Analytics’ Hierarchy of Needs

There’s a hierarchy of needs when it comes to delivering a product or service. Just like Maslow’s Hierarchy of human needs, the items at the top are not important if the bottom isn’t first provided.

This mental model can apply in lots of variations. Here is an example using analytics and actionable data science:

1) Is the solution going to be accessible to the people who will need it?
2) Does it make things better and provide value in some way?
3) Does it work on every relevant variation of the problem?
4) Is it faster than the status quo or other options?
5) Is it easy to use?

Using this model, you can justify building something that is hard to use and slow, if it is still accessible, valuable, and relevant.

But if you can’t show the value or provide the outputs to the right stakeholders, it doesn’t matter fast or easy the solution is.

The Hype Cycle

Emerging technologies and trends sometimes follow a pattern such as the image below, first called the Hype Cycle by Gartner. There’s an initial peak of excitement and an explosion of market activity, followed by the rapid fall into the “Trough of Disillusionment.” Beyond that spike is a more sustainable, steady growth. This pattern is observed in many phenomena, not just in technology. For example, look at the price of Bitcoin

There are a number of technologies going through the hype right now, and I’m enjoying the enthusiasm. But the challenge is to be practical as well. I believe we are reaching the top for AI and we may already be sliding down the bottom for BigData – there’s going to be some pain and failure before these technologies reach the true growth curves that everyone is projecting. Now is the time to learn as much as possible, prepare your teams and workforce for the future, and start many projects, some which fail and all of which help you learn. There is massive opportunity for the people and the firms who are ready when the hype pops and the value climb begins.