SOPHISTICATED FINANCE

The Overlooked Intangible in Healthcare—What Abstract Thought Teaches us about Entrepreneurship

 

Photo credit: Nelson Designs https://www.youtube.com/watch?v=jOrwlhBNu3Y

 

Takeaways:

1. Technology attempts to solve problems of matter, energy, space, or time,
2. To apply technology to mental health and emotional problems, look to make the abstract tangible
3. 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.

 

 

 

Fall 2018 Courses

 

This Fall I am teaching two courses at FIU in the Honors College:

1. The Fourth Industrial Revolution    This course is for two semesters. The course starts with an introduction to industrial revolutions and the writings of Carlota Perez. I used to start with Thomas Kuhn, but that was heavy going for undergraduates. Then we read Complexity: A Guided Tour by Melanie Mitchell, a researcher at Santa Fe Institute. Stephen Hawking said that complexity will be the science of the 21st century. We finish the semester reading The Nature of Technology by W. Brian Arthur. One of my students, an engineering major, said that every engineer should read this book the first week of engineering school. The book reading is supplemented by several current articles, which are included in this first-semester reading list,  Download 4IR Reading List F2018.  After setting the stage with Perez' writings, the course moves into an exploration of the technologies of the 4IR--artificial intelligence (AI), Blockchain, gaming,  bio-sensors--to name a few. Much to my surprise, last year the students admitted that they did not know much about the technologies. This year we go deeper into the technologies. 2nd semester we explore the social, economic, political and environmental issues of the 4IR, which the students need to understand to fully function as citizens. Income inequality and the environment are two recurring themes, as I see these topics as the two critical issues of the 21st century. Course project will be to propose what the government will be in 2050. Students work in teams to perfect their collaboration skills.
2. Thinking, Design and Impossible Problems   This course is for two semesters. For several years I have been teaching a course on thinking disguised as an entrepreneurship course. What I realized is that better thinkers produce better entrepreneurs. This year I am just unabashedly teaching a course on thinking and the real objective is to help the students think like a genius. The readings, the authors, everything except the professor, is about the mental frameworks of genius level people. In part, the course was inspired by the first reading in the course, The Evangelist of Molecular Biology. This article is about James Watson, who won a Noble Prize for his work on DNA, and how he almost became an ornithologist. One day he realized that he would make no real contribution to humanity in ornithology, looked for a new field of study, and found molecular biology and genetics. From this article, I realized that high potential students need to be immersed in the thinking and writings of geniuses in order to better understand their alternatives. First book in the class is Melanie Mitchell's book on complexity (described above). One of the best frameworks for thinking about problems is to model them as a complex system. The second book is Ray Dalio's Principles: Life and Work. Dalio is a legendary hedge fund manager and a well-known advocate for the use of mental frameworks to address problems. Similar thinking and approach to another legend--Charlie Munger. The first-semester reading list  Download TDIP READING LIST F2018 also includes several articles. Many of the articles focus on inter-disciplinary approaches to problems and new fields where modeling is being used for the first time, such as mathematics, computer science and neuroscience. Each weekly class the students present their analysis of a different impossible problem and the course project will probably be to explain why art and science will converge in the 21st century. Students can work on all the problems in teams or individually. 

 

Image credit: Tomorrow Today Global

The Trilogy of the Fourth Industrial Revolution--Nature-Design-Technology

My professional life revolves around entrepreneurship in its many forms, the Fourth Industrial Revolution--4IR (that the World Economic Forum correctly started heralding a few years ago) and how these two themes intersect around opportunity, wealth creation and social innovation. One of the devices to understand the 4IR is what I call the Trilogy, which was written about by Daniel C. Wahl in the very good article, "Facing Complexity: Wicked Design Problems". The Trilogy, which is a device to simplify the 4IR, is that this revolution can be understood as the convergence of nature-design-technology. Until today I would have said go away and study complexity science, artificial intelligence, bio-mimicry, slime mold, design thinking and 10-20 other concepts and then the Trilogy is obvious. Today I had a realization. 

Fashion represents the Trilogy. Please remember my twenty years in retail and retail consulting. Now one might argue that fashion has existed from before we left the caves (all of intellectual history beginning from the first drawing on a cave wall) and you would be correct. Remember, it could be that all of human history can be understood through the lens of the Trilogy-nature-design-technology (see this article on the Krebs Cycle of Creativity). Now back to explaining the Trilogy in terms of fashion.

 

Now almost everyone can understand fashion in terms of design, at least it is superficially obvious. Technology is much the same, with different fabrics and colors being the result of technology. Where it becomes interesting is when we consider the role of nature in fashion. Of course, nature is where we introduce the human-centric focus and that leads us to the drape of the clothing on the body, the equally important emotional engagement of the wearer and most importantly to the question of customer self-esteem. What the fashion example makes clear is that every consumer opportunity, product or solution should be considered in the terms of the trilogy, whether you were sitting outside a cave or a modern design studio. As you venture forth in the 4IR remember one does not understand fully until one can explain the issue or opportunity in terms of nature-design and technology.

 

Note: The Krebs Creativity Cycle is not obvious and takes awhile for people to appreciate its utility. I will do a followup post to explain its utility in more detail.

 

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SOPHISTICATED FINANCE - Why I use Medium Now

My Latest Writing on Entrepreneurship and Complexity

For the last five years most of my thinking and teaching has revolved around three major areas:

1. Entrepreneurship
2. Creativity and learning
3. 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:

The Foundation of Entrepreneurship: Large Market Opportunities that have Repeated for 40,000 Years

If anyone thinks the essay is suitable to develop as a book, let me know by email.

Information, Capital and Blockchain

If you study complexity science you soon realize that reality is energy and information. If you study physics, one school of thinkers believes reality is binary [0,1] otherwise known as bits of information. This may not come as a surprise if we study Claude Shannon’s seminal work in information theory, which sparked the Third Industrial Revolution and the digital era. As we look at the Forth Industrial Revolution we see that information continues to be important in areas such as AI, IOT and robotics. So maybe we can conclude this information concept is important, even if we cannot tell what happened to Schrodinger’s cat or that tree in the forest.

Last week a friend was talking about healthcare and he asked me who had the most money in the healthcare system? The answer,  the insurers. Who has the most information in healthcare? The answer, the insurers. Historically, those who controlled the greatest amount of information were able to amass the greatest amount of capital. If you think about the enormous valuations of Google, FB and Baidu, one realizes that their platforms have chokehold on information from which they extract enormous value.

If you study the Blockchain and its distributed network of highly secure information, one realizes that this infrastructure eliminates the opportunity for information choke points and the related value capture. Now you know why the non-speculators are excited about Blockchain. The economics of value creation through information will remain intact but the value will be shared widely and not concentrated the way it is today.

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The New Role of Social Sciences in Technology

"The internet is entering a second era that’s based on Blockchain. The last few decades brought us the internet of information. We are now witnessing the rise of the internet of value. Where the first era was sparked by a convergence of computing and communications technologies, this second era will be powered by a clever combination of cryptography, mathematics, software engineering and behavioral economics."World Economic Fourum (WEF) Realizing the Potential of Blockchain

The Third Industrial Revolution (3IR) was marked by the emergence of computing and the conversion of information to digital formats. Starting in the early 1960s, and for the next forty years, the role of computing expanded largely in commerce and industry. With the advent of the personal computer and its increasing processing power, the widespread availability of the Internet and the emergence of cellular telephones as handheld computers, computing transitioned from a technology to a mainstay of business and personal life. Effectively, computing became like electricity--ubiquitous, cheap and easy to use in new applications.

While code and computing power were the original limiting factors, what now limits computing is the ability to correctly understand the social environment. Of course, this social environment is complex and therein lies the challenge for computing. Complex systems such as social systems are not deterministic but rather stochastic. Instead of using calculations we use computation, simulation and rules-based modeling. However, to properly develop these approaches we need disciplines such as game theory, behavioral economics and the social sciences such as psychology. This is the trend which the World Economic Fourum (WEF) highlighted above.

In simple terms it looks like computing has matured to the point where it needs to be multi-disciplinary in order to add further to its functionality...and in this case that means involving the social sciences to give insight into those pesky, complex humans.

Some articles on this theme:

The Threat | Edge.org

The Evolution of Trust  

If you want to understand the Blockchain philosophically and technically, the WEF paper referenced above is very good. 

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Why the 4th Industrial Revolution may not surpass the 3rd

I was talking to someone recently that argued that government grants to private companies were the most effective grants because the companies had proven methods to commercialize innovation. The person cited government funding for Tesla, but I can find little evidence of government cash as opposed to incentives going to Tesla.

This Tesla example reminds me of a big difference now at the beginning of the Fourth Industrial Revolution compared to the Third Industrial Revolution that began in the 1960s with the advent of computing and digital information. In the 1960s government funding was plentiful at top universities like MIT and for government agencies like NASA. This investment lead to new technologies such as computer networks, microwave and advanced materials which were widely adopted. Eventually the resultant creation of economic and social benefit reached unheard of levels of prosperity. 

The situation today is one where government funding, in limited amounts, is made available for basic research at universities. Little money is available for applied research and agencies like NASA have been greatly reduced for many years. If we think about when a startup needs money, the answer is in the early stage when it cannot easily access capital markets. If we look at an Industrial Revolution, again the capital is needed in the earliest stages to fund the primary innovations.

What might save the Fourth Industrial Revolution from a lack of government funding is that so much innovation surrounds data, information and technology (like the Blockchain) that does not require huge amounts of funding. Now generally I favor limited government and a commercial playing field not disrupted by government. However, government funding for significant basic and applied research makes sense to me, particularly given the declining spending on research by corporates. The corporates with the best ROI still invest in research according to HBR. Almost all the other corporates choose to enrich management or shareholders rather than invest in research.

The views expressed herein are my personal views and do not reflect the views of any organization that I might represent.

For expert advice on real estate in Queens, NY, please contact my daughter Christina at 347-768-0427 or email [email protected]

My Concern about How AI will Change Research and Thinking

Recently there have been some excellent articles and talks on AI, including:

1. The Physicist Who Sees Crime Networks 
2. Science has outgrown the human mind and its limited capacities
3. Mobile Is Eating the World, 2016 (recommended video)

Each of these articles deals with the advances in AI with respect to data analysis. The articles herald the amazing conclusions we have only recently been able to draw from the data. The second article goes on to talk about how the way humans think is changing to better use the new AI tools. The third article talks about how AI tools have totally changed in the last ten years, moving away from rules toward something that approximates human "learning". I could have picked 10-20 other articles in the last month that herald the same trends as these three articles. 

The depressing conclusion I draw is that science and social science is now going to be almost entirely shaped by the available data sets and the AI tools available to researchers. Also, probably for the first time in history private companies now have greater resources to do AI research than universities and more importantly are using the resources for this research. However, this corporate research is more likely to find the next behavioral insight than a breakthrough such as chaos theory or quantum mechanics. Furthermore, the best academics in Physics, math and computer science are being lured away by the corporates to do AI research. The outlook for breakthrough research that changes the future of mankind looks much less likely.

All of this would be distressing if not for a bigger concern. As we continue to advance science we are coming to realize that almost all human behavior can be explained by biology and physics. A representative article showing this trend is Swirling Bacteria Linked to the Physics of Phase Transitions. (For some unknown reason I love these articles where the apparently chaotic is explained.) I call this the "think like an ant theory". To understand a problem, think like an ant.

A popular emerging field is the combination of biology and business, where complexity science brings a cohesiveness to two such disparate fields. From this increasing understanding and reliance on biology and complexity science, one comes to realize that these simple models and methods can probably explain nearly everything. For example, to understand cities, first understand hunter-gatherer tribes. To understand entrepreneurship, first understand exploration and exploitation (what we now call Lean Startup), the fundamental behaviors of every living thing. This trend toward simplicity, however, is not supported by the popularity of AI and data sets.

If we look back in human history, until the twentieth century research was not heavily reliant on data collection and data sets. Therefore, most of the great thinking in human history was done by methods that were far simpler than AI. I do not think we need to return to the 16th or 17th century methods at the expense of AI, but I do think we need to realize that AI is not a panacea and traditional thinking still has much to contribute.

One could probably argue that the problem with research since the last century has been an increasing effort for it to look data-based and scientific. AI will only make such approaches easier and wider ranging. The original style of thinking of Aristotle, Descartes and Hayek should not be forgotten or held in disdain. 

Brain Pickings today writing about Bertrand Russell:

"But beneath such a surface impression is enormous depth of insight and a timeless, increasingly timely clarion call for nuance in distinguishing between the sort of knowledge driven by a greed for power and the higher-order wisdom that makes and keeps us human."

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Insights on the economics of technology

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:

1. "...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)."
2. "...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:

1. 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. 
2. The low revenue/IT cost in software and Internet publishing is consistent with the relatively low value-add in those services
3. 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.

 

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My Summer Reading List

This year's reading list is shaped in part by a new course I want to teach, "Cognition, Neuroscience and Artificial Intelligence". Also, I am still trying to answer some questions for a new book on market opportunities. All of this is increasingly tied together by my growing interest in evolution and biology. For several years I have told my students to think like ants. Now I have enough background to defend the position.

The recommended readings are:

1. "The Master Algorithm" by Pedro Domingos  The book is a history of artificial intelligence with a focus on machine learning (no math). The notion of a master algorithm that can create all knowledge is a very interesting idea.
2. "Money Changes Everything" by William Goetzmann  A history of money. Should be the first reading in every introductory finance class.
3. "Our Mathematical Universe" by Max Tegmark  Reconsiders the age old question of what is reality. 
4. "The Invention of Nature" by Andrea Wulf  A biography of the first naturalist scientist--Alexander von Humboldt
5. "The Evolution of Everything" by Matt Ridley  Questions many traditional explanations of issues and shows that evolution is a better explanation
6. "The Pre-history of the Mind" by Steven Mithen  Scholarly work on the cognitive origins of art, religion and science.

 

 

Innovation--Frequently discussed, Rarely Understood

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.

The future of VR

This article on cooperation in VR (virtual reality) between Samsung and Six Flags, the amusement park operators, prompted today's post.

Technically I think the cooperation is in augmented reality because the technology supplements the actual ride experience. The user wears a VR headset during the ride so it is more than traditional VR. I digress.

The point I took away from the article is why do I need to go to a theme park. I can duplicate the experience of the park rides with just a headset. Maybe I would need a chair hooked up to the VR to duplicate all the physical sensations, but I think the combination of headset and chair would be compelling.

VR today suffers from the same problem personal computers had in the early days--no use case. It was not until spreadsheets came along that personal computers took off. We need to find Excel for VR or else it will stay a niche technology. Spreadsheets worked because they served a very basic need-mathematical computation. What very basic need can VR serve (after which it can proliferate into hundreds of other use cases)? My guess would be something related to music. (Almost every Apple product launched on the back of an innovation related to music.) Perhaps allowing the users to share the perspective from the band's point of view during a concert would be compelling. Maybe sell that experience on a subscription basis for a well known band's world tour.

Self-organizing Systems

For some time I have been looking for a phrase that describes what I think is the future direction of software. Frog Design provided the phrase in this story, "We Are the Builders of Tech Revolutions. Why Are They Still a Surprise?" Frog predicts that software will be "self-organizing" by ~2030. Whether Frog and I agree on the meaning of self-organizing is not important.

I define self-organizing to mean that the software has sufficient data about the user combined with well developed artificial intelligence sufficient to predict an experience equal or better than the user could do. The experience might be a purchase such as a vacation trip or a list of recommended books to read or know who of your friends to send an article to. In the work environment your archive of information would dynamically connect with co-workers around the world who show the same degree of seriousness about a subject and create meta tags (or whatever is in use then) so that similar articles are more easily available to you regardless of how one person tagged them.

The information capture about you is already there. Note the Facebook ads you keep getting until well after you buy the new bag you researched at Michael Kors. The AI software probably needs a bit more time to reach the standard of designing a vacation as well as you would do it, but another ten years should be sufficient. A lot of data is being run through that AI software in ten years and the software keeps learning.

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WriteLab--Very Nice Editor App

A friend sent me a link to WriteLab, an AI-based prose editor. The company was founded in 2013 and an early investor was Mitch Kapor's Kapor Capital. (Kapor founded Lotus, a predecessor to Excel.)

Given the amount of writing I do, I had to sign up for a free trial. I took it for a test drive using a chapter from my next book. The chapter deals with how complexity theory applies to opportunity identification in entrepreneurship. Not a simple subject so I thought it would be a real test for the AI. A sample screen of the app, my prose and the comments is below.

 

I think the comments are generally excellent with very few computer style mistakes. The software is targeting a very high standard of writing, which I [modestly] define as better editing than I could do myself. I cannot figure out why editing comments  are classified into seven categories, but I would guess it has something to do with how the software learns. 

The setup is clunky. Just signup, ignore all the tutorials and just upload a document. It has MS Word type logic that we all understand. It will take a few minutes to get comfortable but when you realize that clicking on a comment takes you to that section of the prose, you have basically mastered the software. I am not yet confident that format is maintained.

One funny note--a computer style mistake. The computer commented on a Howard Gardner quote in my prose. Howard Gardner is a very famous education professor at Harvard. The computer did not know not to edit a quote (the edits would have improved Gardner's writing).

If you do serious writing and do not pay for editing, WriteLab is definitely helpful. Recommended for any considerate students :-)

WriteLab is further evidence that last week's story, "AI is the Paradigm Shift", is going to turn out to be correct.

Note: I rejected two changes proposed by WriteLab for this post but accepted 8 other comments.

 

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Facebook at Work

Business Insider reports that Royal Bank of Scotland is testing Facebook at Work as an email alternative. RBS cites the better functionality of the experimental Facebook at Work as the reason for the choice. What the Bank really mean is that we have learned to communicate in a new way, Facebook, and we now prefer that way. Interesting that consumer-focused Facebook realized their attractiveness as a business product....or maybe they wanted to get ahead of the other messaging powerhouses.

This quote from Inside Intercom may explain it.

"Given so much of our work is based on the back and forth exchange of ideas, it’s not surprising designers are imagining a new generation of messaging products, with dialogue at their center. Conversational UIs are breaking out of messaging apps and into products we use every day.

The cause of this shift is simple: human nature.

We’re innately tuned to converse with others. It’s how we share knowledge, how we organise ourselves, and how we share emotions. Language has been part of our makeup for hundreds of thousands of years. So of course we message all day long in bursts and binges, with family, friends, and colleagues. Messaging has become a layer through which daily lives are conducted."

I have been using Slack for about a month. I am not impressed. WhatsApp did not impress me either. I look forward to seeing FB at Work.

 

The Future of the Corporation--How They Will Process Information

This post reflects some of my thinking for a new book on a framework to identify the large market opportunities that have consistently repeated themselves over the last 4000 years.

 

 

Image credit: en.wikipedia.org

 

Evangelos Simoudis guest posted in Steve Blank's blog: 

 

"The last 40 years have seen an explosive adoption of new technologies (social media, telecom, life sciences, etc.) and the emergence of new industries, markets and customers. Not only are the number of new technologies and entrants growing, but also increasing is the rate at which technology is disrupting existing companies. As a result, while companies are facing continuous disruption, current corporate organizational strategies and structures have failed to keep pace with the rapid pace of innovation." 

 

Much of the article is devoted to the evolution of organization structure as technology fostered changes in society. Small family firms evolved into specialized corporations that then became geographically disbursed to serve multiple markets. This very interesting history supports Simoudis' point that corporate organizations change in both strategy and structure. What Simoudis does not explain is why these organizational changes take place. The answer lies in the amount of information that an organization needs to process.

 

Has information increased or decreased since the Industrial Revolution began around 1770? Of course, the answer is that information has increased dramatically and since the 1960s the rate of increase has accelerated. Ronald Coase the Nobel Laureate helps us to understand why increased information causes organizational change. Coase showed that firms were organized to reduce transaction costs. Firms internalized functions when it was economically beneficial compared with buying the service. This insight defined the line between the firm and the market. Now if firms are organized to efficiently use external resources, one might logically expect that firms also organize to use their internal resources in the most efficient way. What are the internal resources? Coase described these resources as legal rights.Effectively, what Coase meant by rights is information--knowledge in workers, contracts, intellectual property, business processes, business models, etc. As JR Galbraith makes clear in "Organizational Design Information Processing”, organization form and structure is updated to process information more efficiently. This, of course, is the same behavior that complexity theory would predict. Organisms are constantly trying to organize information in order to reduce the amount of energy required for search and organizing. 

 

Now what does all this discussion of information mean for how corporations should be organized. Brainspace has a good article, "5 Impacts of Sharing Knowledge Within an Organization,

proposing one way to look at the problem. The five key takeaways from Brainspace about how corporations should deal with information (in the future) are:

 

1. Identify subject matter experts 
2. Information will be captured for reuse
3. Access to information in context creates value
4. Open, collaborative workflows and processes will be required
5. Leaders need to gain a real-time view into the knowledge network

 

Brainspace identifies correctly the need for a corporation to totally redefine how they think about information and how they create it and manage it to achieve knowledge (meaning derived from information). The most important point is No. 4, where Brainspace tries to articulate the new role of the individual employee. However I think that words like collaboration, workflow and processes, Twentieth Century words, do not accurately capture the new environment. I think ants, as famous in complexity theory as ducks, may be a better way to describe this new organization. Individual ants, with no directions or orders seek out food sources, independently capture information about food and report back (through pheromone trails), which may trigger exploration by additional ants who also report back until sufficient information through pheromone confirms a good food source. Workers in the future will capture information that will be available to everyone in an organization, which will prompt various other employees to investigate.. some in more detail. A significant portion of the information will be in real time, captured by IOT sensors.

 

I expect that corporations in the future will:

1. Assign a portion of each employee day to information management--search, analysis and curation--in order to keep up the larger volumes of constantly changing information
2. Use some form of Evernote designed as an enterprise-wide app, with equal attention to the future and current environment
3. Use AI to organize and re-organize information in enterprise systems, based in part on the results  from individual employees doing information management
4. Adopt more analytics for decision making, but realize that information capture to feed the analytics is the priority

 I think that when artificial intelligence can re-organizes the information for a company’s employees to better reflect their evolving understanding of a subject, then organizations will look like ant colonies with a large number of integrated but autonomous information gathers. Some might call this holacracy, but I think "ant colonies" better captures the idea.

Corporate Staff Development Challenges

One of the most challenging issues in corporate management is the training, development and support of employees. The current environment increases the challenges for the reasons listed below.

1. The change from hierarchical to flatter organizations places more responsibility on lower level employees to take decisions and act
2. Flatter organizations tend to self-organize, making it less clear who is responsible for staff development
3. Outsourced employees, project staff and contractors may require development to remain a viable alternative to employees
4. The accelerating growth in relevant information and data finds employees needing a whole new tool set to stay current and informed

In considering the development of a new approach to corporate staff development and support, four factors need to be considered.

1. Corporate strategic goals and objectives
2. Regulatory requirements (SEC, HIPPA, etc.)
3. Environment (competition, technology, economy, globalization, ecosystem, etc.)
4. Standards for software, apps, dashboards and data are not set by corporate IT but rather by Uber, Dropbox, Medium and Apple

Corporate Strategic Goals and Objectives

I am sure most F500 corporate CEOs are confident that the company strategy is well articulated. Now imagine that we are onboarding a graphic designer contractor to a project. Imagine the contractor is from Tajikistan, a Moslem woman and English is her fourth language. Now how confident are we about the clarity of the strategy given the social, cultural and language issues? How confident are we that our information and support systems have been designed to recognize the particular needs of this woman contractor?

Regulatory Requirements

Since the 2008 financial crisis, U.S. federal regulators have scrutinized large corporations. Scrutiny with respect to risk exposures increased after the Snowden affair of 2014. Such events of extreme consequence will probably increase. Therefore, it becomes incumbent upon corporations to keep their staff abreast of regulatory requirements but also the philosophy and concepts underlying the regulation. I hope the woman contractor from Tajikistan is familiar with, for example, FCPA regulations.

Environment

The pace and scope of change has increased as computing power has increased, whether we examine the actual change or the pace at which new information circulates in world markets through informal communication systems (such as Twitter or WhatsApp). This complexity strains employee’s ability to stay current and understand new issues sufficiently to develop proactive strategies.

Standards for Software, etc

Employees and third party workers all over the world have become accustomed to beautiful interfaces for a large feature set of necessary information all on their phone. Formats include You Tube videos, Slideshare presentations, e-books, PDFs, MOOCs and 100 other formats and delivery mechanisms. On any subject you can get information in the format you prefer. Few corporations have yet reached this level on proprietary applications let alone their information archives (if they even exist).

Next post I will talk about the solution.

 

 

 

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Learn from a Great Designer

A few years ago I had the pleasure to work with Yves Behar at fuseproject. He was the designer for the One Laptop per Child laptop and then the tablet (the project I lead). Yves has many talents, as would be expected from a world class designer, but what I always noticed was his unwavering focus on understanding the customer.

This story from the fuseproject blog, "On Crafting Wearability", makes the customer focus clear. I inserted the bold to show the insights about the customer in the reprint of the story below.

"Wearables represent an immensely excited and daunting design challenge. There are very few things, let alone electronic devices, that we wear on our bodies 24/7. In fact, we entered wearables because we felt that, in addition to our technological assets, the key to true success would be creating something inspired and unique -- something you would love to wear. Delivering on these principles is not easy. It takes time, commitment, invention; these combined with great engineering and never tried before manufacturing methods has led to a new collection of UP2 and UP3 offerings.

UP2, already the slimmest and lightest wearable on the market, has been reimagined with a new style strap, making it look even smaller on the wrist. The rope-like TPSIV rubber band with a polished metal hook is a new style that is extraordinarily comfortable and graceful. The open strap gives more breathability on the wrist, while looking complementary next to a watch or jewelry."

Would you have researched wearables well enough to draw the insights bolded above? I particularly like the insight about the wearable looking good with a watch or bracelet.

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Designs for better living

Miami's Best Medical Project Offers Fellowships and Startup Opportunities

What do you do when you have a breakthrough diagnostic medical technology that needs more partners to develop multiple use cases? How do you find the "best and the brightest" individuals to partner with? How do you find these people with no concern for their age, background, culture or any other discriminatory factor? 

Meet Protean Labs.

To become a Protean Fellow you simply need to submit the answer to one of five questions listed under the Apply Now tab on the website. If accepted:

"Join us for a one month Protean Fellowship. You may choose to work on a problem defined by you or alternatively, a problem assigned to you by Protean Labs. You will be given access to research lab space, equipment, reagents and access to our scientific network. You will be expected to demonstrate self-efficacy and resourcefulness. At the end of your fellowship, a stop-go decision point is reached. If you have sufficiently demonstrated the potential for your project to succeed as a startup proposition, you will progress to the next phase where you will become a Partner in Protean Labs working with us to spin-off your technology into an independent company. You will be given the option to lead this company."

Just to say it again, applicants of any age will be considered.

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Companies with No Humans

This quote in a story in Fast Company caught my attention:

"...a system in which a program can be written to find an answer—or to execute a smart contract that can buy something, sell something, or do something. In aggregate, a group of smart contracts could run what is known in Ethereum-speak as a "decentralized autonomous organization" (DAO) or a "distributed autonomous corporation" (DAC)—in other words, a corporation distilled to its most basic tasks, and operated by little more than code and the logic of if this, then that." (emphasis added) Companies will have a single asset, a code base using AI, that will enter into transactions with independent service provides to create, deliver and capture value.

Perhaps this novel idea caught my attention because I had spent the weekend reading about datafication, which is explained in a study by Ericsson "The Impact of Datafication on Strategic Landscapes". Digitalisation is the evolution of IT starting in 1950 which brought us apps, mobile devices and a focus on IT for productivity improvement. Datafication is the new approach to IT which recognizes the changes coming in IT from the large number of physical objects capturing or generating data. The differences in digitisation and datafication (from the Ericsson study) are summarized below.

 

Now, as every aspiring entrepreneur knows, one must understand the customer and their problem to successfully start a new business concept. The question one should be considering is whether datafication provides sufficient information for the code based AI company to successfully identify a large need and develop a solution. Ericsson believes the answer is yes and the data source will probably be your cell phone, which captures and generates data on your entire life. When a company with no humans is analyzing data about you, it brings privacy issues to a whole new level.

Maybe the solution to the problem of the morality of capitalism is to replace the human managed companies with "no humans" companies. Might be more socially aware :) 

Instead of robot challenges every weekend, maybe we should have challenges for best code to autonomously operate a company. 

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