I have spent quite a lot of time recently watching the World Cup and Wimbledon.
I have described this to Stella as research into human performance under pressure.
She has described it as watching television.
Either way, it has been educational.
Sport is now surrounded by data. Possession, expected goals, first serve percentages, distance covered, shot speed, heat maps and recovery times.
At some point, I fully expect Wimbledon to tell us how often a player looks at their mum between points and whether it improves their backhand.
And I am not against data. Far from it.
Good data reveals patterns, challenges assumptions and stops us relying on the dangerous leadership method of, “I have been doing this for thirty years, so trust me.”
It helps coaches prepare, players improve and teams understand where performance is slipping.
But it has one fairly important limitation.
The data knows what happened. It does not know what happens next.
It can tell us that a tennis player has won 78 per cent of the points behind their first serve, but it cannot guarantee they will land the next one when they are match point down, their arm has turned to wood and fifteen thousand people are waiting for them to mess it up.
It can tell us that a football team has dominated possession, but it cannot predict what happens when a defender makes a mistake, the crowd turns and eleven highly trained professionals suddenly look as if they met in the car park ten minutes before kick off.
That is because there is a difference between something being complicated and something being complex.
A complicated problem may have hundreds of moving parts, but those parts usually behave in ways that can be studied and predicted. Given enough expertise, information and computing power, you can normally work out what is likely to happen.
That is data heaven.
People react to one another. They lose confidence, regain it, misunderstand what was said, become defensive, change their minds and occasionally do something brilliant that nobody predicted.
The situation keeps moving because the people inside it keep moving.
This opponent, this pressure, this crowd, this history between these people, in this exact moment.
It has never happened before and it will never happen in quite the same way again.
This moment only once.
Data can help you arrive better prepared. It can tell you what usually happens, what happened last time and where the risks might be.
But when the moment arrives, somebody still has to notice what is changing, make sense of it and adapt.
We now have dashboards for sales, engagement, productivity, retention, customer satisfaction, performance and risk. Leaders use them because they are trying to make sense of complexity, which is entirely reasonable.
The mistake is assuming complexity has been understood simply because it has been turned into a chart.
A pipeline might tell you that a deal has moved backwards, but it cannot tell you whether the customer has lost confidence in the solution, the salesperson or the whole process.
I have watched teams arrive at customer meetings armed with beautiful decks, detailed data and enough analysis to launch a small satellite.
They still failed because nobody noticed the customer had stopped trusting them.
The numbers were accurate. The conclusion was nonsense.
That is the real danger. Not that the data is wrong, but that it can make us believe we understand more than we actually do.
It will process more information, spot patterns faster and identify problems that may previously have taken months to become visible.
That is a good thing.
What AI will not do is make a complex human situation uncomplicated. Emotion, history, fear, trust and ego will still be in the room, probably sitting near the front.
AI may expose slow decisions, ignored customer signals, overdependence on one person and the same problems being avoided again and again.
It may even identify the uncomfortable possibility that the leader is part of the problem.
The difficult bit is whether anyone is prepared to say so, and whether the leader can hear it without blaming the team, the system or possibly the AI.
AI can show you where the pattern is. Someone still has to read the room, have the conversation and do something useful about it.
It can give you better information, but it cannot make you curious, stop you becoming defensive or persuade you to listen when the evidence suggests your original plan is wrong.
The better the technology becomes, the harder it will be for leaders to blame the system when they still cannot listen, decide or adapt.
Data is brilliant when the variables behave. Leadership matters when they do not.
The best athletes understand this. They use data to prepare, study patterns, identify weaknesses and improve technique.
But when the moment arrives, they do not play the spreadsheet. They play the person in front of them.
Organisations need to understand the same thing.
So, the next time a dashboard tells you something has changed, ask:
What are the numbers telling us?
What are the people closest to the work seeing that the dashboard is not?
What do we need to adapt now?
Because the data can tell you why you lost the last point.
It cannot play the next one for you.
