The Importance of Networks: A Lesson Learned from the Pandemic

“…there are still massive challenges we’re ill-equipped to meet, as evidenced by climate change and the COVID-19 pandemic, which have shown that we are yet to understand the complexity of nature.” Scientific American April 16, 2020

Scientific American frames the current problem well — we do not yet understand nature. The other way that they could have said it is that we do not yet understand the relationship between natural and manmade systems or the relationship between natural and designed systems or maybe even the difference between natural and synthetic systems.

The nature of these two-sided systems has also been the topic of much recent writing on the pandemic, and if you followed it, you now have heard of complexity science or complex systems. Complexity science is a framework that demonstrates that all natural and manmade systems can be explained by the same set of principles. Everything from slime mold and ants to commodity markets, organizations, pandemics and biospheres can be explained with the same concepts from complexity. Arthur Eddington, the renowned physicist, is frequently credited with birthing complexity in the first half of the twentieth century. Nobel Laureate Herbert Simon did a defining article, “The Architecture of Complexity”, in 1962. In the last few years BCG, the international consultants, has been advocating principles from complexity as the model for 21st-century management.

This article defines complexity, explores the critical role of networks in complex systems and then shows the importance of stacked networks as a better means to define an organization and manage it.

Complexity is defined differently by almost everyone who seriously studies it. I think it is beneficial if we define Complex Adaptive System (CAS) and ignore here complex physical systems such as volcanos. I think there are five characteristics of CAS that are important and agreed upon by almost everyone.

1-Emergence

Unexpected outcomes arise that are not explainable or predictable from the characteristics of the agents and [sub]systems (boiling water turns to gas)

2-Hierarchical

Nested [sub]systems are an integral part of a larger system with no dictated instruction from outside the system (the stomach within the digestive system)

3-Non-linear

Agents have random or chaotic behavior (unpredictable and uncertain)

4-Adaptive

Agents learn or evolve based on information or the related feedback

5-Self-organizing

Agents and [sub]systems are autonomous to achieve purpose

Credit: MIT

If we look at these five definitions, two words stand out and need to be further defined — agent and [sub]system. An agent is an individual component of a system that has the ability to react[1]. A sub-system reflects the hierarchical structure of all natural and manmade systems. Therefore, the term we need to define is “system”. A system is:

…”a group of interacting or interrelated entities that form a unified whole. A system is delineated by its spatial and temporal boundaries, surrounded and influenced by its environment, described by its structure and purpose and expressed in its functioning.”[2]

In summary, a system is a “group of interacting agents” with a structure to achieve purpose. The structure of every system is in one sense a network and the purpose of the network is for the agents to interconnect to exchange and process information. Much as all natural and manmade systems are complex, all of these systems rely on a network for the exchange of information. Information is used here in the richest sense — an apple is insurance and stores information against hunger and a chemical reaction can be explained by information entropy.

The question one might ask at this point is, “why are networks so common or prevalent”. Three concepts explain the widespread presence of networks in natural and manmade systems.

1. Metcalfe’s Law

“The value of a telecommunications network is proportional to the square of the number of users of the system.” — Robert Metcalfe Larger networks are more valuable. Metcalfe’s Law has been generalized over time to explain social networks (although the math has been modified to a logarithmic scale).

2. Assortative Mixing

Nodes of similar size connect.

3. Autocatalysis

Where a process generates an output that initiates the same process again (Google’s original search algorithm prioritized by the number of links to a web page, which then prompted a higher rating for future searches)

These three features of networks explain the presence of networks in all adaptive and manmade systems. Networks are the tool that supports the most basic behavior of sharing in all living things. Network features also explain in part the spread of pathogens at epidemic levels. The pathogens or agents become more and more effective because of Metcalfe’s Law, they are able to spread because humans associate with other humans (associative mixing) and the contagion is auto-catalytic because one agent infects the next agent who then infects others.

From a more positive perspective, perhaps networks provide an explanation for why organisms were able to relax self-preservation and form communities. Communities are built on networks in a hierarchy as complexity would indicate. Communities are information networks. Think of the critical information you need to live in Miami, FL and that is the list of networks that define the city. Geoffrey West’s excellent book, Scale: The Universal Law of Growth…” explains in detail cities as information networks.

A stack of networks is proposed as a model or framework to also understand an organization. An example will illustrate. A university can be considered a community and an organization. A university can also be considered a stack of networks (in bold), where the critical functionality is shown, and their subsystems are in the parenthetical clauses below:

- Students (e.g. undergraduates, graduate students, freshmen, minority student)

- Faculty (e.g. teaching faculty, adjuncts, Visiting Professors)

- Research (e.g. grantors, post-docs, NAS)

- Government (e.g. regulators, accreditation, partnerships)

- Alumni (e.g. donors, continued education, mentors)

- Community (e.g. student jobs, internships, social impact)

- Administration (e.g. accounting, public reporting, student recruitment)

To use the stack methodology, we could first start by defining the current strategic objectives of the university. Hopefully 3–5 critical deliverables (and not 20 or 30). Then for each major network shown above, we would first identify the subsystems of that network that we think are critical to the strategic objectives. For example, if we had a strategic objective to achieve a more diverse group of researchers, we might identify any networks for students, faculty and researchers that support diversity around sex, gender, race, origin, etc. Analyzing these subsystems would lead to identifying the missing, underutilized and active subsystems that might need to operate well to achieve diversity and need more funding. We could continue to take this sort of analysis to more and more detailed levels, depending on how you identify value.

Another way to further the analysis of the subsystems is to consider which create value, which deliver value and which capture value (Porter, ME (1979)) in a particular network. Shortcomings in any of the three value activities might lead to further analysis to better understand how the network supports the overall strategy or a particular objective. If it is a key network, it should support the strategic objectives.

You could also use the network stack methodology to define the organization’s mission and then define the required networks in the organization stack. In the next article I will apply Porter’s teachings on value and the network stack methodology as a means to develop and manage a startup company.

“After you have exhausted what there is in business, politics, conviviality, and so on — have found that none of these finally satisfy, or permanently wear — what remains? Nature remains; to bring out from their torpid recesses, the affinities of a man or woman with the open air, the trees, fields, the changes of seasons — the sun by day and the stars of heaven by night.” Walt Whitman Credit: Brain Pickings 04–19–2020

[1]https://www.complexityexplorer.org/explore/glossary?utf8=%E2%9C%93&explore_glossary_collection%5Bsearch%5D=agent&commit=Search&explore_glossary_collection%5Bsearch_descriptions%5D=0

[2] https://en.wikipedia.org/wiki/System

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

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Robert Hacker

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