Rick Klau, chief technology innovation officer, and Phoebe Peronto, deputy chief technology innovation officer, shared some of their takeaways during the 2022 NextGen Government Virtual Training Summit May 11. The session was called “Public Entrepreneurship: How to Innovate within Government and Bring New Ideas to the Table.”
“At its fundamental level, public entrepreneurship is really the process of introducing innovation on the generation and implementation of new ideas into the public sector,” Peronto said.
While she noted that bringing new ideas to the table can be a daunting task, it is becoming increasingly critical as the public has come to expect more from government.
One example Klau described was the introduction of the digital vaccine card. When COVID-19 vaccines became available, Klau said the limitations of the paper record were made apparent. Not only was the paper record easily lost or damaged, but it was easily forgeable.
The potential to create a digital alternative was introduced early through a memo. This would allow venues to open back up with reduced public health risk through the use of a more easily verifiable record. And while conversation was encouraged regarding what the target outcome would look like, the specifics of the solution were left to the design and development team.
That initial memo was circulated in April 2021, and by May, the code was being written. The digital vaccine record was available to the public within six weeks.
Since the launch, the state released the code that had been developed to the public domain in September so that other states could implement or adjust it for their own needs. Now, Klau said over 80 percent of the U.S. population have access to the same digital COVID-19 vaccine record QR code.
The key takeaways from this experience, Klau said, were to ask questions early, get agreement on the ideal outcome and then empower a dedicated team to find a solution to reach that outcome.
Another example of public entrepreneurship was the state’s shift toward digital forms. This project, Peronto explained, started with a survey, enabling stakeholder engagement about the issue and outcome early on. By asking how many forms exist, how many residents are impacted and how much taxpayer money goes toward administering the forms, it was easy to make a case for change.
“Data doesn’t lie, and it’s really hard to argue with,” Peronto said. “So when you’re setting up a problem, and it’s a new idea, think of really lightweight, super quick ways to get a lot of data around your product or problem and then synthesize that into a problem statement.”
With the problem outlined and stakeholders invested, it simplified the process of moving forward to find pilot partners and building a minimum viable product, which is the current status of this effort. If the pilot is deemed successful, it will be scaled out to departments and agencies throughout the state.
Finally, Klau described the process of moving the state’s many decentralized websites into one location. For example, one website may be hosted on an internal server while another may be in an AWS environment.
“What can we build that is not just reusable, but leverageable and creates compounding advantage over time?” Klau asked.
The first step to achieving a solution was to define what success would look like. The team was able to start this process with the pages OET maintains. Having the websites in one location enables things like translations of content into other languages to increase accessibility for users.
Peronto underlined the importance of driving decision-making with data, which allows teams to point to the problem in quantifiable terms. She said that “math is a universal language.”
And if leadership pushes back due to risk aversion or a desire not to reinvent the wheel, she suggested thinking of creative ways to get quick wins to demonstrate what a solution’s possible outcome might look like.
She also suggested governments start small. This allows government to minimize risk while teams learn what works and what doesn’t, which can then be iterated and improved to implement solutions on a larger scale.
