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Public Interest Technology: Design, Data and Delivery of Government Solutions

The views expressed are those of the author and do not necessarily reflect the views of ASPA as an organization.

By Bill Brantley
May 15, 2021

“There is no solving the world’s hardest problems without governments and institutions that really work for people,” writes Tara Dawson McGuiness and Hana Schank in their newly-released book, Power to the Public: The Promise of Public Interest Technology (2021). McGuiness and Schank argue that governments can better solve challenging problems through public interest technology which they define as the, “Application of design, data and delivery,” to build or rebuild government services.

Both authors worked on high-profile digital technology projects during President Obama’s administration, including implementing the Affordable Care Act. Along the way, they’ve learned great lessons in how to effectively use design thinking, data analytics and agile project management to create effective government solutions. They developed three principles that guide public interest technology:

  1. Government must be part of solving the world’s most challenging problems.
  2. Technology plays a critical role, “But it is never the solution alone.”
  3. The government’s role is to help all people.

Governments solve problems through the cycle of design, data and delivery. If the design, data and delivery cycle seems familiar, it is the lean startup methodology applied to government operations. The authors stress that design, data and delivery are, “Interlocking tools that, when taken together, form a model that seeks to have a transformational impact.”


McGuiness and Schank advocate starting with an, “Informed design that places humans at the center of the policy process.” They use the example of a 42 page form that the state of Michigan used to grant emergency help to citizens. Using design thinking principles, a team of public interest technologists reduced the form’s size by 80%. The time needed to complete the form went from over 45 minutes to under 20 minutes.

Two highlights from the case study are how the team had a group of senior officials complete the old form in 20 minutes while seated in a noisy office. Then, the senior officials were walked through a 100-foot journey map that detailed all the steps in processing the application. These two steps engendered empathy in the senior officials for the applicants who must face the 42 pages of the form before they can receive help.

The design part of the book reminded me of my training in design thinking at the Office of Personnel Management’s Lab. We taught how to develop empathy for stakeholders and customers through interviews, observations and journey mapping. You need first to understand the process and refine it before applying technology. Otherwise, you automate a bad process which will make things worse for the citizen.


Governments are great at creating and collecting data. I’ve worked at the Social Security Administration, General Services Administration, Office of Personnel Management and U.S. Patent and Trademark Office to create or analyze massive datasets. I’m building yet another metrics program around training in my current job at the Navy Inspector General Office. However, the kind of data McGuiness and Schank mean is, “Real-time data to identify solutions and establish success metrics.”

For example, think of the 42-page form. Success metrics involved reducing the number of questions and time to complete the form while still meeting the 1,700 pages of regulatory requirements of five benefit programs. Like the lean startup methodology Measure component, data is created from the customers’ (or citizens’) interactions with the new designs. The data is analyzed to guide the further development of the design. The team streamlined the form significantly using the data from the 42-page form redesign. The sequence of designing and testing the design through user data is essential to the design-data-delivery cycle.


The third part of the public interest technology process is, “Running pilots before scaling.” Building prototypes is my favorite part of design thinking because this is where you create solutions. The empathy exercises and data collection are vital, but running pilots is where you get the richest information, especially if you take McGuiness and Schank’s advice to, “Build with,” your customers.

As an information technology project manager early in my career, I have been guilty of building software applications around what I thought was best for the user. Many public servants are dedicated employees with the best interests of the citizens in mind. However, they don’t have the life perspectives of the citizens they serve. Empathy is vital in all three parts of the design-data-delivery cycle.

Careful and Iterative Approach Versus the Big Bang Approach

A fundamental tenet of public interest technology is, “Start small, learn, improve and scale.” The case study of redesigning Vermont’s state benefits system (pages 43 to 55) is an excellent example of using small pilots to learn and improve before scaling up. The Vermont case study is also a cautionary tale of how public interest technology projects can fail due to the turnover of senior management and/or events such as the COVID-19 quarantine. Big Bang approaches have the appeal of rapidly solving problems. Still, the authors make an excellent case for the careful, iterative method of the public interest technology’s design-data-delivery cycle.

Author: Bill Brantley teaches at the University of Louisville and the University of Maryland. He also works as a Federal employee for the U.S. Navy’s Inspector General Office. All opinions are his own and do not reflect the views of his employers. You can reach him at http://billbrantley.com.

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