43 Quintillion Types of Innovation

Learning to solve a Rubik’s cube can lead to plenty of trouble but ultimately brings quite a lot of personal satisfaction and perhaps a few lessons for work too.

A Rubik’s cube is a good metaphor for innovation. Innovation is not often about creating something entirely new (strictly speaking that’s invention) but about finding the right combination of factors that solves a critical problem in a new way. Like the different colours on the Rubik’s cube, these factors are of different types – consumer needs, emerging technologies, regulatory requirements, commercial implications etc. And like the Rubik’s cube, to “solve” the innovation problem you need to put each of the pieces in the right place. Even given a small number of inputs (6 coloured sides, 9 bricks on each face) there are 43 252 003 274 489 856 000 combinations! And if 3x3x3 is too simple, there is even a 17x17x17 cube – perhaps a better analogy for disruptive innovation… and with a world record solving time of around 38 minutes compared to around 3 seconds for the 3x3x3 cube!

If the odds look daunting, consider another difference: we know what the “solved” Rubik’s cube looks like. In the real world, the final innovation solution is often not clear at the start, and you can’t always know the difference between the right and the wrong combination before creating them. Nevertheless, this hobby has some parallels with professional innovation work. As with any profession, the more time spent cubing the better one gets – with broader experience the more likely you are to find the “right combination” when you’re presented with a new problem.

There are lots of different sources of teaching for Rubik’s cubes: books, videos, even friends with advice. While different parts of the solution can be picked up from different places (that’s a lesson in itself), many struggle until they find one excellent resource. Given enough time (and a few false starts) it becomes possible to solve the 3x3x3 cube each time by following a set of repeatable algorithms.

But the journey to getting better and faster reveals another insight: you don’t just need new algorithms; you need to know when and how to best use them – and even how to break these “rules”. The first (and the easiest) sources of input, and perhaps even those that feel most comfortable today, are not necessarily the ones that will lead to the breakthrough you need.

The same is true for innovation. There are tools out there which given enough time and enough false starts (i.e. innovation fails…) can give results. In the real world however, there is cost to those failures – and reducing the time it takes to find the right solution is critical. And so, for important real world innovation problems, even if you’ve read the books and know the “algorithms” – it might be a good time to work with someone else to ensure you make that breakthrough.