Photo credit: Nelson Designs https://www.youtube.com/watch?v=jOrwlhBNu3Y
Takeaways:
Technology attempts to solve problems of matter, energy, space, or time,
To apply technology to mental health and emotional problems, look to make the abstract tangible
Some of the best entrepreneurship was the conversion of abstract aspirations into tangible solutions
I have been working recently with a talented young professor on commercializing her mental health idea based in AI. This is just after finishing up a medical device project to design a wearable for monitoring symptoms of a particular disease. Both of these projects have the same challenge, and it is the biggest challenge in healthcare. Both company solutions have to change human behavior in order to have any benefit of value and that is a hard problem. It is also why so much of healthcare is so ineffective and eventually wasteful.
The question becomes why do some technologies in healthcare (and any industry) succeed and others fail. Yes, sometimes we get the problem wrong or the solution, but less well recognized is that the technology itself may never be purposeful. As stated so well in the blog Code Simplicity:
“In general, when technology attempts to solve problems of matter, energy, space, or time, it is successful. When it attempts to solve human problems of the mind, communication, ability, etc. it fails or backfires dangerously.”
If we look at the categories in healthcare with notable commercial success, we easily arrive at diagnostic devices and pharmaceuticals. Diagnostic devices give us a window into the human body (matter and energy) and pharmaceuticals change matter. If we look back at my two examples from the first paragraph, how could we turn changing human behavior challenges into problems of matter, energy, space and time. Although my solution follows, it should perhaps not be overlooked that these four factors related to technology mirror fundamental concepts from physics.
When we think about changing human behavior through healthcare technology, this is akin to taking abstract problems and making them tangible. If you are not following, remember Schopenhauer’s insight into art:
“Art makes the emotions tangible.”
Art is in effect a technology that translates the abstract emotion into a tangible form in matter. If we consider Maslow’s hierarchy and the highest level of satisfaction—self-actualization or aspirations, we realize that some of the greatest commercial successes translated abstract aspirations into tangible solutions. One might argue that the iPhone, the Model T Ford and photography made tangible respectively creativity, freedom of movement and self-esteem (at a whole new level).
If we can translate an abstract problem, changing human behavior, into something tangible, then we can apply the logic of the four factors from physics and effectively use technology. An example may help to illustrate. Before money we had barter, but in order to transition from barter to money what was the abstract thought that had to be made tangible? Value! Coins were the tangible vehicle, gold showed physically value and the monarch’s picture created trust (all consumer behavior is based on trust). If you did not notice we also just proved that money was a technology. Every change in money—bank accounts, credit cards, derivatives, etc.—were all changes in the tangible form of money. If you cannot see money as a technology, read Daniel Goetzmann’s excellent book, Money Changes Everything: How Finance Made Civilization Possible.
Now to consider how to use our abstract-tangible model in healthcare, lets think about smoking cessation. Suppose we put a $25 device on your wrist, which is only removable by a device that costs $500. The wrist device loudly alarms when it smells any smoke including cigarettes. We could add a CO2 monitor as well to add value for the customer. A loud embarrassing alarm would translate the desire to stop smoking into a tangible energy format—sound waves—and increase the likelihood to stop—especially if the smoke alarm continues throughout the entire cigarette. Chantix beware!
I like the concept of alarms to transfer intangible concepts like emotions and behaviors into tangible sound waves. With all the AI, sensors and cyber-physical research underway, many behaviors could eventually trigger alarms. I am sure there are other ways to make tangible desired behaviors, but the alarm illustrates the point. I think it is more energy efficient and effective than shocks on the wrist. The point, we only need some creativity around the solution to use the abstract-tangible framework in healthcare.
This is a supplemental reading list I prepared for an 8-hour course in entrepreneurship that I was asked to create. List includes videos, Powerpoints, articles and books.
Most of my books and major writings are prompted by a single comment or sentence that typically leads to two or three years of thinking about the related topic. This article is no exception and was prompted by a writer’s observation that every startup is based on a key assumption about the problem, the solution and scaling. These three assumptions can be simply illustrated by a proposed new medical device. The key assumption about the problem is whether the device correctly diagnoses the disease. Key assumption about the solution is whether doctors will use the device (and stop using their current approach). Key assumption about scaling might be getting FDA approval or Medicare reimbursement for a procedure using the device. It should be noted that once a key assumption is identified, it often leads to identifying other key assumptions about problem, solution or scaling. Such clear identification of assumptions also frequently focuses the entrepreneur on the viability of the business concept. The usefulness of this three-part technique and its easy adoption by entrepreneurs lead me to further study the concept of assumption.
Studying about assumptions, I realized that assumptions are one of those concepts that are critically important but with only limited writings on the subject. I see information theory, networks and incentives, as examples, to be similar subjects — critically important in multiple disciplines but almost ignored in popular and academic writing. While some would argue that these topics are widely written about by academics, I would point out that the themes in the academic articles have no practical application. For example, in information theory the positive asymmetry of information was presented by Kirzner to explain entrepreneurship and the negative asymmetry of information Spence used to explain poverty. However, I rarely see any discussion of asymmetry of information in the writing on poverty. The absence of writings on assumptions prompted me to write this article in an effort to facilitate practical applications about assumptions in entrepreneurship and related fields such as innovation and engineering.
While many terms have domain specific definitions or usage, especially in social, economic and political fields of study, “assumptions” is a term that remains unchanged as it crosses disciplines. Another concept that crosses domains unchanged is symbolic logic. Symbolic logic is a system of inference rules that dates back to Aristotle. What does the system of inference rules manipulate? Answer, the propositions, premises or assumptions in the argument. The entire nature of symbolic logic is domain agnostic and therein lies the “proof” for the first characteristic of assumptions — assumptions are domain agnostic, not changed in their behavior or definition by the domain. A simple example might clarify this point. A “set” in math is a “collection of individual objects which is itself an object” whereas in tennis a “set” is “the first player to win six or more games by two more games than the opponent, where a majority of sets alone determines the winner”. Obviously “set” is a domain specific term and “assumptions” is not.
The discussion of symbolic logic above reminds me of an important point. We cannot discuss assumptions without some references to philosophy, math and physics. George Polya, credited with coining the phrase “random walk” and a famous Stanford math professor, was once asked, “why did you study math?”. He responded, “I was too good for philosophy but not good enough for physics”. Any discussion of assumptions needs to include some philosophy, math and even physics, although the math and physics are very elementary and the philosophy may not even be identified as such. What is the significance of thinking about assumptions in terms of philosophy, math and physics? Philosophy, math and physics are the three ways to describe reality and the role of assumptions it turns out is a useful concept to better understand reality. This concept is fully developed in Section 2.
While philosophy, math and physics are widely disliked by many students, entrepreneurship and the related concept — social entrepreneurship — are increasingly popular with students at the five universities where I have taught entrepreneurship in various capacities over the last thirteen years. I have also designed, developed and executed two startup incubators and one accelerator in Miami, FL at Florida International University. Before that I built a billion-dollar publicly-traded company in Indonesia in seven years and served as the CFO of One Laptop per Child (OLPC). OLPC was a project that started at the Media Lab at MIT and gave me the chance to teach an IAP course in social entrepreneurship for seven years at MIT Sloan.
My practical experience combined with my academic pursuits have made me a serious student of entrepreneurship. One thing that I have realized is that entrepreneurship is best thought of as a process, whether one uses Eric Ries Lean Startup methodology or another approach. At every step in the process I have learned to identify the key assumption(s), to manage the validation of those assumptions as milestones and deliverables and to be extremely vigilant to not overlook a key assumption (as discussed in Section 4). Leading venture capitalist Mark Andreesseen put it well:
“So you come in and pitch to someone like us. And you say you are raising a B round. And the best way to do that with us is to say I raised a seed round, I achieved these milestones. I eliminated these risks. I raised the A round. I achieved these milestones. I eliminated these risks. Now I am raising a B round. Here are my milestones, here are my risks, and by the time I raise go to raise a C round here is the state I will be in.”
Note that milestones can also be intangible, like assumptions, and that such milestones and assumptions are linked to risk reduction. We will come back to this important point about the linkage between assumptions and risk in Section 3. I first explored the linkage between risk and assumption in my first book, Billion Dollar Company. Companies go out of business typically because they run out of cash. They run out of cash because they misjudge a known risk or miss an unknown risk. Systematically studying key assumptions in a business concept reduces the likelihood of unknown risks and may give new perspective on known risks, which in part explains why I keep writing about assumptions.
This article is organized in two parts, the first dealing with a definition of assumptions and some of their characteristics and the second part presenting some practical applications of assumptions in entrepreneurship…and many other fields. The Sections are shown below.
For the last five years most of my thinking and teaching has revolved around three major areas:
Entrepreneurship
Creativity and learning
Complexity science
Today on Medium I published an essay on these subjects and how they explain many of the large market opportunities that consistently have repeated throughout history:
Yesterday's reading discovered some excellent articles:
Esko Klipi on Medium, "It is only a few network connections away". He points out that networking is growing increasingly important as the Internet shrinks the world. Makes one realize that networks created by people could be more powerful than 20th century forms of organization.
Evonomics.com on inequality, "The Science of Flow Says Extreme Inequality Causes Economic Collapse". What caught my attention was a quote from Robert Reich, "But in The Work of Nations (2010), Robert Reich also points out that the companies that are flourishing through globalization and technology are ones pursuing what he calls high-value capitalism, the high-quality customization of goods and services that can’t be duplicated by mass-produced uniformity at cheap places around the world." I rarely agree with Robert Reich, but I think he is correct this time. I think that corporate governance has enforced too narrow a set of objectives and the executives have opted for the easiest path. BTW, Evonomics is doing an excellent job of trying to redefine how we look at government economic policy with a particular emphasis on complexity economics.
Stanford Social Innovation Review on corporate social responsibility, "Corporate Social Responsibility for a Data Age". In managing disasters much valuable data is behind corporate firewalls and not normally available to the government. The article suggests that the data be made available after the disaster, but it appears more logical to me to pre-position the data.
At 25iq two great articles on entrepreneurship, "A Dozen Lessons on Growth" and "A Dozen Lessons About Product/Market Fit". Just simply one of the best blogs around on entrepreneurship. Step-by-step type detail on understanding subjects that most people misunderstand.
In another of my favorite blogs on economics, Marginal Revolution, "Online Education and Personalized Learning". The article makes the point that in any class there are students performing at many different grade levels. Online learning provides one way for students to follow their own pace of learning. Pace of learning is a big issue that I see rarely addressed. (See image above.)
Aswath Damodaran on ValueWalk, "My Snap Story: Valuing Snap Ahead Of It’s IPO!". Damodaran is a leading academic authority on valuation and Snap will be one of the biggest IPOs of 2017, if it gets away. Sorry, got confused and included a finance article
I do not think I have ever posted my work-in-progress notes on a subject. These are unedited excerpts that I put together from my archive as the first step in a new project. The document attached is on "proof of concept" and how one might think about delivering such a concept. Notes are not complete but there are definitely some nuggets included that go back to 2009. Document is here Download POCC Notes 2017.
This is a chapter from a new book that is almost finished. Comments are most welcome.
The book explores ten large market opportunities that have repeated throughout the last 40,000 years of human history. Every methodology for entrepreneurship that I have studied or taught always assumes an opportunity. I thought it was time to address how to find the opportunity beyond the usual advice to follow your passion.
I increasingly believe that BCG is doing the best thinking and writing on business and related topics, far superior to HBS, Stanford or McKinsey to name a few organizations. In a recent article in BCG.Perspectives, Why Technology Matters, there are two interesting quotes:
"...the energy industry produces the highest income per dollar of technology spending ($24.24). At the other end of the spectrum, the software publishing and internet services industry produces the lowest ($0.98)."
"...in the US, the IT cost per day of a hotel bed is $2.50, and for a hospital bed, it is $65. The IT cost of a car is $323."
My observations on each quote:
Pricing in the energy market is probably the largest wealth transfer mechanism ever devised or to be devised. Increasingly the issue of income inequality comes back to governments that tolerate it or facilitate it.
The low revenue/IT cost in software and Internet publishing is consistent with the relatively low value-add in those services
The IT cost per day figures demonstrate competitive advantage to me and the lower the number the easier it is to use IT technology to disrupt the industry. Airbnb would be an example. BCG does not provide statistics for all industries, but I imagine the number is low for retail also where disruption is rampant. For your next entrepreneurship venture, calculating the IT cost might document the opportunity. Note, it might not document the timing.
I have just returned from teaching a program at Babson College to a group of entrepreneurs from across the U.S. A few observations:
- More and more women entrepreneurs, who tend to be better educated than the men (in my opinion)
- The trend toward older startup entrepreneurs is confirmed in my experience
- Many people innovating in medical care, focused on improving the customer experience through personal approaches (as opposed to digital)
- Much interest in applying technology to improve services for mental health
- Starting to see companies that have developed information management products for the government thinking about how to commercialize these products in the private sector; suggests to me that the government may be ahead of the private sector in information capture and collaboration
- People that offer professional services such as attorneys, accountants, architects are very concerned about their future viability; they lack any method to understand where in the customer service process the value is created
- Everybody thinks they understand the need for cybersecurity, but few people really understand the depth of the issue; affordability is an issue for most SMB (Small and Medium Businesses)
- Most SMB still do not have effective web presence for e-commerce
- Marketplaces are an area of great interest for new businesses; few companies understand the complexity of starting such a venture despite the quality of writing on the business model
One of the domains that is studied at the MIT Media Lab is the use of computers in early childhood learning. Both Marvin Minsky and Seymour Papert said that the computer would only make a meaningful contribution to learning if we could find new ways to learn through the computer. Clayton Christensen from HBS shared the same view in his book on disrupting education. For example, flash cards on a computer was no better than the old paper flash cards. Khan Academy and all the MOOC programs did little to change how people learned (although they had a profound impact on the availability of good teaching).
Today on the AVC blog there is a video interview of film maker Werner Herzog. In the interview they ask Herzog if he is considering to develop movies in VR. Herzog answers that he will not do VR movies.. He says we have to look for new ways to use VR (for it to be valuable).
This concept that we should use computer technologies in new ways got me thinking about AI. Using AI to do data analysis is not all that big an improvement over what humans have done since Descartes. However, using machine learning to do pattern recognition to diagnose cancers is not something humans can do at scale. So on the one hand AI is focused on 20th century objectives with limited real benefit and on the other hand is being used for state of the art medical diagnostics of potentially enormous benefit.
The takeaway is that with new technologies we should look for new ways to use them and not fall into the trap of re-using them in old ways.
I believe that the economic prosperity of individuals can be achieved through individual empowerment and entrepreneurship. Regardless of whether one discusses poverty, equity or the wealth gap, empowerment combined with entrepreneurship provides a solution that offers the most effective approach.
I began studying individual empowerment after I concluded that government economic development programs will never address poverty effectively. The simple reason is that government programs typically focus on government objectives and not individual solutions to problems. I saw this mistake by governments all over the world when I worked at One Laptop per Child.
For individual empowerment to succeed, there are three necessary conditions that must be met for the individual:
If we look at the conditions for individual empowerment, we see that condition 1 frames a psychological requirement. Condition 2 dictates a minimum level of education (FA Hayek thought it should be through primary school). Condition 3 addresses the constraint or boundary that must be overcome.
Now if we think about applying this three-part framework to entrepreneurship for disadvantaged peoples, we might use the same types of conditions:
Trust and sharing (psychological)
Education
Access to capital (constraint/boundary)
(We would also have to provide access to information.)
Condition 1, trust and sharing, would be required to address the worldwide problem of most entrepreneurs--finding good staff. Of course, most of the reason they cannot find the staff is that they have not learned how to trust people, which demotivates staff and prevents delegation. Education would be specialized training on identifying opportunities and execution. Condition 3 would address the limiting boundary--capital. Capital is also frequently cited by entrepreneurs around the world as one of their biggest problems.
I think that many programs fail to address the psychological issues and access to information. Much as the early Head Start programs succeeded when they realized they had to feed the children breakfast, any program to overcome poverty has to address the fundamental issues which include the participants psyche and their risk profile. And, of course, no economic program can succeed without access to information because therein lies the opportunity for the individual to help themself...which brings us back to individual empowerment.
(These conclusions are derived in part from teaching a national program for over 200 small and medium size businesses.)
It has been quite awhile since I wrote about a new market opportunity. I tend to write about opportunities that I think are underappreciated.
Schopenhauer said that art makes our emotions tangible (or real). This unique mission is what, in part, makes the arts precious. Since the earliest days of computing people have been trying to bring this technology to art. However, typically they make the same mistake we see in edtech. If we use technology to duplicate an analog experience, do not expect a different outcome or much user uptake. Music streaming might be the one noticeable exception, but I would argue that streaming makes listening so much more covenient that it is not really an exception.
The power of art is that it changes our perception of reality. Therefore where technology should focus Is in facilitating the understanding of perception. Rather than focusing on the art object--the music, the artwork, etc.--we should be facilitating how the participant interacts with the artist. Fred Wilson's post today, The Online Club, talks about how music performers can get immediate feedback from thousands of online listeners. Certain book sites allow readers to question and converse with authors and a new Miami company, Kurator, will allow purchasers to talk with the artist before they buy one of their works. All of these examples I think highlight a new focus and opportunity for how to change the user's experience with art.
Bloomberg reports that annual art sales alone total $54 billion, before we consider music, literature and film. Ever wonder why the Kardashians have millions of Twitter followers. All of the arts are important to us and we want more personal relationships with the artists. That is the big opportunity where I think people should focus.
In the new book "The Master Algorithm" by Pedro Domingos, the author makes the casual but very telling observation: "all information is statistical". This observation is based on Frank Knight's seminal views on risk and uncertainty. With so much understanding of the relationship between information and statistics, it is surprising there is not more business literature on the role of assumptions in business planning and modeling. A few good articles on the subject that I will use in my graduate engineering class on entrepreneurship are below.
Reasonably confident that Knight influenced Drucker and Drucker influenced McGrath, but I cannot find any documentation. The Hierarchy of Engagement is an article by Greylock Ventures and very practical. The Sequoia article shows the assumptions they made in their You Tube investment.
The Master Algorithm should be required reading for everybody. If you want to understand AI, this might be the only book you need to read. No math in the book.
I will be giving a talk (with an exercise) on "Validating the Idea" for StartUP FIU on Thursday, June 16 at 615 pm at the MARC Pavilion on the Doral campus. This talk will be a good example of the content that we will be giving to teams in the incubator program starting in September. To apply to the incubator, please go to the StartUP FIU website.
I am the Director of StartUP FIU and the strategy is described in this Miami Herald article.
I was reading an article on innovation by some researchers at Santa Fe Institute, "Innovation novelty and impact". The article tries to make a case for innovation matching patent code combinations. This looks to me to be a case of not framing the question correctly. Almost everyone who seriously studies innovation accepts the following definition: innovation is invention commercialized. I saw this definition attributed to a professor at MIT, but many claim to have said it.
This definition of innovation is based in part on the concept that technology and artifacts are created to solve customer and societal problems. Therefore, inventions must succeed in the market to become innovations. (Patents really have nothing to do with innovation except in the antiquated notion that government "licensing" preserves the proprietary nature of the solution.) Innovations create value for customers and allow the business to decide how much value it can capture from the customers.
Bill Aulet from the MIT Entrepreneurship Center discusses innovation in this video.
I am starting to put together the content resources to help the teams in the new incubator at FIU--Startup FIU. Everybody has their favorite book, article or SlideShare deck on pitching to investors. I just reviewed a book from HBR, "Get Backed: Craft Your Story, Build the Perfect Pitch Deck and Launch the Venture of Your Dreams". The book is very well done. Filled with 10-15 examples of good pitch decks, all of which raised money. Also a lot of advice on content, format and design. I have not seen such a comprehensive (and correct) collection of useful advice anywhere else.
We will be accepting applications to Startup FIU hopefully within two weeks and throughout the summer. Students, faculty, FIU alums and the community are all invited to apply. More on this here at SF shortly. A graduating student from Morocco asked if his team could Skype in from Rabat. A meaningful number of team members need to be physically present in Miami to attend weekly events at the incubator. At an event last week we had everybody from high school students to post-docs come to hear the speakers. We welcome applications from local high school students.
Much has been written about entrepreneurship, but the beginning of the process is the least explored and described. In fact, little has been written to describe how one identifies the business opportunity, which sets the theoretical size for the business. I have been thinking quite a lot about opportunities in what will be my third book on entrepreneurship and have identified ten types of opportunities that have repeated throughout history and have always been large "new" markets. The overall framework of such market opportunities falls into three categories:
Human values
Neuroscience (think Kahneman)
Complexity
The reader should note that each category of opportunity represents a basic, almost primitive, understanding of human beings.
What follows is an early draft of a chapter on networks that comes from the section on complexity. I would appreciate any comments, including by email.
"Chapter IX—Networks
“So in the future, ideas will be the real scarce inputs in the world - scarcer than both labor and capital - and the few who provide good ideas will reap huge reward”
The Second Machine Age Brynjolfsson and McAfee
In the last chapter we learned that complex human systems, such as social and economic systems, are non-deterministic, adaptive, self-organizing systems that process and store information. The dynamic tension between exploration and exploitation makes a complex system adaptive. The behavior that cannot be ascribed to any individual part of the leaderless system is the emergent quality of complex systems, which is more easily understood in the context of networks, which are the subject of this chapter.
One classic example of complex systems in both biological and human systems is networks. The term network refers to the framework of routes within a system of nodes. A route is a single link that can be tangible or intangible between two nodes. Networks can be physically constrained, such as transportation systems, or non-spatial, such as certain social and economic systems.
Examples of networks and their role in the history of economic development is shown in this quote from Jean-Paul Rodrigue and Cesar Ducruet’s article, “The Geography of Transportation Networks”:
“Transportation networks have always been a tool for spatial cohesion and occupation. The Roman and Chinese empires relied on transportation networks to control their respective territories, mainly to collect taxes and move commodities and military forces. During the colonial era, maritime networks became a significant tool of trade, exploitation and political control, which was later on expanded by the development of modern transportation networks within colonies. In the 19th century, transportation networks also became a tool of nation building and political control. For instance, the extension of railways in the American hinterland had the purpose to organize the territory, extend settlements and distribute resources to new markets. In the 20th century, road and highways systems (such as the Interstate system in the United States and the autobahn in Germany) were built to reinforce this purpose. In the later part of the 20th century, air transportation networks played a significant role in weaving the global economy. For the early 21st century, telecommunication networks have become means of spatial cohesion and interactions abiding well to the requirements of global supply chains.”
Carlota Perez is a history of economics scholar who has devoted much of her research and analysis to understanding paradigm shifts or more simply put—technological revolutions. In a paper in 2004, “Finance and Technical Change: A-Neo-Schumpeterian Perspective”, she includes a graphic, shown below, that traces each of the major technological revolutions, starting with the Industrial Revolution in 1771. [graphic omitted]
If one examines each example of the “New or Redefined Infrastructures” (Column 3 above), almost every example is a network. If one accepts Perez’s analysis, this graphic clearly demonstrates the role of networks in the history of economic development and by extension in entrepreneurship. (Perez’s analysis shows all the network examples as infrastructure. The other common form of economic or social networks is a marketplace, which we discuss in the next Chapter.)
When one considers an explanation for the close link between paradigm shifts and networks, traditional economic considerations of production, distribution and consumption provide me with no insight. However, if we return to the insights of Ronald Coase, we see economic activity in a less traditional way as a combination of property rights [information], arrangements for collective choice [collaboration/feedback] and contracts for motivating managers and employees [social exchange/signaling]. [Footnote: Coase paper] Stepping back, what one realizes about economic networks is the efficiency a network provides. Networks provide connectivity, communication, operations and management, all in a self-organizing mechanism for information. Networks are nature’s answer to the Swiss Army knife.
Networks are such a “popular” and versatile mechanism for four reasons:
Networks lower the cost of searching for information
Networks lower the cost of verifying information
Networks lower the cost of processing and storing information
Networks lower the friction in exchanging information
Economic and social networks achieve these benefits in part through trust amongst participants, which we discussed in Chapter I. The further disclosure and transfer of information within the network builds the trust and fosters the organizing, processing and archiving of information. Trust also lowers transaction costs, thereby facilitating the construction of larger networks.
Herbert Simon writing on hierarchies [networks] cites three reasons why they are so common [Footnote: Simon 1962]:
Networks facilitate the formation of complex systems (see Metcalf’e’s Law below)
Networks have direct channels of communication (connectivity)
Networks are naturally redundant (lower transaction cost)
Strengthening the versatility of networks is Metcalfe’s Law, which says that networks follow a scale-free power-law distribution. (Every additional node in a network increases the value of the network.) As Albert-L´aszl´o Barab´asi explains it, “This feature [power law] was found to be a consequence of two generic mechanisms: (i) networks expand continuously by the addition of new vertices [nodes], and (ii) new vertices attach preferentially to sites that are already well connected. A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.” [Footnote: “Emergence of Scaling in Random Networks”]
Mitchell makes an interesting point about the size of networks:
“Self-regulation in complex adaptive systems continually adjusts probabilities of where the components should move, what actions they should take, and, as a result, how deeply to explore particular pathways in these large spaces.” [Footnote: Mitchell, Melanie (2009-03-02). Complexity: A Guided Tour (Kindle Locations 2952-2953). Oxford University Press. Kindle Edition]
Mitchell’s probabilities, what might in the vernacular be called uncertainties, are discussed in more detail by JK Galbraith:
"the greater the uncertainty of the task, the greater the amount of information that must be processed between decision makers during the execution of the task to get a given level of performance".
This rather simple observation explains the evolution of “organizations”, which is the subject of the next chapter, and leads to two observations:
In small, resource constrained networks there is usually a large node or organization that dominates
In large networks the need for a large, dominant node is reduced (because of the distributed information processing power)
This relationship between network and the number of organizations [node] explains why early U.S. colonies required a federal government. Conversely, with today’s large, global, interconnected networks, perhaps we can downsize federal government in the U.S.
The relationship between networks and entrepreneurship is only now emerging, mostly due to the growing fields of information theory and complexity economics. However, in some ways the practitioners are ahead of the academics in their understanding of this relationship. Notable venture capitalist Fred Wilson of Union Square Ventures sees the establishment of a network as a competitive advantage that prevents competition from entering a market. Peter Thiel of PayPal fame recommends that startups go after small markets where dense networks can be created. (Giulio Tononi’s Integrated Information Theory uses “dense network” as a measure of how much more a system is than the union of its parts.) Thiel sees networks as a mechanism to achieve monopoly, his preferred position in any market. Facebook’s eclipse of MySpace shows, however, that networks are not a panacea or invincible business model, An even better example of the network model is Google. Google’s search algorithm targeted nodes with a large number of connecting links, just what Barab´asi explained about networks when he said, “new vertices attach preferentially to sites that are already well connected”. The insight here is that the Google algorithm followed the pure theory of power laws and networks and the opportunity proved to be quite large. Google’s approach also used autocatalysis, a characteristic of some complex systems, where the product of the search reinforced the importance of the information in future searches
Academic research has shown that companies using the network business model create more shareholder value. In an HBR article, “What Airbnb, Uber and Alibaba have in Common” [Footnote: https://hbr.org/2014/11/what-airbnb-uber-and-alibaba-have-in-common], the authors analyzed companies in the S&P 500 over a forty-year period starting in 1972. Companies were categorized as one of four types:
Asset Builders
Service Providers
Technology Creators
Network Orchestrators
Companies that were network orchestrators showed “higher valuations relative to their revenue, faster growth, and larger profit margins”. The researchers also discovered that only five percent of S&P companies are network orchestrators. The authors explain the value creation, “We believe this occurs because the value creation performed by the network on behalf of the organization reduces the company’s marginal cost, as described in Jeremy Rifkin’s The Zero Marginal Cost Society.” Looking for a more network-oriented explanation, I would think that the scarcity of network operators perhaps shows the challenge of successfully building and sustaining a network model. The efficiency of network value creation perhaps demonstrates Michael Porter’s findings that the competitive advantage [in successfully building and sustaining a network] is a key requirement for extraordinary value creation.
As we look to the future and the market opportunity offered from our understanding of networks, “The Second Machine Age” perhaps provides some guidance:
“The winners are no longer those able to compete solely based on cheap labor or ordinary capital, both of which are being squeezed by automation. … Fortune will instead favor a third group: those who can innovate and create new products, services, and business models. … So in the future, ideas will be the real scarce inputs in the world - scarcer than both labor and capital - and the few who provide good ideas will reap huge rewards.”
The Manifesto 15 Handbook discusses a new pedagogy, but I believe it can be generalized to show a type of market opportunity:
“Our traversals across networks are our pathways to learning, and as the network expands, so does our learning. In connectivist approaches to learning, we connect our individual knowledges together to create new understandings. We share our experiences, and create new (social) knowledge as a result. We must center on the ability of individuals to navigate this space and make connections on their own, discovering how their unique knowledge and talents can be contextualized to solve new problems.”
Scientists have long believed in the power of networks to foster research and learning. The Royal Society in England was founded in 1660 to support understanding in science. My point here is not to foster the further development of learned societies but rather to show that scientists have viewed the world in a similar way to The Second Machine Age since 1660. The opportunities suggested to me by this expanded networking include increased outsourcing, more hands-on learning between masters and apprentices and more tools for curating information.
One of the most interesting and difficult to understand parts of complex systems is that all complex systems are emergent. Before proceeding further, we should heed Melanie Mitchell’s warning that what do not understand about a complex system is not necessarily an emergent characteristic. Emergent properties are characteristics or behaviors that cannot be explained by the leaderless system of independent variables. Some scholars explain consciousness as an emergent property. Others explain sexual desire as an emergent property. Facebook perhaps demonstrates an interesting emergent property of some networks. A report by the international audit and consulting firm Deloitteestimates that the economic impact of Facebook on a global basis in 2014 was [Footnote:http://www2.deloitte.com/content/dam/Deloitte/uk/Documents/technology-media-telecommunications/deloitte-uk-global-economic-impact-of-facebook.pdf] $227 billion, of which $29 billion was attributable to “platform effect”—third party apps and services that attached to the Facebook infrastructure. I believe that “platform effect” is an emergent quality that enriches both the original network and the third party extension. Another example of an emergent characteristic might be many authors joining a network of book readers where they can interact directly with the readers. Readmill, acquired by Dropbox in 2014, offered this feature. Perhaps the advertising revenue model of Google search is another example of a successful network with an identifiable emergent characteristic. Perhaps a greater focus on the emergent characteristic would have enabled Readmill to survive as a standalone company. Building networks to foster symbiotic emergent characteristics such as platform effect may be a large market opportunity. The platform effect at both Google and Facebook was an after thought, as would be expected based on complexity theory, but in fact a key to success in both cases. At Google it provided the means to monetize search and at Facebook it accelerated the network effect for Facebook (and probably drew the world’s attention to social media). A business based on a network without an emergent characteristic is by definition a failure as a network. Fostering emergent qualities in networks should be a big opportunity given that the number of potential networks will only increase with the proliferation of digital technology. Such opportunities could involve network design or perhaps services to encourage the emergent characteristic.
Another interesting opportunity related to the network effect is Bitcoin and the underlying Blockchain infrastructure. Originally I was totally enamored of the idea that Bitcoin would replace government as the monetary authority by eliminating the need for government–issued currency. (The notion of eliminating government control of monetary affairs is almost irresistible.) With more thought on the subject I think Blockchain is a potentially bigger opportunity. Blockchain allows the members of a network to collectively authenticate data, replacing the role of a central authority. The MIT Media Lab Enigma project, according to Fast Company, uses the Blockchain technology to “enable a marketplace where users can sell the rights to use encrypted data in bulk computations and statistics without giving raw access to the underlying data itself”. For example, personal health record data could be shared without revealing individual identities. Effectively the Blockchain technology creates trust, verifies the data and reduces the cost to a network of processing information. With the increased size, versatility and resources of current networks with support from Blockchain, perhaps the biggest opportunity should be to use the newfound power of networks to replace government.
Note: The Edward Snowden affair may demonstrate that we have more confidence in Google than the U.S. government, these two being the largest collectors in the world of personal information. Now if we could only convince the Communist party in China and the Republicans and Democrats in the U.S. to go along, we could let individuals combined with network and AI technology manage global affairs. Ever the idealist!
The last opportunity that may emerge is in services to networks. For example, a university wants to start offering educational tours in Africa to alumni as a means to add value to the alumni network (and hopefully increase donations). The university will need a wide range of services to execute a strategy outside classroom education. Another example comes from Blackrock, the asset management behemoth. Any company that Blackrock invests in can purchase travel through Blackrock’s travel supplier[s] and take advantage of the volume discounts. An interesting example comes from my hometown Miami Marlins. They have created a network to share business between their corporate ticket holders. Both Blackrock and the Marlins need services for the network to exploit this additional opportunity to create value. As network becomes a better understood method to add value to an existing business model, the need for network services should increase."
Many people believe that we are at or approaching another technology revolution or paradigm shift similar to the steam engine or the transistor. Candidates for the technology to mark the next paradigm shift are artificial intelligence (AI), Internet-of-Things (IOT), nanotechnology or perhaps a less publicized technology.
The concept of a paradigm shift was first introduced by Immanuel Kant, further developed by Thomas Kuhn and recently explored in detail by Carlota Perez. Perez has done much analysis of the cycle of a paradigm shift, where the last stage is the widespread introduction of the technology in many applications. At this stage the technology risk is lower and the greatest amounts of capital are attracted and invested.
Yesterday Lyft, the car sharing service, announced a $500 million investment from General Motors. The blog AVC, where the principals are investors in Lyft, announced that the money is to "develop a network of self-driving cars". I think this Lyft investment will be looked back on as the first big investment in Perez's last stage of a paradigm shift to AI everywhere.
Part of the benefit of teaching is what you learn from the students. Yesterday in class one of my students made what I thought was an interesting observation. More and more companies are disrupting themselves. He said that the ability to disrupt your own company was a competitive advantage. In other words, consistently disrupting your own company is a unique input or expertise that satisfies the conditions for a competitive advantage.
For those who forget how to define a competitive advantage, the definition is below.
Valuable--has significant value to the customer
Rare--not common
Inimitable--not copiable
Not Substitutable--there is no substitute
The expertise of disrupting oneself is similar to the expertise of designing airplanes for quick rebuilding. This airplane manufacturer can crash, rebuild and test again faster than their competitors. This expertise enables them to get to market faster. The self-disruptor is constantly identifying a smaller feature set that satisfies an unserved portion of the market. The ability to see the unserved need and match it with a feature set repeatedly becomes a competitive advantage.
The more I think about this idea the more I like it. Imagine that you are running a food company. It might be easier to identify new products looking for ways to disrupt existing products rather than the more traditional ways used in the food industry.
I will be in Boston this week, a city I have grown to like very much. Usually I am at one university campus or another and rarely get to center city. This week is no exception:
Lecturing with a team from Demeter at the Fletcher School at Tufts University. (Demeter is a group that started at MIT and offers advisors and a network of experts for entrepreneurs in developing countries. My entrepreneur is working in the medical device space in Nigeria and currently raising a seed round (which is still open).)
Visiting friends at MIT
Happy to meet up with other people in the area. My contact info is on the "Profile" tab.
