Data Utilities — The Business Model Built for Speed

“[Jay] Forrester’s insightful observation that organizational structures and governance need to change in order to meet rapidly changing technologies and social needs is as relevant today as it was in 1965.”[1] Georgianna Bishop, Director Human Resources Development, Environmental Protection Agency 1995

This article discusses a new business model, the Data Utility, and the speed it provides to solve imminent problems such as COVID-19 and environmental sustainability.

Introduction

Entrepreneurship is the conversion of the abstract to the tangible, from an idea to a product or solution that changes human behavior and thereby creates value. Science has shown that the tangible can be explained in terms of matter, energy and information. Science seeks the basic laws of nature in order to explain these three concepts. Math provides the theoretical confirmation of these laws and engineering gives the science purpose in order to solve society’s problems.

Much of the role of information is based on Claude Shannon’s Information Theory, which is based on the second law of thermodynamics (science) and statistical mechanics (math). The engineering applications of Information Theory provided the basis for a new industrial paradigm. Thomas Kuhn’s seminal work in the philosophy of science shows us that a paradigm is achieved when multiple new technologies combine to solve multiple problems in multiple industries. “In the second half of the 1940s a four-part revolution took place in information theory (Claude Shannon), logical computer design (John von Neumann), semiconductor physics (William B. Shockley and Walter H. Brattain), and the establishment of a new, integrative science called cybernetics (Norbert Wiener).”[2] This “revolution” or paradigm launched the Third Industrial Revolution (3IR) and the Computer Age.

What Shannon did was to provide the theory for the management of information in digital form. Starting with the simple distinction between signal and noise, he introduced error correction and data compression. From these concepts, today the management of information has advanced from early computers to worldwide telecommunications networks, artificial intelligence (AI) and now quantum computing. Shannon’s Information Theory transformed the economic wealth creation model that had been in place for 7,000–10,000 years since agriculture was invented. This first wealth creation model was based on matter, mechanistic fundamentals, labor and capital. Shannon initiated a “phase change” in wealth creation to information, financial engineering, digital processing and capital.

If we trace the history of this new wealth creation model based on information we notice that it continuously builds on other fundamental principles such as time, space and network. Real-time customer experience is based in the Internet and smartphones. Airbnb’s model is based in a two-sided marketplace of owner and renter information that enables real estate (space) to be redefined. The Internet of Things (IoT) is reinventing the network with information capture through sensors located everywhere including the human body. In all of these examples, we see the same pattern that retired Stanford Professor Brian Arthur predicts in his classic, The Nature of Technology. To paraphrase Arthur, a new technology emerges to solve a problem of the era and frequently a new business model is created.

The current version of a business model based in information theory is the emergence of the network business model that supports platforms (Shopify), marketplaces (Uber) and communities (Facebook). The VC firm nFx analyzed the impact of the network business model and determined that 70 percent of the total market valuation of tech companies (1994–2020) is attributable to the network business model.[3] In hindsight, this statistic is perhaps not so surprising given that networks are present in all natural and manmade systems. To be more objective, this wealth creation would also not have been possible without artificial intelligence, advanced database technology and real-time operating infrastructure. All of these technologies are also based on Shannon’s Information Theory and demonstrate an evolving paradigm.

Today, again the business model is beginning to change. Tim Koehler at Santa Fe Institute teaches us that before society can advance to the next level, we need to develop the tools to manage information at the next, more advanced level.[4] For that reason, an advance in information technology is an important part of every industrial revolution. Newspapers in the First Industrial Revolution (IR), radio, telephone and movies in the 2IR and computing in the 3IR all document the point. The next level, the 4IR, is now being defined by the speed at which new information is being created. Whether you see information doubling in years, days or hours, you will be correct within 20–30 years. A new technology paradigm is being developed to manage this exponential increase in information. The paradigm will initially be defined by Artificial Intelligence, cloud computing and IoT. IoT captures the information at the “edge” of the network, cloud computing provides the tools to collect and store the information in real time at almost any scale and AI provides the analytical, modeling and simulation tools to find knowledge in the information.

However, as we notice in the 3IR, the Computer Age, the computing paradigm advanced over time to solve new problems in new industries. Therefore, it is logical to expect that the paradigm of the 4IR — AI, Cloud Computing and IoT — is going to evolve further. Irving Wladawsky-Berger describes this evolution well, “… these technologies are general purpose in nature, they require massive complementary investments, such as business process redesign, co-invention of new products and business models, and the re-skilling of the workforce.”[5] The MIT Sloan Management Review writes about a digital ecosystem where companies partner to perfect their business models[6], a LEGO-like approach to designing a business model. This type of business process redesign is going to produce what I call Data Utilities. Consider a power utility. The business model is quite straightforward. You build an infrastructure to deliver power over a network and you connect different components of power — steam, hydro, nuclear, solar, etc. Now if we think of the evolution to the next paradigm, I think we can understand those new business models also in terms of infrastructure, network and components. The infrastructure will be a data infrastructure, something similar to the McKinsey diagram below. All of the tools to collect, clean, integrate, store and process data will be combined with cloud computing (for instant scaling) and algorithms for analytics, modeling and simulation. This is where the company will create the value and the defensible proprietary innovation. The design of this infrastructure will also create additional advantage in the speed with which the infrastructure can be deployed successfully for new purposes or opportunities. The network will connect customers, suppliers and/or collaborators for seamless, friction-free sharing of information and knowledge in real-time. Components can be understood as the lines of business supported by the infrastructure. All the different types of marketplaces and services (lines of business) at Amazon are supported by the same versatile data infrastructure. Components can also be thought of as the uses for the infrastructure. For example, to analyze interventions (vaccines), treatments, or preventative measures for a disease, Moderna’s uses the same infrastructure to research different applications of their mRNA technology. As we can see, this approach is made possible by the versatile infrastructure repurposed through new components for the next problem and business opportunity.

Each component, or a line of business, would be bolted onto this all-purpose infrastructure. In the case of applications in biology or materials science, the data infrastructure might be modified to more closely match the diagram from a16z below.

We can unpack the concept of the AI Utility. With its versatile infrastructure to address multiple problems and create multiple lines of business, this business model is built for speed. This is the speed to react to new opportunities, to make better use of the vast amounts of information being collected in real-time and to innovate before competitors. Moderna’s ability to develop a COVID vaccine in just two months, compared to the former multi-year model, was a wake-up call to the world. We now have the technology and business models to solve problems at speeds never seen before. Now you know why Amazon is such a juggernaut of new businesses. They only need to pick the opportunity

they want to tackle, the data infrastructure and network is largely already in place. This focus on speed also explains the emergence of a new generation of high performance computers. According to AMD, “the El Capitan supercomputer is expected to be the fastest in the world when it comes online in 2023. It is so fast that it would take eight years if all 7.7 billion people on Earth each completed one calculation per second to do what El Capitan can do by itself in one second![9] This computing speed will provide the processing power to handle huge exabyte data sets, which will be required to successfully develop solutions to the critical problems of climate change, material science, medicine, agriculture and perhaps even wealth inequality.

Whenever technology changes the standard for solution time from days to hours or hours to seconds, the technology produces foundational changes for society. For example, photography changed the time to create art or a remembrance and quickly achieved worldwide adoption. Txt and email both revolutionized messaging by changing delivery time to instantaneous. Google Search did the same thing for information. If the tools appear to solve the problems as Bryan Arthur teaches, then perhaps it is not surprising that new data management technologies, computing equipment and business models all designed for speed would appear now as we face the most daunting problems in human history.

[1] https://www.google.com/search?q=REFLECTIONS%2C+Volume+1%2C+Number+3&rlz=1C5CHFA_enUS772US772&oq=REFLECTIONS%2C+Volume+1%2C+Number+3&aqs=chrome..69i57j33i299.1158j0j7&sourceid=chrome&ie=UTF-8

[2] https://www.nature.com/articles/d42473-018-00286-8

[3] https://www.nfx.com/post/frameworks/

[4] https://www.nature.com/articles/s41467-020-16035-9?fbclid=IwAR3IRJcRhSpprYf00TwNepqjZrIXIL_Al-DdHwVci72LhbSf5NkHzt0P2cA#:~:text=We%20find%20that%20sociopolitical%20development,by%20further%20increases%20in%20scale.&text=Polities%20diverge%20in%20socio%2Dpolitical,Threshold%2C%20but%20reconverge%20beyond%20it.

[5] https://blog.irvingwb.com/blog/2021/04/the-increasing-economic-value-of-digital-capital.html

[6] https://mitsloan.mit.edu/ideas-made-to-matter/3-ways-digital-initiatives-create-value

[7] https://www.mckinsey.com/~/media/McKinsey/Business%20Functions/McKinsey%20Digital/Our%20Insights/How%20to%20build%20a%20data%20architecture%20to%20drive%20innovation%20today%20and%20tomorrow/How-to-build-a-data-architecture-to-drive-innovation.pdf?shouldIndex=false

[8] https://a16z.com/2021/01/08/platform-disease-fit/

[9] http://www.nextplatform.com/2021/04/26/high-performance-computing-will-power-the-next-normal/

--

--

Director StartUP FIU-commercializing research. Entrepreneurship Professor FIU, Ex IAP Instructor MIT. Ex CFO One Laptop per Child. Built billion dollar company

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Robert Hacker

Director StartUP FIU-commercializing research. Entrepreneurship Professor FIU, Ex IAP Instructor MIT. Ex CFO One Laptop per Child. Built billion dollar company