State government center of analytics goes nowhere without user engagement

"I find your lack of faith in a center of analytics disturbing." Note: This is not the way to engage users. Image by Flickr user Ripster55
"I find your lack of faith in a center of analytics disturbing." Note: This is not the way to engage users.
Image by Flickr user Ripster55

In this third post about a government center of analytics, the focus is on creating an environment that enables successful implementation, and perhaps even more importantly, successful adoption of new analytic solutions. (Check out "Hey, government of [insert state], where's your center of analytics?" and "4 keys to building a state government enterprise analytics system", if you missed them.)

While analytic solutions can bring significant benefit to business decision makers, those benefits are only realized if the solutions is actually used to impact business decisions.  New analytic solutions represent change.  And change can create both anticipation and trepidation.

Questions about how analytics will impact job security, create more work, reveal information that may be less than positive, and other concerns can impact willingness to embrace new technology.  By recognizing these challenges, a center of analytics team can facilitate more successful implementations.

Engage the business users

It’s important to understand the business need and how access and insight to enterprise data can improve an organization decisions and service of citizens. But remember that an agency leader’s, and a front-line worker’s, idea of what is needed may differ.  Acknowledging these different perspectives helps ensure that the right people are involved early and often so the analytics will meet everyone’s needs. Here are some tips to engage business users.

  • Avoid developing analytics for the sake of analytics. Ensure there is measurable benefit for the user.
  • Keep it simple. Fix the critical problems first to show value and then expand to more advanced analytic capabilities.
  • Allow the user to “see and feel” how the analytic solution will work through tool demonstrations and building prototypes.
  • Build an advisory team of end users to ensure the final outcome works well for the user community.

And keep in mind that no analytic solution can replace the knowledge and expertise of the business user.  Analytics cannot make a decision about how to act on a business problem – but it can help equip the business user with the right information to make the decision.

Learn a new language

One of the best phrases I’ve heard was shared by the Oregon Youth Authority when discussing their analytics approach to support juvenile justice reform – “learn a new language”.  The point of the message was that business users of an analytic solution and developers of an analytic solution each speak different languages based on prior experiences and knowledge.  When striving to build a new solution, finding a common new language for mutual communication is critical to the adoption and integration of a new solution into business processes.

If the users of the solution find it challenging or frustrating to use, if they haven’t been involved in learning the new language of the solution, they will return back to what they’ve always known and the solution may become shelfware.  Regular, iterative engagement, training, and education can help institutionalize the new language, increasing the chances of the analytics becoming embedded in business process and changing business outcomes.

Operationalize the result

A focus on change management can help organizations understand how analytics will help make current processes and searches for information data more efficient.  Who wouldn’t want to be freed up from tedious administrative tasks to focus on more challenging and meaningful activities?

But that line of thinking can change slowly. Training and adoption efforts should be a planned and iterative activity.  Find the champions and innovators in an organization – those people who like a new opportunity.  Tap into their enthusiasm to encourage others.  Pilot the solution to work out the kinks before deploying to a more expansive user community.  These activities can help identify, mitigate and resolve inhibitors to usage of the new solution.

Learn, refine, repeat

Finally, recognize that developing and using analytic solutions is a learning process.  Once the user community can use their analysis, they begin to understand what else they might be able to do with the data.  Models are refined, new processes developed and additional data sources added.  Analytics allows us to be proactive, creative and better informed.

Watch for the final post in this series about finding the value in analytics!


About Author

Kay Meyer

Principal Industry Consultant

Kay Meyer is a Principal Industry Consultant working with SAS’ State and Local Government practice. She brings experience, best practices and strategies to help states establish Centers for Analytics for Government Advancement. Prior to joining SAS, Kay spent 18 years in state government and led the efforts in North Carolina to set the strategic vision, definition and implementation for the North Carolina Government Data Analytics Center. Kay also led the formation of NC’s first enterprise fraud, waste, and improper payment detection program, as well as the implementation of the state’s first integrated criminal justice system, CJLEADS, which supports over 27,000 criminal justice professionals statewide. Kay holds a Bachelor of Science in Management Information Systems from the University of Virginia and a Master of Business Administration from George Washington University.

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  1. Pingback: Measuring benefits of a state government center of analytics - State and Local Connection

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