For a large organisation to be agile, frontline employees – and not just executives – need to make higher-order decisions. This requires an open, self-serve data architecture, and a workforce with the right data skills to make the most of it.

Our own data from our Digital Org Diagnostic shows that companies who lack routine data-sharing practices rarely have open cultures. After all, how can we trust employees to make smart decisions if we do not give them the raw materials to do so?

We are not saying all frontline employees should have degrees in data science. But employees do need a baseline of knowledge and confidence with data, so they can make decisions based on evidence rather than gut feeling.

Easy to say, but how is this done? It starts with careful training and coaching. The global logistics company UPS uses familiar concepts – in this case, cost per mile – to train its drivers on how to use algorithms.

Data for the masses goes beyond the edges of the business. The Spanish lender BBVA just opened its banking data sets to business customers and start-ups, who can go on to build new products and services on top. Open innovation in pharmaceuticals, pioneered by companies like Eli Lilly, promises to accelerate drug discovery and improve R&D.

A more data-fluent workforce has enormous potential on both innovation and society. Don’t we owe it to our employees – and ourselves – to raise our collective Data IQ?

Below is some further reading on the topic: