It is better to be approximately right than precisely wrong. – Warren Buffett
You can’t ignore the excitement about technology that suffuses LinkedIn these days.
It’s everywhere: from new data science pundits to commentary on changing business models everywhere you look.
Which, of course, means I start to look some more.
I was quite taken by Jeff Immelt and Vijay Govindarajan’s article about how manufacturers must use tech to survive drawing on their experiences at GE.
There were a few points that resonated with me – the idea that much of the resistance to change comes from inside the organisation and how to address the question of whether you should work with a partner or develop your own capability?
And then, I thought a little bit more.
The article has an echo about it.
Jack Welch, a former GE CEO, also wrote about change at GE in his book several years ago.
Much like Immelt, he also took the view that existing businesses had an advantage over new entrants – they already had assets and could simply bolt this new digital internet thing onto their existing operations and all would be well.
But it wasn’t. As we now know.
Instead, we have new behemoths that stalk the digital ecosystem.
But what’s really changed? Who’s winning and losing here?
And to think about that we should go back to an old favourite – the essays of Warren Buffett and his views on risk.
The question we should ask ourselves about everything is not what we hope to win but what is our possibility of loss or injury?
Buffett argues that what we should aim for in any investment situation is whether what we get back over time gives us at least as much as we had at the start plus a modest rate of interest.
Note the word modest.
Not outlandish or spectacular or ludicrous.
The real risk we have is whether or not we get our money back with interest.
He then sets out five tests to evaluate this risk.
- Can you understand, with certainty, the long-term economic characteristics of the business?
- Does the management have the ability to run the business and wisely use their profits?
- Can they be trusted to put money in the shareholders’ pockets instead of filling their own?
- What price are you being asked to pay?
- How will tax affect what you get at the end.
The interesting thing is that when you apply this test to many other situations it works just as well.
Let’s say you’re considering advertising with an organisation.
You can ask yourself whether it’s got a clear and sustainable business model.
Are the people who run it good?
Are they going to make sure you get a return on your investment or are they going to take your money with no guarantees?
Is what they are charging a reasonable amount or are the gouging you for all you’ve got.
And will you have enough left over at the end of all this to make it worth while?
But what does any of this have to do with AI and data science and all that new stuff?
Well, the main point is that the benefits from innovation tend to go to one set of people.
Very little value from innovation sticks to the manufacturer.
Most of it goes to customers in the form of lower prices.
That’s why social media is free for so many of us.
If you want to make money then what you need is an unfair advantage.
To keep it what you have to do is understand real risk.