Mergers and acquisitions are difficult to pull off, but they can impress when the right strategy is applied. And analyzing your data almost always helps with the right strategy.

In the first eight months of 2021, publicly announced M&A activities were valued at more than $3.6 trillion globally and $1.8 trillion in the US, according to Dealogic. Both numbers are the highest since 1995 when the data provider began its tracking.

But the challenges that come with these types of strategic maneuvers are nothing to scoff at. The acquired companies in these situations usually have vastly different marketing and sales processes, different technologies, different data, and a different approach to workplace culture. Developing harmony between the organizations involved in M&A activity is a delicate process. Often, the first step is aligning the way you collect and analyze data.

Founder of Butterfly Data, Sara Boltman, has learned many lessons as head of the data management consulting firm when it comes to this delicate balancing act.

Starting from scratch? Establish a baseline

Butterfly Data leans on its data science and data management experts to help companies achieve their digital transformation goals and solve M&A challenges.

When a large multi-line insurer acquired two small property and casualty providers, Butterfly helped develop a cross-sell renewal campaign. Boltman says the insurer wanted to bundle home and car insurance offerings and use various communication channels to get the message out to customers.

Unfortunately, the large insurer did little to align the separate data warehouses during its acquisition spree. Insurers' data was siloed and rarely updated when subscribers changed address, marital or living status. And the lack of a quality audit process prevented accurate communication from going to the right subscribers.

The data and process in place were so bad that home subscribers at one point received random auto-renewals – a costly mistake given they spent $1 per subscriber to send each incorrect letter, then a corrected letter, followed by an apology mail.

"I think improving communication, quality audit processes, and breaking down some of those silos was probably our biggest challenge and biggest achievement," said Boltman.

As a best practice, organizations with disparate data should start by mapping out the data pipelines for every process in their business. You can't properly execute a strategy until then.

Don't re-invent past errors

Communicating the technical problems to senior stakeholders behind M&As is crucial. In the example above, the SAS partner started by consolidating data to get a single version of the truth for each customer.

Another Butterfly project involved a large credit union acquiring a smaller credit union that retained two reporting and forecasting teams, each using different business processes and tools. The large firm with a more advanced analytics modeling practice needed to consolidate, harmonize, and deliver their forecast by the fifth of each month. The smaller of the firms relied on poorly maintained Excel spreadsheets with models developed by an author who was no longer with the company.

Legacy processes aren't always well-documented, and no one wants to waste time deciphering past errors. Integration teams should lock in on the obvious obstacles and avoid having a single person holding all the keys to the kingdom. Too much organizational knowledge attached to one person can put the entire organization at risk.

"It's unacceptable when you're running a business that's accountable to regulators," Boltman said.

Don't underestimate resistance to change

Change is necessary, but pushback should always be expected. And it's understandable. People have feelings and when changes out of their control impact them directly, they'll let you know about it. Communicate effectively with stakeholders and help them understand the importance of data and model transparency.

This step can often be more of a challenge to overcome than any technical hurdle associated with M&A, according to Boltman.

Monthly meetings with all stakeholders to review data quality and accuracy will help keep everyone aligned. Communicating successes and key achievements will help keep the momentum going.

The results are worth it

When you stay focused on consolidating and cleaning data – and using modern analytics practices, the results are almost always worth it. Consider these improvements.

In the case of the large insurer, personalized and proactive communication delivered through their preferred channels led to double-digit improvement in customer retention.

The forecast process for the credit union improved from five days to two days allowing for in-depth analysis and better use of computing resources. Analysts were able to spend their time performing actual forecasting.

"It's the people on the process side that makes all the difference," Boltman noted.

Know your limits

Good ideas are contagious but don't stretch yourself thin. Lay a strong foundation so if a larger consultancy does come in to continue the integration work, there's no backtracking.