Welcome to the evolution: data analytics in M&A

December 2019  |  COVER STORY  |  MERGERS & ACQUISITIONS

Financier Worldwide Magazine

December 2019 Issue

Data provides much of the glue that connects people, processes and technology. Such adhesion is particularly important in an M&A context, where shrewd data usage is key to maximising shareholder value.

In an era of profound technological advancement, the M&A landscape is likewise changing rapidly, with dealmakers increasingly utilising the likes of online data rooms, corporate search services, information databases and advanced analytics – all of which have helped boost the speed and efficiency of deals.

According to the 2018 KPMG survey report ‘Data & Analytics in M&A: A new weapon in the modern deal maker’s armoury’, data analytics are being deployed in many ways across the M&A lifecycle, from initial identification and screening of opportunities, through to enhanced due diligence in-deal and ongoing value realisation post-deal.

“Analytical tools can now transform massive volumes of raw transactional data into meaningful

financial and operational insights in record time,” notes the report. This, in turn, has changed the way deal teams operate. Previously, a large amount of time was spent collating multiple summarised data sources before analysis could begin – a scenario often compounded by challenges around data completeness and integrity. Dealmakers now spend this time analysing outputs and having in-depth discussions with management, supported by factual analysis.

“Once an M&A opportunity has been identified, data analytics allows potential acquirers to drill down into the semantics and perform much of the due diligence and discovery, which can involve interviews and transcripts of a large volume of confidential documents,” says Sing Koo, chief strategic investment officer at SiteFocus Inc. “Often, a failed M&A engagement can be very costly to parties. For example, a failed deal between Anadarko and Chevron resulted in a substantial walk-away fee in the billions.

“Analytics offers the ability of ‘scale’ in terms of acquiring intelligence about the parties in a deal,” he continues. “The ability to overcome the limitation of ‘bounded rationality’ is one major advantage of using data analytics in the M&A process, where the limitation of time and labour can prevent full discovery of a hidden variable.”

Testifying to this is 55 percent of respondents to the KPMG report who stated that data analytics was a critical component of their due diligence, while almost 70 percent said they received raw data from a target and used their own company to analyse that data. Another survey report, Intralink’s 2018 ‘Data-Driven Dealmaking: Impact of Data and Analytics on the M&A Process’, reveals that the primary goal in using data analytics for 55 percent of respondents was to determine value, synergies and risks. Additionally, 22 percent stated that analytics are used in M&A to reduce the reliance on intuition to support a value hypothesis with fact-based insights.

“Data analytics can help accelerate the delivery of benefits during integration, as well as identify additional opportunities for synergies through applying data mining techniques to gain further insights,” adds Mike Creasey, client director at Moorhouse. “Use of these technologies can provide companies with a competitive advantage when considering an acquisition. It enables them to gain a better understanding of the target company, the markets they operate in and the quality of their customer base.

“Being able to utilise the technologies available during the M&A lifecycle will enable those companies that embrace them to drive increased value from their acquisitions,” he continues. “Accessing the data available will also enable companies to make more informed decisions around potential acquisitions.”

In the experience of Andy Moseby, a partner at Kemp Little, technology can help buyers select target companies, provide market insight, assist with valuation modelling and facilitate efficient due diligence. “Rather than a revolution in M&A, this is evolution, as buyers and sellers become more comfortable with their advisers using algorithms to analyse key issues,” he believes. “The real revolution actually comes when buyers look to utilise data analytics tools in their integration planning and execution, which is often under-resourced or overlooked during a deal process.”

Whether a revolution or an evolution, the use of data analytics in M&A is enabling smarter, faster decisions throughout the M&A lifecycle. In effect, the traditional approach of relying on the likes of spreadsheets to analyse data is quickly becoming a relic of the past.

Capabilities, limitations and compliance

When drilling down into the respective pros and cons of bringing data analytics – which encompasses artificial intelligence (AI), machine learning (ML) and other technologies – into the M&A space, efficiency opportunities and potential cost savings become clear. That said, such technologies do raise security and regulatory compliance concerns.

According to Deloitte, data analytics in M&A is all about asking – and answering – smarter questions throughout the M&A lifecycle. What is the true source of a company’s growth? How successful is this company in retaining its customer base? Where are margin trends negatively impacted by specific products, locations or customers? What is the specific net impact of decisions reflected in the purchase agreement? Which risks are likely to be encountered in doing the deal? Which employees and customers should be covered by non-compete agreements? Where should renegotiations with customers or suppliers be pursued to quickly achieve cost savings or revenue improvements? How are customers responding to the change in ownership? Has there been a change in risk profile as a result of the transaction? What are the results of changes made to the business after the closing of the deal?

“Applying data analytics enables organisations to be more efficient with their analysis, as well as identify additional opportunities for synergies that would otherwise have been overlooked,” says Mr Creasey. “The ability to dive deeper in the data behind a few strong sales quarters can shine light on the reality of the business. While there are limitations on the type and depth of data that can be shared during a due diligence process, the opportunities to apply these techniques once a company has taken legal ownership are significant.”

However, while the use of more advanced, integrated and dynamic analytical tools means companies can obtain big-picture insights and microscopic levels of detail, such oversight also comes with greater regulatory compliance obligations. Indeed, the likes of the 2018 EU General Data Protection Regulation (GDPR), with its potential penalties up to the greater of €20m or 4 percent of total worldwide annual turnover for the prior financial year, and the imminent arrival of the California Consumer Privacy Act (CCPA) – effective as of 1 January 2020 – are doing much to complicate compliance.

“Compliance is becoming tougher for companies, particularly in respect of data regulation,” asserts Mr Moseby. “This means compliance risk is increasing and corporate lawyers are being asked to provide increasingly technical analysis of an increasing amount of data in ever-decreasing amounts of time. Companies invest in data analysis tools because they gain insight into highly technical issues, combined with an efficient way of undertaking important but process-heavy grunt work.”

Data analytics-led transactions

Testifying to the effectiveness of data analytics in M&A is the number of transactions that have been driven by the science in recent years. Moreover, as well as upping their use of data analytics in order to actualise an acquisition, companies are also seeking new data sources to feed their analytics capabilities.

“In a recent merger, a retail bank was concerned about the risk of losing customers during a period of uncertainty following completion of a transaction,” relates Mr Creasey. “Using data analytics tools, the bank developed models to identify the underlying drivers of churn. This then enabled it to design specific retention strategies for those customers most likely to churn. As a result of this detailed analysis, the bank was able to move quickly with targeted initiatives which led to a 20 percent reduction in the churn rate.”

That said, for those companies that prefer to maintain a traditional approach to M&A in lieu of utilising analytics technologies, the risks are substantial. “Companies need to utilise richer and more detailed data sets to drive their analysis and increase confidence levels when making a transaction,” asserts Mr Creasey. “Failure to make use of these technologies increases the risk of making the wrong decision on an acquisition, as well as losing value post completion due to risks and issues that could have been mitigated through more detailed analysis.”

Clearly, then, integrating data analytics into an existing organisational structure is key. “Any M&A transaction which involves a large data room, a difference in expectations in valuation between the buyer and seller, and a large acquirer that needs to integrate the target quickly post-close can benefit from the input of sophisticated reasoning and data manipulation technology,” suggests Mr Moseby. “Understanding long-term trends or getting to microscopic levels of detail to properly assess risks typically takes a lot of analyst hours. Data analytics can provide this quickly and comparatively cheaply.”

In terms of partnering, where vendors that need to beef up their data analysis capabilities acquire another company’s data expertise (a relatively new phenomenon known as ‘acqui-hiring’), activity is booming. Among the key transactions in this space in recent times is Salesforce’s June 2019 acquisition of data visualisation specialist Tableau for $15.7bn, which came hot on the heels of Google’s purchase of data analytics company Looker for $2.6bn.

Confidence with caveats

While data analytics enables dealmakers to answer challenging questions they otherwise could not, as well as gain a greater understanding of a target’s markets and the quality of its customer base, their use should be tempered with caution, according to some.

“Understand the current limitations of the tools involved, and do not expect the use of a software tool to give you all the answers during the M&A process,” advises Mr Moseby. “When used to supplement, rather than supplant, the decision making of the board and the expertise of its advisers, data analytics can make an extremely powerful impact.”

An additional cause for concern is that while companies typically use analytics for M&A strategy development and screening targets, there is still a reluctance to embrace them during the due diligence and integration planning phases.

“Yet, there is real scope to drive improvements in M&A decision making through the use of these techniques,” contends Mr Moseby. “For example, HR data can be used to gauge the overall health of a business. Analysing the data available to understand roles and responsibilities, average tenure and salaries in each function, turnover rates, as well as employee satisfaction rates, can help to accelerate integration planning post-deal completion and focus on the priority areas, including retention of key talent.”

Shaping the future

Constantly evolving, data analytics is increasingly a key component of the M&A lifecycle, with a number of new technologies, such as Internet of Things (IoT) analytics, augmented analytics and DataOps analytics, likely to take centre stage.

“We expect to see an increased ability to process and analyse unstructured data with the advancement of advanced analytics,” opines Mr Creasey. “This means that previously unusable and unstructured datasets, such as those defining corporate culture or other harder to grasp financial data, will become valuable for use across the whole deal lifecycle.

“The use of data mining techniques and being able to analyse data from different sources will be key in analysing a company and its market,” he continues. “Companies will need to embrace these technologies in order to stay competitive when considering acquisitions, otherwise they run the risk of not being able to maximise value from their transactions.”

Although evolving, data analytics is still relatively nanscent technology. “We are still in the early days,” believes Mr Moseby. “Most of the AI available today is essentially enhanced database search tools. But one does not need to look too far into the future to see how general AI, which can engage in higher-order thinking involving creativity and innovation, can help businesses identify target companies and ensure that the integration of those business is undertaken in a manner which maximises the chances of an acquisition being a success.”

Slowly but surely, data analytics is transforming the M&A landscape. Taking its place among the tools, templates and processes that make up an M&A playbook, data analytics is now a key weapon in the dealmaker’s armoury.

© Financier Worldwide

BY

Fraser Tennant