More than 50% of today’s S&P500 faces replacement in the next 10 years, while one in three listed companies are at risk of being de-listed in the next five years alone.

20th Century management theories are based on a hierarchical chain of command, a separation of functions and an emphasis on planning, budgeting, efficiency, process, risk mitigation and of crouse, maximising shareholder returns above all else.

This might have made complete sense in a time when the impact of technology change was not as pronounced as it is today and decisions could be made with a little more certainty about the what the near to middle term would look like. Throughout the 1990s, Moore’s Law took the transistor count per chip from one million to over one hundred million, this was representative of an increase of 99 million transistors. Sounds impressive, right?

However, from 2010 to 2016 alone, we’ve added over 10 billion transistors. That’s more than 100 times the growth in transistors we enjoyed in the 90s. And the rate is accelerating.

Moore’s Law is relentlessly surging ahead and bringing us to an inflection point with the convergence of technologies such as artificial intelligence, the internet of things, nanotechnology, robotics, automation, virtual and augmented realities and blockchain, amongst others, together with changing political, economic and social realities across the globe resulting in more uncertainty than ever before and posing a significant threat to every industry and business model.

Large organisations are finding themselves scrambling to stay survive and stay relevant, let alone compete and thrive.

Most large incumbents have developed systems that, not unlike McDonald's, make them adept at efficient delivery but not chaotic discovery, something inherent to breakthrough, disruptive innovation. Incumbents are adept at execution, but not exploration. With growing uncertainty, the ability to make long-term decisions with any degree of conviction or accuracy is perhaps best left to clairvoyants, simply because the rate of change is so fast.

Israeli historian and author Yuval Noah Harari says of AI and exponential technology growth, the scenarios in which AI goes beyond human intelligence are, by definition, the scenarios that we cannot imagine and therefore ill-positioned to plan for. This fact has prompted Elon Musk, Reid Hoffman, Sam Altman and others to establish OpenAI, whose goal is to advance digital intelligence in a way that ultimately benefits humanity.

But to offer a less dystopian and slightly more relatable example to us humble homo sapiens, think of all of the enabling technologies and business models we take for granted today that we would struggle to live without? Most of these didn’t really exist in any meaningful way as recently as 20 years ago (think search, the smartphone and cloud infrastructure for starters). Yet, the breadth and depth of disruption over the next ten years is likely to go far beyond these examples.

Thriving under chaos is something successful startups do well and it’s also something that best-selling author Tim Harford says helped Donald Trump win the election. “He made the primary campaign all about him and sucked the oxygen away from all of his rivals. They just couldn’t make headlines, and couldn’t respond quickly enough to what he was doing.” By the time his opponents had prepared their thoughtful rebuttals Trump was off to the next disorienting announcement and left them scrambling again to make sense of the situation and respond.

For large incumbent organisations, it’s not a case of simply flicking the switch on “the way things have always been done around here”, donning white shirts, red ties and embracing a, dare I say, Trumpian approach to innovation. Culture, mindsets, processes, systems, performance incentives and values at large organisations can often be the very antithesis of innovative thinking and if I’m a senior executive whose success has been pegged to having what appear to be the right answers, mitigating risk and maximising shareholder value and my core business is still, after all, making money today, then the prospect of genuinely moving from delivery to discovery for most large organisations is a grim one.

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But it is not without its remedies.

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Incumbents can attempt to re-design or create parallel processes and systems internally to support exploration but need to ensure that it doesn’t compromise the delivery of the core business. They can carve out a new business unit to deal with disruptive innovation, create spin-offs or spin-ins or they can invest in, partner with or acquire startups.

The latter approach is indeed the most straightforward and popular one with technology M&A deals in the United States alone totaling US$42.8B across 486 investments in Q1 2017. Globally, corporate venture capital participated in US$24.9B across 1,352 deals in 2016 with seed and Series A investments accounting for almost half of this so clearly large incumbents see startup investment as a significant part of their growth strategy.

However, in the case of acquisitions, the question of independence or integration is one most large incumbents still seem to struggle with.

Clayton Christensen urged caution in The Innovator’s Solution in which he wrote that if a large incumbent is acquiring a startup for its processes and resources, then the last thing it should do is integrate the targets as this will “vaporize the processes and values of the acquired firm”.

The key lies in corporate-startup partnerships...

A better strategy, Christensen tells us, is to let the acquired startup stand alone and to infuse the parent’s resources into the acquired company’s processes and values. If and only if the target is being acquired for its resources only then integration makes sense.

Christensen sights IBM’s acquisition of telecommunications company Rolm as a classic case study. Big Blue’s integration of Rolm, whose value resided in developing and finding new markets for PBX products, destroyed the very source of the original deal’s worth.

More recently, I had a conversation with the Head of Digital at a large commercial bank who shall remain unnamed. He revealed that the organisation had spent US$4M acquiring a startup, only to spend an additional US$5M integrating it into the mothership, shrouding it in corporate bureaucracy and IT systems, effectively destroying the startup’s culture and cadence. This culminated with the startup founders leaving the organisation out of frustration. When all was said and done, over US$9M was invested into what fast became a train wreck with dwindling to little value.

Countless research papers and journals estimate that M&A deals fail to deliver on financial expectations up to 90% of the time.

With this in mind, the following guide provides readers with a high level overview of the when, how and who of corporate startup partnerships and acquisitions.

Perhaps more importantly though and to quote Simon Sinek, large incumbents on the investment trail should always start with why.

When deciding to invest in, acquire or partner with a startup, what is this decision really based on? Market sentiment? FOMO? Me too complex? Actual strategic alignment? Diversification?

When to acquire

Timing is another aspect of acquisitions that large incumbents appear to struggling with.

The instance of incumbents paying massive premiums to acquire or invest in later stage startups, who in many cases have already done the majority of their growing, appears to be on the rise. In some cases, this might make perfect sense where there is strategic alignment and where the resources of the acquired firm don’t exist in the parent or where the acquired firm provides other complementary business model improvements.

Quite often though, such acquisitions are ill advised and are driven by not knowing how else to respond.

Yahoo acquiring Geocities in 1999 for US$3.7B and eventually shutting down the service as users defected to blogs, Twitter and Tumbler or Newscorp acquiring Myspace for US$580M in 2005, only to sell it six years later for US$35M are case studies in the wrath of terrible acquisition timing.

Prominent venture capitalist and founder of Foundry Group and Techstars, Brad Feld, reiterates these sentiments, stating that “there are continuous cycles of non-technology companies entering into the world of trying to buy technology companies going back well before I started even my first company (Brad started his first company in 1987). And a small number of those companies extract significant value out of [those deals] because they buy well at the right time on their curve and they’re able to do something with it. And a whole bunch of companies don’t get a whole lot of value for their investment”.

Think of it as the buy high, sell low folly of corporate acquisitions. Something we’re so often told not to do when it comes to our own investment philosophy by the likes of Warren Buffett and Charlie Munger and other prominent investors.

Sadly, the instance of large organisations falling into the same hype cycle as individuals, paying premiums for sentiment driven acquisitions and investments and later suffering the cost shows no apparent signs of slowing down.

Dumb money

When a startup successfully raises investment from an entity or individual that can’t provide any tangible value above and beyond the color green, they’re said to have received “dumb money”.

I recently facilitated a pitch night for a legal-tech accelerator program. One of the budding legaltech startup founders was a former partner at a top-tier law firm. During question time, a senior partner in the audience asked him “why do you need the money?” in response to the $55,000 investment that successful applicants would receive for participating in the accelerator. I couldn’t help but laugh at the naivety of this question - as if money is somehow all that stands in the way between an entrepreneur and realising their vision.

If only it were that easy.

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