There are a few key things that stand out from my memories of my University academic studies, and one of them is the ideas behind a book written in 1958 by Michael Young (father, I found out this morning, of journalist Toby) called The Rise of Meritocracy. In Young’s satire, he paints a picture of a world which is truly meritocratic, and the outcome is totally dysfunctional. Those at the top know that they deserve to be there and so become complacent and arrogant; those at the bottom know it’s their place and so shut down completely.
Whilst there is a common call that we live in a meritocratic society, the reality is that (in my humble opinion) we simple don’t – and that the capitalist system would break down if we did. Why bother striving harder if where you are is where you deserve to be, bearing in mind that it’s hard work plus ability that would be the deciding factors? Earlier this year I saw Dan’l Lewin, the Microsoft exec who heads up the BizSpark startup initiative globally, who said (in paraphrase) any successful entrepreneur who doesn’t acknowledge that luck has a significant factor to play in success is being disingenuous.
I’ve been thinking about this as the result of a chance conversation yesterday about how technology may or may not enslave us to data. The current trends towards increasingly quantitative, (big) data-driven decision making in business has been troubling me, and I think it’s because I see parallels in Young’s observations from over half a century ago.
Risk, alongside inequality of economic standing driving people to want to achieve more, is one of the things that powers the economic systems we live in. Making risky decisions is how profits (and losses) are made. And without the opportunity for risky decisions to be made, the system will grind to a halt.
But, and here’s the concern, reducing risks of decision making seems to be the modern-day alchemy that is underpinning so much of what gets labelled “insight”, “business intelligence” or whatever the current vogue may be. Sure, if you can gain greater insight than your competitors to reduce down the risks in decision making, you may well get to exert some advantage over them for a while. But increasing analysis and data-reliance squeezes risk out of the system, and margins along with them. Companies then get into arms races around marginal improvement on those analytics – which seems to be where the world of economic algorithmic trading now sits. The problem, then, is that vast resources are deployed in ways that make little positive difference.
One of the themes at the CBI Conference earlier in the week was how the British economy needs to be able to push STEM (science, technology, engineering and maths) subjects in education to bolster and build our engineering industries to remain globally competitive. What didn’t get a mention was how the analytics arms race results in the best STEM graduates today being sucked out of the world of engineering, and into the world of financial services, lured by salaries that are totally out of proportion to what other industries can afford to invest. We end up deploying great minds to (tiny) marginal improvements, rather than risky step changes in how we do things. Polishing rather than building…