Predicting technical change in three variables

Posted on Posted in Data Driven Culture, Machine Intelligence, Machine Learning, Marketing Science, Predictive Analytics, Technology

A great mind in public policy told me, just this last September, that people are really bad at judging the rate of technological change and when it’ll affect them.

It’s like standing on a railway. You can see the train out there. Some people assume that the train is going to hit them very soon. They get off the tracks. Then, when the train is getting very close, others misjudge the speed and assume that it’s still a far way. And then they get hit.

It’s a great analogy because it combines prediction with decision.

The rate of technological change is actually quite difficult to predict. If it was easy there’d be a lot more successful startups.

One Heuristic

Start with the user. Start with the market segment. Start with TAM. If you can seriously imagine adoption, you can start to get serious with Total Addressable Market estimation.

From there, estimating the rate of adoption takes a few variables, but an generally be abstracted down to two for simplicity. When does hypergrowth begin and how long will it take for the product to saturate Total Addressable Market (TAM).

One heuristic. Three variables. So many ways to be really wrong.

Three Variables and the Train

The first variable, TAM, is entirely about whether or not a train truly exists on the horizon. Is there a train? Is it even on your track? Is it a toy train? Is it something big enough that maybe you can get on?

The second variable, Hypergrowth Begins, is about how far away the train is. If you think the train is really far away, you’re going to set Hypergrowth as starting a long time from now. If you think the train is really close, you’re going to estimate that Hypergrowth starts now.

The third variable, Takeover Time, is about how fast the train is going. If you think the train is moving very fast, you’re going to get turned into a pink spray. If you think the train is moving very slow, you have enough time to hop on or get out of the way.

Good news

If you’re aware of your own biases, and you can measure them, you can manage them.