A subset of your application’s users – call them analysts, power users or techies – will immediately grasp the value of ad hoc analytics and make it useful for their reporting needs. This may be the top 20% of end users if you’re lucky. But there will always be a larger population of casual end users who also need ad hoc reporting. You cannot ignore their needs and expect them to see self-service analytics as a valuable element of your application. So the question becomes when launching self-service analytics in your application, how do you get these users on board?
You need to budget time for training them. Other priorities for your company and its application’s end users mean that training does not always deliver what is necessary for success. Here are some ways to mitigate this during your rollout of self-service reporting.
Add Context to Guide Users
Categorize your application’s end users not only by their role (power user or casual user) but also by the type of data they analyze. This minimizes the cognitive load they face when learning a new tool. To keep their focus on the software, don’t train users in one vertical using data from another. It’s unfair to expect a user who has spent years gaining a deep familiarity in the EHR field to learn how to create reports using logistics data.
Don’t attempt to train all users in all things. Resist the temptation to explain every widget and setting in the application. A better option is to explain the big picture – the actual boundaries of functionality that a role has, what they can and can’t do. Sometimes all an end user is missing is some context, such as the relationship of one database to another.
It is hard for IT to give up ownership of this information or even understand the gaps in user knowledge. It can help to document in concrete terms the relationship between different data sources used in reporting. This does not have to be a discussion of the intricacies of inner and outer joins. It could be as simple as how primary and secondary keys associate data across commonly used tables.
Focus Training to Minimize Frustration
Do not expect a classroom-style training session to be a good solution for all users. Generally, long training sessions breed failure. Instead, focus on getting users to immediately log on and use the system after training. If possible, turn on logging to report on actual system usage to ensure they are using the solution.
A separate training environment is helpful. A small subset of production data makes it easier to understand visualizations or to tell if a query works as expected. Applications that report against data covered under compliance restrictions like HIPAA may require this approach. Users will feel more comfortable creating their first reports in this environment. Consider rolling out reporting functionality in stages to give users a chance to digest it.
Employ Multiple Ways to Familiarize Users with the Application
Identify power users in the organization for training or as a resource to “train the trainer” within their departments. If no in-house experts or power users exist on day one, consider allocating time for an on-site technical resource to answer questions and gather feedback. Documentation is usually a casualty of a phase one rollout. This is not always a huge loss – these users don’t typically have time to research a problem. They most likely will just default to old habits for reporting.
There are alternatives. Many SaaS applications use a daily email cadence to deliver training to new users in short, digestible tips. This familiarizes users with common reports and dashboards instead of overloading them on day one. An email could prompt users to view common KPIs on a new dashboard or to drill down into a report for details that legacy reporting could not deliver. Use these emails to ask for feedback as well. Simple competitions or quizzes can get new users to try self-service reporting.
A Starfleet Research survey revealed that 91% of companies “agree” or “strongly agree” that creating organizational alignment [on] a corporate culture that emphasizes data-driven decision making rank as top success factors with self-service business intelligence. Your software company needs to cater to this demand to increase user adoption of your application and its BI and analytics platform.
Don’t underestimate your application’s end users. They probably developed workarounds to help them do their jobs using less than desirable reporting tools. Past failures may have made them skeptical about how a new product can solve their problems. These users may not have time to explore all the functionality your reporting offers. Most likely they have a much greater familiarity with their data than management (for example, identifying outliers in the data).
Seek feedback from them whenever possible. They are your best opportunity to cultivate champions of your application. Ultimately, the success of your application resides with them.