Everyone loves self-service for insurance policies, banking, and sorting out any number of personal accounts. But when it comes to self-service data analytics, while everyone loves it in the boardroom, it quickly dies out in the real world.
Why is that? After all, on paper, and at the design and implementation phases, it seems ideal. And it is: the benefits are obvious, it takes workload off the IT people, it allows business users to get results when needed, there is no delay and users can play with data as ‘masters of their own destiny’.
But there’s a flip side.
Self-service means users who have a million other things to do must put in the effort. More than that, they must know how the tools work; nobody wants to go to the CEO with dodgy numbers and when something is self-created, the onus is firmly on you. In practice, that means unless the training is thorough, and unless the user has absolute confidence in the data, the tools and the outputs, there is that nagging feeling of ‘have I got this right’.
And if there are multiple tools, dashboards and reports being created which don’t tally up, confidence can be rapidly undermined.
Then there is the self-explanatory ‘lazy-person’ factor. Some users don't have the time or can't be bothered to make analysis a part of their day; they don’t see the value, the benefits or the advantages.
So, if this is why, in my experience, adoption of self-service tools is just not where it should be, what can we do about it?
The obvious stuff is to train and reinforce the what, why and how of the tools provided. It helps if the data (and, therefore, outputs) can be demonstrated to be reliable, too.
The less-obvious and harder stuff is to establish a data-driven culture. The key here is ‘data availability’ and creating an environment where people can get in, use data and analysis for insights that underpin decision-making. That’s a shift from the culture where reports are spoon-fed to passive recipients.
Yes, it is somewhat nebulous and yes, this is difficult to achieve. However, for those organisations which have deployed self-service tools, adoption serves as a ready measure of the transition to a data-driven culture.
In effect, if you have implemented the tools but suspect that the adoption isn’t quite what it should be, the raw material to improve is at hand. Find out who is – and who isn’t – taking to the tools, examine the underlying reasons and look to gain the real value of self-service.
The good news here is that you are not alone. We’ve been through the journey with numerous businesses and learned many lessons. The learnings from both failures and successes have been distilled into methodologies and experience that we put to work helping clients every day.