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Government Innovation Is Hard Because There Is No Direct Path to Innovative Solutions

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

By Bill Brantley
April 14, 2019

What makes innovation, especially in the public sector, so difficult? Two recent books may give the answer. The 2015 book, Why Greatness Cannot Be Planned  by Stanley and Lehman, argues that setting strategic objectives is useless and even counterproductive to achieving innovations. The 2019 book Loonshots by Bahcall uses the history of groundbreaking accomplishments to explain how dismissed ideas came back to create significant breakthroughs. But, to put both books in perspective, I’ll discuss an earlier column  that addresses innovation.

Fitness Landscapes and Innovation

Complexity Economics, and Government Innovation described how 30 federal agencies were working with the General Services Administration to create solutions using cognitive computing, chatbots and blockchains. I suggested that Dr. Beinhocker’s complexity economic theories could aid agencies in building new digital innovations. Specifically what could aid innovations is the competition between government program business plans (BP) that comprise physical technologies and social technologies.

According to Beinhocker, you can place the competing BPs on a fitness landscape. Imagine a physical landscape where you have both valleys and mountain tops. The BP tries to climb the highest mountains while avoiding the valleys. The mountain tops represent the highest levels of fitness (or success) while the valleys represent low levels of fitness (or failure). 

“According to Dr. Beinhocker, successful BPs have the right mix of physical technologies and social technologies that work together to effectively and efficiently execute the strategies and processes of the BP. The purpose of economic evolution is for BPs to continually refine the mix of technologies as the BPs interact with other BPs in the market.”

Stepping Stones to Innovation

Stanley and Lehman used the fitness landscape metaphor to create an artificial intelligence program that would evolve images. The concept was to seed the landscape with random patterns. Then, every round, people would pick an image that somewhat resembled a real-world object. The selected images would then take another turn of random inputs until the final pattern was considered a close representation of a desired image.

What Stanley and Lehman’s discovered is that having a strategic objective prevented innovation. This is because the images between the initial random image and the final image looked nothing like the final image. These in-between images (designated stepping stones by Stanley and Lehman) were not predictable based on the objective. For example, the final image of a car was initially called the alien face because the image had large froglike eyes that later became wheels.

An analogy that Stanley and Lehman refer to is how modern computers built of microchips evolved from earlier computers composed of vacuum tubes. Microchips bear no resemblance to vacuum tubes, but it was the creation of vacuum tubes that helped spur the invention of the transistor that ultimately led to microchips. The authors write that “[b]eing open and flexible to opportunity is sometimes more important than knowing what you’re trying to do.”

How The Science of Phase Transitions Leads to Breakthroughs

Bahcall is a biotechnology entrepreneur and worked on President Obama’s council that studied the future of national research. He traces the history of inventions like radar, statins, the Boeing 747, Pixar and the Polaroid instant camera.  He found that the, “Most important breakthroughs come from loonshots, widely dismissed ideas whose champions are often written off as crazy.” Paradoxically, once the breakthrough has been validated, it takes a large group of people to make the breakthrough successful. The key is to provide a structure that transitions between a loose structure that encourages loonshots while being rigorous enough to build the final product.

Radar is a good example. The discovery of how radio waves reflected from objects was one serendipitous event in which a scientist was studying one set of phenomena when something surprising happened. When the scientists demonstrated how radio waves could detect ships traveling through fog, darkness or a smoke screen, the U.S. Navy was not interested. Radar, which was discovered in 1922 was still being tested in a small, poorly-funded experiment on December 7, 1941.

It took a visionary manager, Vannevar Bush, who created an army of scientists to create “crazy ideas” to win World War II. His genius, affecting both teams of scientists and soldiers, allowed for the free flow of innovations and feedback turned into workable products (Bahcall terms the product teams as “franchises.”).

Government Innovation Means Successfully Traversing the Fitness Landscape

Based on the lessons of complexity economics, the science of stepping stones and loonshoots, there are three steps that government innovators can take to increase the number and impact of innovations:

1) Approach programs as a mix of physical technologies and social technologies. The key is to continually experiment with the combination to help in climbing the peaks of the fitness landscape.

2) Realize that the intermediate steps of innovation will not resemble the final innovation. The key is to take advantage of the opportunities presented by the intermediate steps.

3) In creating the final innovation, make sure there is a good balance between nurturing the innovation while empowering the team that will form the final product.


Author: Bill Brantley teaches at the University of Louisville. He also works as a Federal employee for the U.S. Patent and Trademark 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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