Driving Successful M&A Through Analytics

It just so happens (and I tell myself that its not down to anything i’ve done) that I have worked with many clients who are, or have been, going through some form of M&A. The process provides unique challenges throughout the organisations involved, from the culture and Target Operating Model (TOM) to IT consolidation and service, there is little which isn’t affected by M&A.

What is often overlooked, or certainly deprioritised, is the progression and consolidation of data. Which seems bizarre in the current climate, where all except the most militant of tradionalists would say that data is now one of the most important areas for operational efficiency and competetive advantage. In my experience organisations actually risk regressing in their use of data and analytics to drive business insights, especially with the current pace of progression in technology in this area. Whilst your business spends years trying to integrate an out-of-date architecture, are your competitors sitting still and waiting for you to finish the process?

So, what drives M&A?

Let’s start by being honest about what M&A is before the deal is signed – ideas and assumptions. That’s not a criticism, it couldn’t be anything else.

What the idea and assumptions are based on however, is identified opportunities. That might be an opportunity to expand the organisations footprint into new markets, buy a capability that doesn’t currently exist internally or even invest capital that is currently burning a hole in the corporate account. There will be some validation in due dilligence, but until the companies actually merge there are few absolute certainties.

Objective to Subjective Process

M&A is a process of contrast. At its inception and definition phase it exists in a very objective state;

• What are the benefits?
• What are the risks?
• How quickly could we realise ROI?
• Will this eventually drive competetive advantage?

But then the deal is signed, and the realisation of the idea has to begin. In my experience, the process then shifts to a very subjective approach, and why wouldn’t it? Integrating teams, changing job roles and trying to create a unified culture without compromising the values each organisation worked for is a delicate, politically charged topic that takes time to define. The challenge it presents is the stagnation of growth, progression and innovation during that time.

The Objectivity of Data

As I mentioned earlier in this blog, data and architecture integration is usually an afterthought of the TOM and organisational structure, yet you would argue that an integrated team would need integrated business insights to be effective?

One characteristic data does have is its objectivity. Does data need legal consultation for a role change? No. Does data have statutory employment rights that need to be followed as part of a teams integration? Haven’t heard of any. What data does have, however, is the potential to validate the assumptions that drove the M&A in the first place, and, actually find new opportunities to make the process more successful. Why does the initial idea have the be the limit of success?

Here is a challenger for the sceptic. If an organisation had not gone through M&A, and decided to drive organic growth, development or reorganisation… would it do so without evidenced approach and benefits understood? Yet so many organisations drive M&A integration blindly, without the data set to inform the best approach and benefits it could create. That’s not smart business.

Driving Successful M&A Through Analytics and Innovation

When is M&A deemed to have been successful?

• At point of signing the deal?
• When both organisations physically integrate?
• Or when the objectives and goals that drove the M&A are realised?

One of the first actions that should be undertaken after the deal is finalised is validation of the opportunity, and quickly treating data as a group asset is one way to achieve that. The role of the Chief Data Officer is becoming more and more prominent in modern business, and its application in this scenario couldn’t be more appropriate. Technology now enables the quick and agile integration of data sets which can realise quick value without uprooting a whole architecture. BIG DATA and advanced analytics platforms can be stood up quickly, and work with each organisations data sets to drive insights that inform the integration and measure the success of the initial M&A objectives. They can also work around the inevitable differences in data modelling and design that become the challenge of most architects undertaking full integration.

Key Takeaways

My final key points in this subject are;

• The realisation of success depends on the flexibility of the approach to integration
• Treat data as an objective area of integration that can deliver quick wins as a Group asset
• Use data and evidence to drive validation of the original idea and successful integration
• Proactivity in addressing data challenges can be turned into an opportunity that drives the success of M&A