How data analytics is transforming PE dealmaking
As businesses gear themselves for a digital future, the use of data and analytics in private equity transactions is gathering pace.
Technology-driven data analytics is transforming the merger and acquisition (M&A) process for private equity (PE) firms. Insights gained from data can help identify targets, confirm assessments of financial conditions and predict business trends. But it can also provide a window into potential acquisition targets and assist in the execution, speed and integration of deals.
Data analytics used in transactions, “transaction analytics”, uses company, target and third- party data, along with statistical algorithms and quantitative analysis to drive better insight and quicker decision-making for mergers, acquisitions and divestitures. From a due diligence perspective, leveraging analytics can help to identify issues more quickly, focus the due diligence process and help buyers and sellers close a deal faster.
“Transaction analytics is transforming the deal process by making it a data-driven process from conception to completion,” explains Malinda Gentry, US Transaction Analytics Practice Leader, EY. “[Transaction analytics] starts the beginning of that transaction, leveraging corporate data, buyer data, seller data, third-party data, in order to tell a story. And every step of that story is based on data.”
In EY’s most recent Global Corporate Divestment Study, 46% of PE executives say that availability of sufficient granular data was the most important factor in staying in an acquisition process. Forty-four percent indicate that a lack of confidence in information is the most significant factor that causes a PE firm to reduce its offer or walk away from a deal. The survey also found that 49% believe access to meaningful data is the biggest portfolio review challenge.
Nearly half of the respondents say that access to accurate, comprehensible data is a significant portfolio review challenge, whereas 81% of respondents say that poor-quality data makes it difficult to use analytics effectively.
Building on solid ground
PE activity set records last year, with funds raising around US$468b – the highest annual amount since a record amount of US$557b in 2008. While we’ve seen a drop-off in activity this year, dealmakers predict an uptick in activity for the second half of 2016 and into the beginning of 2017.
EY’s latest global technology M&A update, Global technology M&A report: 2Q16 final look, found PE deals hit a record deal value in the second quarter: US$25.7b in disclosed-value tech deals by PE buyers topped previous records by US$85m. And with 95 deals, it’s the second-highest-volume PE quarter, falling just shy of the record 99 deals for third quarter 2010.
Significantly, seven of the 10 deal-driving trends were led by big data analytics, which was up 82% in year-over-year (YOY) value and 72% in YOY volume.
Jeff Liu, EY Global Technology Industry Leader, Transaction Advisory Services, says: "Digital disruption is not standing still for global economic uncertainty and neither is global technology M&A.”
"Big data analytics is a perfect example as tech and non-tech companies alike seek new data sources to feed their analytics capabilities, especially where machine learning technologies are involved. We expect the waves of M&A and new partnering trends to continue."
Bill Stoffel, US Private Equity Leader, Ernst & Young LLP, adds that the tremendous amount of dry powder available in the marketplace is only going to spur more of this activity. “Currently, there’s around US$320b out there, and almost half a trillion globally, and we think that there's going to be three main sectors that we will see activity in: energy, health care and technology.”
This record level of dry powder also means a higher level of competition in the marketplace. And this has shortened due diligence time frames. So today, it’s not unusual for a transaction’s due diligence period to be reduced to just two or three weeks.
“What that means is that you have to have a team that is able to hit all of the key areas that impact value.” Stoffel says. “Hit it hard, hit it quickly and get the right answers as quickly as possible.”
“The two key things that you always encounter on private equity deals, whether it’s buy side or sell side, are really the quality of the data and the speed that things need to get done. The speed has changed significantly and the window has gotten narrower and narrower as years have passed.”
Better for buyers and sellers
For a buyer, transaction analytics gives focus to the due diligence process and allows a prospective buyer to identify any potential issues for discussion in initial conversations. By carrying out thorough analytics on the target, a buyer is quickly armed with detailed, targeted questions in those first rounds of management meetings.
“By leveraging transaction analytics and data analytics, it allows you to tell your story through data for the business or set of assets you’re selling,” says Gentry. “That’s going to provide management transparency, generate trust and ultimately help you craft a story to open the pool for potential buyers that want to learn more about the business or set of assets you’re selling.”
“Post deal, good transaction analytics can also aid integration,” says Gentry. “One of the most common pitfalls or the one of the most common issues we hear about is how we begin to drive out those synergies in the first hundred days. Transaction analytics allows you to look at that target’s data and compare that to your corporate data and figure out how you’re going to best drive out those top-line synergies – as well as cost synergies – in an expedited fashion.”
Picking up the pace
Data analytics enables faster transactions by more quickly identifying potential issues so that they can be discussed earlier in the process. It helps to build transparency between the parties involved in the deal and also aids with post-deal integration.
Transaction diligence can be used post close from an integration point of view to drive out top-line synergies and operational improvements that are a part of management or the business case. And beyond those, data analytics across a portfolio makes for better decision-making throughout the capital allocation process, regarding when to invest capital, when to sell businesses and when businesses need to be fixed or further invested in. So it can be a part of an entire chain of events, a circle around the entire capital allocation process.
Brian Gentile, former Vice President and General Manager at US-based TIBCO Analytics, says: “advanced analytics and big data can help to make or break a merger combination.” Data analytics plays a vital role throughout the deal process, he explains, from the required due diligence to realizing synergies post-deal.
“Every merger or acquisition requires a well-thought-out and structured plan, carefully explaining how the deal enhances the company’s core strategy,” Gentile says. “For this to happen, thorough market research, number crunching and due diligence are naturally required, meaning data analytics has a critical role to play while a merger or acquisition is being targeted.”
“Another factor that is often overlooked during M&A is just how quickly data needs to be put to work. What is more important to your business, for example: accessing a richly defined data set for broad analytic use or getting hold of data quickly?”
A closer look
But if companies can get this balance right, it can also provide valuable insights into existing or potential new customers. For example, in a retail deal, data analytics can reveal how customers are segmented, what they’re buying, when they’re buying and the influences on that buying behavior.
“We can also use data analytics to think about a buy-side deal in which you’re acquiring a set of customers,” says Gentry. “To look at that potential target’s customer base, compare it to your own customer base and identify the areas for cross-sell and up-sell help drive out those top-line synergies immediately after close.”
Data analytics touches every aspect of the due diligence process, enabling a seamless way to get to the right answers in a quick and timely fashion.
Data for every occasion
EY’s Malinda Gentry explains the many uses of transaction analytics:
- Data manipulation. There is a lot of complex, unstructured data out there today. Whether it’s company data, target data or third-party data, being able to bring those disparate pieces of data together and combine them in a structured manner in order to drive quick analysis is one way in which EY is using transaction analytics.
- Data visualization. Building interactive dashboards allows potential buyers and sellers to interact with live data, carry out analysis and see comparisons in order to better frame the transaction.
- Advanced analytics. Advanced analytics means predictive analytics: predicting what kind of markets we are going to see in the future, what kind of revenue can be expected and how that business is going to operate in the future. This is in addition to prescriptive analytics, which is how to leverage that data to optimize the running of a business and drive the greatest profit for companies and their shareholders.
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