make sure the merged company will run as efficiently and profitably as possible – and in today’s digitally driven world, data is critical to this. You can’t combine all of the other parts of the business successfully if your data remains separate – how can you ever see the big picture or engage with your newly expanded customer base if there are multiple versions of the truth?
Does pre-M&A due diligence improve Data Quality during integration?
Yes and no. Yes, due diligence does include Data Quality exercises. No, it doesn’t necessarily improve overall Data Quality, especially not in the long term.
When it comes to merger and acquisitions, everyone involved in the undertaking understands the importance of due diligence, and how necessary it is to get as true and accurate an image of the business (its financial and commercial health) as possible prior to signing the deal. Yet it’s a reporting first, not data first, angle. Quality exercises are often focused on specific data sets, not on how that data is managed and whether it will still present the truth in the future.
Then there’s the fact that regardless of how good both parties’ Data Quality is before the deal, there is still the reality of merging that data together and extracting a single, combined version of the truth from it after.
Why is Data Integration important for a successful Merger & Acquisition?
A single, merged business should have a single version of the truth, whether it’s on customers, assets, performance, or any other aspect of the company and its operations. This single truth is the only thing that can give an accurate insight into the merged business as it grows and develops, and reliably inform decision-making moving forward.
As an example, let’s look at the recent surge in merger and acquisitions in the energy sector, following the collapse and customer redistribution of several suppliers and the purchase of several other ailing firms. Each merger has brought two different sets of customer data into one organization, in most instances, very quickly. How can those organisations be sure that they are offering the same experience to both sets of customers if they don’t have a single view? How can they understand their customer base as a whole and not two halves? When you consider that many of those customers didn’t choose to move suppliers, the new company is already on the back foot: they need to quickly and effectively integrate that customer if they want to succeed in demonstrating their value and make good decisions moving forward.
How can you tackle post-Merger & Acquisition Data Management successfully?
Data can be one of the most intimidating aspects of post-merger and acquisition reality, particularly as businesses are collecting more data than they ever have before and using it for increasingly critical operations within the business. As a result, the temptation is to avoid the challenge, rather than risk making a mistake. Yet as the example above demonstrates, there is more risk in ignoring Data Integration than tackling it head-on. Eradicating silos and creating a single data view with MDM has to be a priority if you want to rely on your business’ data following a merger.
Here are our tips for avoiding a Data Management headache post-M&A.
Do act fast and address data integration quickly
Without being too blunt, burying your head in the sand when it comes to post-merger and acquisition Data Integration will only worsen any data problems you encounter. As with any data silo, the longer it is left, the more entrenched it becomes. If you adopt MDM, it doesn’t have to be a long, drawn-out process and can start delivering value quickly, even in more complicated cases like M&A.
Don’t wait for all systems to be integrated before you address Data Management
Technology is only one part of Data Management: successful MDM is about people and processes, as well as platforms. Identify critical data, start defining Data Quality rules, and introduce shared data definitions. You can also start looking at silos within each business and the root causes that are creating them, to simplify the integration process later on.
Do use Data Governance to create a shared Data Culture
Mergers and acquisitions can be a culture clash, even when the two businesses seem like a perfect fit. Everyone has different ways of doing things, and when it comes to data, these habits can be particularly hard to break. You need to create one, unified Data Culture across the new business – and Data Governance is the first step to doing it.
Don’t let data silos fester, no matter how small
Data Governance can also help you to tackle database protectionism: the more that people can see the benefits that new Data Processes and platforms bring, the more likely they are to follow the rules – and think twice about siloing data for their own objectives in future.
Do identify a shared goal for data before you commit to technology
Yes, you need to act fast to bring merged business’ data together – but do you know what you want to achieve at the end of it? Don’t lose sight of the merger and acquisition’s purpose in the rush to integrate your data: it will influence the technology you choose to manage it. Work with a Data Partner to list your goals and evaluate the software on the market against them.
How can organisations introduce MDM as part of their Merger & Acquisition?
The healthcare, technology, financial services, and retail sectors are no stranger to M&A activity, and when economic conditions are poor mergers and acquisitions intensify. As we have seen over the past two years across the energy, utilities and resources (EU&R) industry significantly, when many small and medium-sized businesses struggle to compete in a marketplace controlled by major players, merger and acquisition activity is rife.
The ability to manage data sustainably as the business portfolio evolves is a core advantage of MDM in helping to underpin the commercial, strategic and operational success of M&As. If you’re navigating a merger, or an acquisition, incorporating MDM into your merger and acquisitionData Strategy will help you establish a single version of the truth.
To find out more about the role of MDM in the energy and renewables sector, and how it is an important business enabler of everything from decision-making to post-merger innovation, download our guide: Power up with MDM: Fuel your data strategy with high-quality master data.