I'm a Tamagotchi

I've got a thing attached to my arm giving me moment-by-moment readings of my blood glucose. It's like having a Tamagotchi, except the Tamagotchi is me. If you missed this in the 90s, a Tamagotchi was a digital pet you had to keep alive for as many days as you could, tending to it day and night. I'm now the pet.

On the one hand I'm loving being a little bit bionic and pretending I'm a biohacker. On the other, I'm sceptical. Is it going to tell me anything I don't already know? Eat less. Move more. Smaller portions. Eat more vegetables. And no, cheese is not one of your five a day, no matter how many times Tom tells me it is.

But I think there's something in the granularity of seeing a timeline of data: a connection between your actions and the outcomes. The modern business world is too reliant on averages, and when I say average it's nearly always the mean, when the median might be more interesting, or the mode.

[Side note: I can still remember Mrs Lomas' maths lesson on averages - the Mooode is the one that happens Moooost often. And the Meeedian is the Meeeddle one]

Take the same look at your business data. What happens most often? Look at the distribution of outcomes, not the average. Look at cause and effect. Cause and effect is where you get an interesting narrative, and that's what stories are built on. I used to work in a business where leadership envisaged nearly full truckloads of product leaving the warehouse. A stark contrast to the median where two or three different items were shrink-wrapped together on a single pallet.

So does the average really tell us anything at all? Do we need to learn new lessons, or do we need more evidence to do the things we already know about, more consistently?

Big was the wrong word

Maybe I'm going all retro here talking about big data. But loads of data on its own isn't enough. You need action or decisions. The problem with big data is that big was the wrong word and useful data might have been a better description. And your actions don't need to be big. Small is good too: little actions done consistently, or the same decisions made earlier.

I see the same pattern in organisations. I don't buy the worldview that says everyone's got the same AI tools so everyone will have the same advantage. Consistent execution is still hard, no matter who you are. When I run workshops, we have teams prioritise crawl, walk, run. Crawl is the things you can do now with the systems you already own. That doesn't mean it won't move the needle significantly, because just because you know what you should be doing, doesn't mean there's not a performance gap.

Your organisation has its own version of eat less, move more: the things everyone already knows, sitting under a pile of averages or glossy communications. It's why I built The Cold Eye. An independent read on which of your AI bets are real, and 90 days to back only those. If you want one, reply to this email.

What am I going to learn from being the human Tamagotchi? I don't know. The jury's still out. It might be data for data's sake, or it might turn me into a mean lean consulting machine. You'll need to stick around to find out.

The workforce verdict

Last issue I asked you to vote: KEEP the AI workforce, or KILL it as procrastination with better branding. One vote was cast. It said KEEP. Fitting for a discussion about averages: a sample size of one, where the mean, the median and the mode all agree. The workforce lives.

Till next time,

Helen

P.S. The glucose tracker told me to do 10 minutes of calf raises last night. Who does calf raises for 10 minutes? Obviously people with massive calves. But what the fork?