Beware of the Cult

‘In the South Seas there is a cargo cult of people. During the war they saw airplanes with lots of good materials, and they want the same thing to happen now. So they’ve arranged to make things like runways, to put fires along the sides of the runways, to make a wooden hut for a man to sit in, with two wooden pieces on his head for headphones and bars of bamboo sticking out like antennas—he’s the controller—and they wait for the airplanes to land. They’re doing everything right. The form is perfect. It looks exactly the way it looked before. But it doesn’t work. No airplanes land. … they follow all the apparent precepts and forms of scientific investigation, but they’re missing something essential, because the planes don’t land.’

— Richard Feynman

The intelligent use of data has become a competitive advantage for companies in all industries. With the current technological advances in machine learning algorithms, it’s now possible to predict a whole host of occurrences from manufacturing defects to customer preferences and voting patterns. Companies who still regard data as ‘something that happens in IT’, will in time struggle to be efficient and profitable. That is if they are not feeling the pain already.

This presents a huge temptation to implement data science solutions without knowing exactly what you want to achieve from the exercise. Steve McConnell describes how software development organisations attempt to emulate their more successful peers by slavishly adopting a competitor’s process without necessarily understanding the reasoning behind it. 

The same applies to data science. Despite the shortage of practitioners, it’s relatively easy to hire a data scientist. Embedding the change in the organisational model and mindset needed to go along with it is much harder. While it’s always a good idea to look at what your competitors are doing so you don’t make the same mistakes, you need to consider how that fits into your organisation.

We’ve heard companies from large multinationals to small startups crow about their artificial intelligence (AI) solutions. But lift the hood and you realise very quickly that there’s nothing there. These unfounded claims can only be driven by an attitude that says,  ‘If they’ve got one, I’ll have one too’. In the long run, this will cost organisations dearly. 

The best data science projects take a holistic view of an organisation and think hard about the tangible outcomes the project is meant to achieve. Mindlessly replicating another organisation’s data strategy without really understanding what that means in your context, is never good business.