Your Fancy New Analytics Platform Doesn't Matter If No One Uses It

This is not who you are building a platform for.

This is not who you are building a platform for. Nyrok555 /


Connecting state and local government leaders

COMMENTARY | Tools should empower employees, not send them running back to spreadsheets.

Data analytics has the potential to revolutionize the services state and local governments provide to their citizens, with some agency representatives calling it “the most disruptive thing that we have going on.” Clearly the technology has the power and potential to greatly improve agencies’ ability to connect with their constituents and improve people’s lives. But that power and potential may go unrealized if agency employees are not using the data analytics tools at their disposal.

Even with the most visually appealing data analytics tools on the market, if the end user applications and use cases are not designed with the user’s perspective in mind, there is a good chance state and local employees will fall back to using time-consuming spreadsheets. That effectively negates the software’s powerful potential and greatly lowers an agency’s return on investment.

Instead of IT building analytical applications that users may not like or understand, agencies should adopt an employee-centric approach to designing and developing their data analytics solutions. By employing the concept of “design thinking” in building their data analysis applications, agencies can create solutions that their employees will actually want to use.

Putting the User First

Design thinking is based on the idea that the best and most effective solutions are designed with the users’ needs in mind. Think of objects that people use all the time without hesitation—a comfortable pair of shoes, an ergonomically correct chair, or even a toothbrush. These objects are the result of design thinking that put the needs of human beings front and center.

The one thing they have in common is they were created based on an understanding and empathy of users. Their creators researched how their customers acted and felt and what they wanted, and designed solutions around their needs.

Agencies can do the same as they begin developing their data analytics solutions. They can start by talking to the workers who will actually use the programs and understanding what kind of solution they would like to use. Then, they can brainstorm new and creative concepts to address those users’ needs. Ultimately they can choose a few of the best ideas, prototype them, and test them and request user feedback. Eventually, they will be able to build and implement the best data analytics solution for the agency and its users—one that will be readily adopted and used on a consistent basis.

Involving Employees Who Actually Use The Tool

The challenge is breaking down cultural barriers and making user-centric design thinking an institutionalized part of the agency. Like all organizations, many state and local agencies have their own ways of doing things. Often, those ways have been the same for many years. Traditionally, that means software solutions are developed by the agency’s IT department and rolled out to the team with very little to no input from users.

This is the antithesis of user-centric design thinking, and it can be extraordinarily counterproductive. I’ve seen IT developers present analytics solutions showcasing decades of data laid out in visually impressive manner, but without any real practical use for end users the solution goes nowhere.  IT thinks it made something great, and can’t understand why it is not being adopted; meanwhile, agency workers roll their eyes at and go back to their old ways of doing their jobs.

Instead of this top-down approach, agencies should involve users at the outset of development. Start by asking some simple questions:

  • What information do you need to do your job that you don’t have today?
  • If you had that, how would you use it?
  • What can be improved?

Bring together users for several hours and truly get to know their challenges. Developing this understanding and connection can help agencies better design data analytics solutions that can directly meet those challenges head-on.

This approach helps users become invested in the solution. If they helped to create it, they are more likely to understand and use it. Then, they are more likely to evangelize and teach it to others within the agency. This can be particularly beneficial to new employees who may not have had the opportunity to be involved in the development process.

Measuring Usefulness

Getting users on board is only the beginning. Just as agencies should use data analysis to improve citizen services, they should also create action plans for continuously analyzing the user engagement and adoption of their software applications. Soliciting user feedback and monitoring usage rates and patterns on a consistent basis can help agencies determine if any adjustments need to be made to ensure that the applications continue to meet employees’ needs.

User-centric design thinking has been around for a long time, but it remains a relatively nascent concept in the public sector. Its benefits, however, are very real for state and local agencies. Those organizations have a great opportunity to adopt design thinking and use it to get the most out of their data analytics programs—and their employees.

Jake Bittner is CEO of Qlarion.

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