Heard the one about Big Data being the new oil? Over time, or so we’re told, those who invest in Big Data will be rewarded with a massive advantage over those who don’t. Indeed, one day we may even be able to do away with scientific method, relying instead on what the data tells us as opposed to working things out for ourselves.

Such predictions assume that everybody’s about to jump on the bandwagon, but it belies the fact that many organizations are far from being ready to make the kind of investments needed to fully embrace Big Data. Indeed, many larger businesses are actually striving to act more like startups these days, looking to slash costs in whatever department they think can afford it, more often than not IT.

For this reason we’re not going to see a Big Data revolution anytime soon, argue Matti Keltanen of service design consultancy Fjord in The Guardian. But what might come instead is a focus on “lean” data that can often provide just as valuable results.

Why Put Lean Data on the Menu?

According to Keltanen, this “lean” data strategy actually makes sense for several reasons, chief among them costs. At the end of the day, most businesses are new to the data game, and so starting with Big Data on an industrial scale will be counter-productive. Moreover, Keltanen points out that small bits of data are often the most meaningful anyway. He points to the example of Food on the Table, an Austin startup that helps people plan meals for their families around what is on sale in their local grocery stores, which only accepted a handful of customers at first, honing its business model on the feedback these provided.

The second point that Keltanen makes is that Bigger Data isn’t necessarily always better. It’s a well-known fact that in statistical measurements, the more data points you have, the less accurate the results will be. It’s exactly because of this reason that Nate Silver, the guy who used data to predict the outcome of the US Presidential elections, actually uses “lean” data when making his predictions.

Lastly, analytics costs time, lots and lots of time. The best analytical software in the world won’t tell you what your data actually means, only humans can do this. By starting out with lean data, organizations will be able to answer the questions that are most relavent to their business first, rather than wasting hours sifting through hundreds of graphs and visualizations they cannot understand.