All too often the customer experience (CX) that governments cook up for citizens leaves a bad taste in their mouths. Unfortunately, we all know the flavor – old and stale. How do agencies freshen up their recipes and deliver more innovative, satisfying CX to people?
For many government employees, the answer may exist in ignoring their potential for failure. Chief Information Officer (CIO) Dorothy Aronson says that this mindset ultimately helped the National Science Foundation (NSF) create better CX.
“You have to have a ‘what the hell’ attitude,” she said during GovLoop’s ninth annual Citizen Experience & Engagement Seminar Tuesday. “The only real stumbling block is fear of failure. You’re not always going for excellence. You’re just going forward.”
GovLoop conducted Tuesday’s seminar in partnership with Carahsoft. Carahsoft is an IT solutions provider specializing in citizen engagement and CX.
NSF, meanwhile, supports fundamental education and research in non-medical fields, particularly engineering and science.
Aronson said that NSF began innovating improvements to the agency’s CX by recognizing a major problem. At issue was whether NSF’s merit-based review system for federal grants was struggling.
“NSF is like a bank,” she said. “We get money and we give it out to researchers based on merit. We review proposals, or requests for funds. It’s not easy to find experts in all these important fields.”
Aronson said that NSF then proposed a hypothesis for strengthening the efficiency and speed of the agency’s merit-based review system.
“It’s important that you start with something people care about,” she said. “We also had confidence that the problem could be solved. You can’t take a timid approach. All we’re trying to do is solve a problem that’s near and dear to everyone’s heart.”
According to Aronson, NSF’s hypothesis was that artificial intelligence (AI) could help agency staff make important decisions about merit-based reviews within two years. After creating the hypothesis, NSF tasked Aronson with selecting a team capable of testing the proposed solution.
“I had to put together a team so that people would engage [the hypothesis] without fear,” she said. “I had to engage volunteers with a taste for the concern. Is this something people would give up their lunch hours for?”
Overall, NSF’s AI project took six months of testing. Aronson noted that the project’s success involved choosing the right people for the task at hand and keeping costs low.
“You have each person doing the thing that they really want to do and that they’re really good at,” she said. “The people who were doing this loved what they were doing. The enthusiasm makes it worthwhile. Everyone was so engaged that they wanted to do it again.”
NSF’s experience quickly implementing AI for one of its top programs provides other agencies with a recipe for innovative CX. It’s list that includes selecting a key problem, suggesting a solution to it, and then finding motivated people who will test that potential solution using their abilities for the greater good. Aronson argued that with energy and time, agencies can eventually address even the hardest challenges without dreading their financial investments.
“All problems in IT can be solved,” she said. “It depends on how much you’re willing to invest, but they can all be solved. Most people are afraid of trying. Try something tiny or bite-sized pieces [first]. Technology is absolutely the easiest thing to get.”