data myths

Ok, so this one isn’t entirely a myth, there are AI based tools that do make you more efficient.
Like the time one of my kids asked me what kind of plant this was when we were out on a walk; a quick snap using the Picture. This app and a few seconds later we knew it was a “Common milkwort”! Brilliant! (Though whether we’ll ever remember that for next time is a different matter).

Oh how I wish this one were actually true!

Asking data scientists to estimate the cost of a project is like asking a bricklayer to estimate the cost based on his bricks per hour when in reality you’ve got a plot of jungle, a sketch on a napkin and all the bricks are hidden.

Around 15 years ago Autonomy claimed this but it turned out to be a myth. In reality this is a really really hard problem for AI to solve. Here’s why, and then I’ll talk about some of the ways you can at least speed it up.

Getting new digital functionality working is complicated, especially when it involves integrating to existing systems from different vendors. The idea of copying all this data into a single ‘data lake’ is very attractive; everything will be in one place, your architecture drawings looks really clean, you don’t need to worry about how to connect to legacy systems or overloading them, the performance should be blisteringly fast. A modern one-stop-shop for all future development. I know this because this was my dream when we started Eigen 12 years ago! We were trying to build the one unifying data model that would enable all our functionality dreams. But here’s what we’ve found over the last 12 years.

We’ve all been there right, the project seemed simple to start with but once we got into it, it started getting complicated and all sorts of thorns started to crop up that took way more time to solve than anyone on the project governance board would believe.