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Dancing with the unicorns of future past

Summer 2016

In December 2015 HBR published a study by Playbigger seeking to find the IPO Sweet Spot hidden in the Big Data. You will find the article here: How Unicorn's Grow. While study can be found here: Playbigger and the slideshow here: LinkedIn

The answer they found was framed by the limitations of the dataset they chose to mine. Specifically the period (2000-2015).

So let's see what happens when you extend the time frame back to 1980 or beyond. What does the historical big data reveal about the fabled Silicon Valley Unicorn IPO sweet spot?

The first question being where do we source the data? The answer being: Jay Ritter

The next question being what does the data reveal?

Let's begin with age

Clearly the average age of the Tech IPO is getting older... But as they get older they are becoming less profitable. Significantly so. Indeed the trend line suggests the average profitability of a Tech IPO by the end of the decade could be as low as 20%.

Not that this is any surprise. We already know that revenues decrease as network adoption increases. This is the economic paradox of the network effect. Stickyness has its price.

To compensate for this lack of profitability the total and average value of the amount of money raised at the time of the IPO to fund future revenue growth - and payout existing investrors (e.g. Venture Capital/Angel) - is increasing.

And this is mirrored in the movement of the average price to sales ratio

So much for the averages. Now let's take a quick look at what the outliers tell us about the IPO Sweet Spot.

What happens when we map the ROI on a basket of the brightest stars from 3 generations of Tech IPO's (i.e. 80's, 90's & 00's) over the first 3, 5 and 10 Years of operations?

We discover - somewhat surprisingly - the birthday of the IPO sweet spot was way, way back in the 20th Century. Circa mid to late 1970's to be precise.

Which raises the question: Why? Given all the excitement. All the rhetoric. All the popular theories - academic or otherwise - about game changing disruptive innovation. But most importantly all the dollar's invested in the network economy. Why is whole idea of Silicon Valley the Global Innovation Leader - at least when it is held to account by the patterns of profitability and investor returns embedded in the big data - apparently so yesterday?

So last century?

Well perhaps the answer to that can be found here...

But perhaps the simple answer is 40 to 50, perhaps even 70 years on, isn't the whole disruptive, game changing, next big thing, ITC innovation narrative streaming out of Silicon Valley looking a little bit tired?

Dare we say: in need of disruption?

Certainly the numbers embedded in the big data seem to suggest so.

Because even a cursory reading of the market data indicates the game of disruptive innovation is little more than a game of marshalling pension fund inflows into the tech sector.

And when money is cheap so are the ideas being funded. That's why tech "start-ups" are no more efficient than mining "start-ups" when it comes down to investors capitalising on the next "bubble".

Which speaks to the heart of what passes for disruptive innovation in the digital economy.

You see - even the most fleeting glance of the big data will reveal - the game of innovation is no longer about solving problems. It's simply about picking the next bubble. Riding the next wave. Harvesting the baby boomer pensions... and you really don't need another app or the cloud to do that do you?... Or, then again, do you?

Further reading:
SaaS Start-Ups and the 7 Year Rule
The problem with being SaaS
Is the pace of technology adoption really speeding up?

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