The late 1990’s was a very interesting time in the stock market. The internet started to reach the public. Investors knew it was going to be a big deal. The dot com era was here. There was a period from about 1997-1999 where it seemed that adding “on the internet” to the investment pitch was a guarantee of massive funding. We saw companies with seemingly no products, no sales, and no assets, valued at flotation at more than some of the world’s biggest companies. Then came the crash. Many companies shut down, others lost almost all their value. Questions were asked. Why was so much money wasted? Why this irrational exuberance on valuations? From the absolute peak to the post-September 11th trough over $5 trillion of value was destroyed. Tech investment changed forever. Never again would investors pile money into companies with such high risk….this isn’t true. And there are very good reasons for it. Think back to the dot com bubble. How could investors put so much money into so many bad ideas? One company alone lost 96% of their value. A company who had never made a profit, who sold products at a loss, and who had invested tens of millions of dollars in a 30% share in the notorious failure pets.com. That company was amazon.com. Now valued at $1.6 trillion. Traditionally investment had meant getting the best return for the lowest risk. Who would you trust with your money? Someone who returned a steady 3% above inflation and had never lost money on an investment? Or someone who put 90% of their investments into companies that subsequently failed?   Risk averse investors, who are the vast majority of the public, would almost always go for the first. People look for the frequency of accurate predictions. But the magnitude is more important.  The investor losing on 90% of the companies they invest in would be regarded as a genius if the other 10% was an investment in Amazon in 2001 or Apple in 2003. Research shows the majority of very successful investment portfolios rely on a handful of exceptionally well performing assets mixed in with a lot of failures. So what has this got to do with football? Risk minimising investors You buy blue-chip stock (an established competitive club) and run through the process increasing the commercial value by improving each and every aspect of how it is run. You bring in the best people with a track record of success and free them up to replicate the processes that have worked in the past.  Data on players is better than ever, you can find undervalued talent, ensure contracts are based on future value not past performance, and find coaches who maximise player performance. This will always be an entirely sensible approach, and in football will likely lead to success as most clubs are not run like this. However, this approach suffers from drawbacks. Diminishing returns from recruitment data Everybody has access to more or less the same data. In the two years we’ve been working in the industry the time between a player flagging as “good on data” to being purchased, usually by Brentford or Brighton, has fallen significantly.  The really clever teams will be using specialists (here comes the plug) like MRKT Insights to support their data analytics and scouting departments. Most of the great players aren’t found by data Much as every data scout loves finding the wonderkid playing in the Romanian second division it is true that the majority of the elite players have been prodigious talents, easily identified long before their first-team debut. If you are scoring 5 goals a game as a 13 year old in the Western world you will be identified by a big club through a traditional scouting network. There is only so well you can do Winning trophies, maximising income streams, adding value to the asset. All great from an investors point of view but if you are putting $1 billion into an already successful club how much can you improve it? Do it brilliantly and you could double, maybe treble your investment. But you are reliant on market conditions, a TV deal collapses, there is a global pandemic, your £100m striker gets injured.  If making a return on the investment is key should we think more like an investor backing start-ups? Venture capital investors The best example I can see of a high risk / high reward approach was at Everton in 2016-17. The academy staff were handed a recruitment budget to sign the best players in U18 football. In total 4 players were signed.  Dennis Adeniran (Fulham £4m), Lewis Gibson (Newcastle, £6m), Josh Bowler (QPR £3m), a combined £13m spent on players who have yet to appear for the club. A spectacular failure then? The fourth player was Dominic Calvert-Lewin (Sheffield United, £1.5m) now valued at £60m, the top scorer in the league, and an England international. Ignore the frequency of success (a mere 1 in 4) and look at the magnitude, a 300% return in value overall. Jeff Bezos uses a sports analogy to describe the success in this strategy: “We all know that if you swing for the fences, you’re going to strike out a lot, but you’re also going to hit some home runs.” “The difference between baseball and business, however, is that baseball has a truncated outcome distribution. When you swing, no matter how well you connect with the ball, the most runs you can get is four. In business, every once in a while, when you step up to the plate, you can score 1,000 runs.” So does professional sport investment suffer from this “truncated outcome distribution”. At a sporting level I’d say it does, there are only so many trophies that can be won. You can only field 11 players at a time. But from a business point of view, is it possible to create huge returns on investment from relatively small input? Can you return 100-1000 times the input? … Continue reading What can football learn from the dot com bubble?