Self-service BI implementations are a bit like cakes in that they don’t turn out well without a tried and true recipe for success. If you don’t want overburdened analysts, frustrated end users, or an unused solution burning a hole in your wallet, it’s best to design a strategy around your organization and its specific needs.

But what does a comprehensive self-service BI strategy look like? We’ve listed out the necessary ingredients so you can launch a program destined for success.

What is Self-Service BI?

Self-service BI is a subset of business intelligence, the collection and analysis of data relevant to your business’s interests. The self-service variety enables users from many departments or divisions within an organization to develop their own insights by gathering the information they need without having to wait for assistance. But even this flavor of BI relies on data analysts and other IT personnel to facilitate.

Know Who You’re Serving

Knowing your users — all of your users — is the first step to creating your self-service BI strategy. You won’t be able to predict how every user will interact with the data reports or how far into the weeds each particular person will want to get, so the best approach is to plan for all levels of comfort both with the data and with the self-service tool you’re implementing.

Defining every segment of your users based on their skill level is far easier than defining them by, say, by their business role. A newly-minted college grad, for example, might be far more comfortable customizing a canned report into exactly what they need for their monthly conversion report while a seasoned high-level manager might not be interested in learning how to do even the simplest modifications. Don’t sort your users before you even get started — give them the tool, and a variety of starting points, and let them sort themselves.

And again, don’t forget about your information workers behind the scenes! Consider what capabilities they will need in order to connect to data sources, groom data objects for non-technical end users, build canned reports and dashboards, and so on.

Give Your Users Options

Whether they’re data analysts or data consumers, everybody using your self-service BI solution is going to change. They grow, they get more comfortable with their roles, their jobs, their tools. Your strategy must have defined tracks for all user levels, but you also need to give them room to move up and down, leveling up when their jobs demand it and even leveling down when they, say, join the management team. It makes no sense to keep your users in their original skill categories because humans will steadfastly refuse to stand still. Just as you define the upgrades you make to the data software you’re running, you should identify the growth pathways in your self-service BI implementation.

Monitor for Feedback

It’s not enough to set your strategy: you also need to measure how it moves. A plan for monitoring usage will help you pick which directions to take your self-service strategy.

For example, you might notice that one department or customer company is making frequent use of the solution while others have yet to adopt it. With IT’s help, you can diagnose the issue. Perhaps those users cannot find the data they need, or maybe the reports they reference are loading too slowly because the filter settings are incorrect.

Whatever the concern, monitoring will help you identify opportunities to ensure that everyone is benefitting from your self-service BI implementation.

Refine and Iterate

Your plan will have to change. It’s not even a matter of if your plan changes; it’s a matter of when and how much.

There are dozens of fluctuating variables to consider as you scale, including but not limited to:

  • Changes in user demographics
  • Capacity of technical resources
  • Budget for additional servers
  • Incorporation of new data sources
  • The release of new analytics features

So although it might be tempting to spend fitful hours wishing your initial implementation could accommodate such changes, it’s best to simply adapt your approach to the new reality. Keeping agile is the final key to a successful self-service BI strategy. If you are attuned to your audience, giving users a variety of analytical tools, keeping tabs on their experience, and prepared to adjust as needed, your self-service BI will delight, like a perfectly baked soufflé.

Want to learn more about data analytics through baking metaphors? We’ve got you covered with this infographic on live data best practices.

Originally published with Analytics Insight.