The Surprise of Big Data

The Surprise of Big Data

Brilliant communication is a collision between art and science. Consider two examples, both from RBS:

Our busiest branch in 2014 is the 7.01 from Reading to Paddington as over 167,000 of our customers use the Mobile Banking app between 7am and 8am on their commute to work every day.


In the UK, [Personal & Business Banking] provided 8% of gross new mortgage lending in Q1 2015, in line with historical market share, delivering £0.4 billion net mortgage growth.

Both contain analytical facts and figures that took an enormous effort to produce, but why is the first statement so much more engaging?

The answer is that the first quote is surprising. You are expecting to hear that the busiest branch is somewhere in a bustling financial hub, but instead you’re given a train timetable.

Crunching lots of numbers to generate charts, diagrams and infographics is useless if the results aren’t surprising. What if the only thing RBS found was that younger people were more likely to use the mobile banking app? That’s not useful because a lot of people already assume that’s true.

Big Data and analytics sells themselves on “value” – actionable insights from the data that lead to some sort of better outcome (often financial). That sounds great, but that kind of value is not actually what you should be looking for in an analytics tool.

What you should be looking for is the element of surprise, because that means there’s value later on. Looking back at the first RBS quote, at first it is difficult to see how they could find direct “value” in that insight. However, at least two things will happen because they found commuters used their mobile app:

The first is that people will realise that the tool is capable of generating interesting, memorable, and engaging results. That means people will continue to use the tool and test their hypotheses. Some of those results will arrive stapled to a proposal to improve your business – actionable and valuable. Without surprising results, the tool is likely to be abandoned.

Secondly, someone creative is going to find a way to create value from that (useless) mobile commuter insight. Whether that involves tailoring the interface for a moving train carriage, or designing it for use in tunnels with no reception – someone will find a way of innovating. That will only happen if the insight is surprising enough to be thought-provoking.

Like the saying goes, “a watched pot never boils”. Big Data and analytics are all about serendipity, and that doesn’t happen when you’re consciously looking for value. Meanwhile, make sure your tool is engaging and surprising to as many people as possible, and the value will come.