Category: M&A

The largest software acquisition in history helped push overall tech M&A spending in October to the second-highest monthly total in the past two years. Acquirers around the world spent $72bn on 319 tech deals, according to 451 Research’s M&A KnowledgeBase. About half of the spending came from IBM’s blockbuster purchase of Red Hat just before the end of the month.

As the most significant transaction in October – and, indeed, of 2018 so far – Big Blue’s big bet on the open source software pioneer is noteworthy both in terms of scale and strategy. For starters, the $33.4bn price is as large as the second- and third-largest software deals combined, according to the M&A KnowledgeBase.

For 107-year-old IBM, its make-or-break pickup of Red Hat marks the first time the company has splashed out more than $1bn on a single acquisition in two and a half years. In that same time, however, the tech veteran has spent tens of billions of dollars on dividends and stock repurchases as it struggled to find revenue growth. For its part, Red Hat has reported 65 consecutive quarters of revenue growth.

IBM’s risky bet on the open source software provider stands out even more when we view it against the tumultuous month of October in the overall economy and, especially, the equity markets. Once-bankable investments in many of the tech industry’s main names turned blood red last month. For instance, Amazon, which secured a market value of $1 trillion in September, saw its shares plummet 20% in October alone. More broadly, the tech-heavy Nasdaq Index ended the month down roughly 9%.

Economic uncertainty and Wall Street volatility can complicate pricing for acquisitions, as well as prolong negotiations as parties sometimes revise their assumptions or recalculate their models if the outlook for the future becomes particularly cloudy. Those potential snags tend not to show up in transactions by corporate acquirers until some months later. In contrast, the impact tends to be more immediate for financial buyers, who rely more than their strategic rivals on the economically sensitive debt market to finance their deals.

Although October could very well be a blip in an otherwise record run by private equity (PE) acquirers this year in the tech industry, we would nonetheless note that buyout activity slumped notably last month. According to the M&A KnowledgeBase, PE firms in October spent just half of the monthly average of the preceding nine months of 2018.

With almost 10 full months of the year behind us, strategic acquirers are spending more on tech companies than at any point since 2015 and with higher multiples to boot, setting the tech M&A market in pursuit of a new high. Yet the sudden stock market dip threatens to snuff out the spark that started the conflagration.

According to 451 Research’s M&A KnowledgeBase, acquisitions of technology vendors have fetched a collective $460bn, a pace that puts the annual total near 2015’s record haul of $577bn. Although a rising cadence of private equity deals has contributed to that, the bulk of the gains comes from strategic acquirers, which have so far spent $352bn picking up tech targets, reversing a two-year decline in corporate acquisitions.

Historically active tech buyers such as Adobe, Microsoft, Salesforce and SAP have all inked $1bn-plus purchases this year, while last year none of them did. Adobe has done it twice, reaching for Magento and Marketo and paying north of 10x trailing revenue for each, a mark it’s never paid before for a target with meaningful revenue. Adobe’s not an isolated case. The average revenue multiple paid by a corporate acquirer across the 50 largest deals stands at 5.8x, almost a full turn above last year’s average, according to the M&A KnowledgeBase.

A rising stock market has provided some of the impetus. In the M&A Leaders’ Survey from 451 Research and Morrison & Foerster, 71% of respondents said that the uptick in public stock prices was a ‘strong’ or ‘very strong’ factor in the surge of corporate acquisitions, rating it higher than any other factor. When we fielded that study in early October, the S&P 500, building off its gains in 2017, was up 8%. In the weeks since, it’s given back most of the year’s progress, which could dampen the historically high multiples.

Subscribers to 451 Research’s Market Insight Service can access the full report on the M&A Leaders’ Survey from 451 Research and Morrison & Foerster, a semiannual survey of tech M&A practitioners that’s now in its fourteenth edition.

For all of its status as the hot new thing, machine learning (ML) has actually been around for some time. That’s true for the technology itself, which is basically an evolution of the data mining and analytics software that have been running for decades. Likewise, it’s true for dealmaking, where companies have looked to make their businesses and products smarter by acquiring ML startups for years.

In fact, the first record in 451 Research’s M&A KnowledgeBase in which an acquirer cited the term ‘machine learning’ as part of the rationale for buying a startup goes all the way back to 2003. For history buffs, the inaugural ML print – at least in our record-keeping – belongs to Nokia, which spent $21m for Eizel Technologies in April 2003. (The then-dominant phone maker was looking to Eizel to help smooth the rendering of email and web content on its phones, which were fairly limited at the time. The iPhone wouldn’t be introduced for another four years.)

More than just a historical artifact, however, the initial ML transaction we captured is worth revisiting because the reasoning behind the decade-and-a-half-old deal getting done could very well have been on a page ripped from a pitchbook making the rounds today. Even Eizel’s valuation, which works out to roughly $1m per employee, wouldn’t be out-of-whack in an ML transaction printed now, particularly if we consider the inflation-adjusted figure of $1.4m per employee.

As exemplified in that inaugural Nokia-Eizel pairing, the strategy and structure of ML transactions haven’t changed all that much over the intervening years. What do we mean? Essentially, the deal boiled down to an established technology vendor picking up some ML technology to optimize an existing product. Further, as is often the case for these ML startups, the technology had its roots in the computer science department of a research-intensive university (Carnegie Mellon University for Pittsburgh-based Eizel).

Those two trends came together more recently, for example, in Microsoft’s reach for Semantic Machines last summer. In that deal, the software giant was seeking some smarts around ‘conversational technology’ that it could deploy on Cortana, Azure and other products, so it picked up Berkeley, California-based Semantic Machines, which had ties to UC Berkeley and Stanford.

It’s almost as if that pair of transactions – separated by half a generation, involving vastly different buyers and technology applications – were nonetheless produced by the same algorithm. For more on how the emerging trend of ML is shaping both the software industry and the M&A market, 451 Research will host a special ML-themed edition of its M&A Summit next Thursday. For more details, see our website.

For more real-time information on tech M&A, follow us on Twitter @451TechMnA.

Companies that have signed off on the certainly-trite-but-possibly-true adage that ‘data is the new oil’ have discovered that the analogy extends far beyond the original meaning of both of the raw materials powering vast and varied industries. Most users of both resources have inevitably found that data and oil become valuable only after they are refined. In the Information Economy, most of that refinement gets done through the application of machine learning (ML) technology.

In a recent Advisory Report, my colleague Nick Patience, who heads up 451 Research’s software practice, notes that ML is a broad collection of technologies that serve a broad collection of uses. Yet, even with the near-universal relevance of ML (who doesn’t want smarter software?), the technology is only starting to find its way into companies. In Nick’s inaugural survey of 550 IT decision-makers, just 17% said they have deployed ML technology, with most of those use cases rather narrowly defined.

At the same time, however, his survey of these tech buyers and users shows they are planning to be much more expansive and aggressive with ML. Looking ahead, roughly half of all of the respondents expect to have ML technology up and running by mid-2019, up from just one in six right now. The soaring forecast for ML implementations is unprecedented in the relatively mature software industry.

That demand has sparked a record rise in the number of ML acquisitions, as suppliers look to pick up technology that helps them get a sense of the ever-increasing piles of information that companies accumulate about their own operations, as well as their ever-expanding relationships with clients, suppliers and partners.

Already this year, buyers have announced more ML deals than any year in history, according to 451 Research’s M&A KnowledgeBase At the current rate, the M&A KnowledgeBase will record roughly 140 ML-related prints for the full-year 2018, twice the number from just two years ago.

To get smart on ML and get even smarter on doing ML deals, 451 Research will be hosting a pair of special ML-themed M&A Summits next week, with morning events held on Tuesday, October 16 in New York City and Wednesday, October 17 in Boston. To reserve your spot for the M&A Summit in New York City, simply click here, and the M&A Summit in Boston, simply click here.