Esko Kilpi on Interactive Value Creation

The art of interaction, the design of digital and the science of social complexity

Category: Digital work

The changing system of skills and responsibilities

We have so far followed a very crude pyramid-like classification in work: skilled work was what highly educated individuals would do. Semi-skilled work was possible for trained people. Unspecified labor was what almost everybody could do after onboarding. This classification of work led to the unintended consequence that the most economical design of mass-era organizations reduces the amount of skilled work and increases the amount of less-skilled work, thus reducing costs. A bigger problem than low-skilled people is the low-skilled occupations we have created.

Classification of work as different bundles of skills and responsibility has been very easy to grasp and easy to follow in compensation schemes. More skills and/or more responsibility — more pay. Managers, who are responsible people, are given responsibilities — and higher wages. Workers are given less demanding tasks, less responsibility — and lower wages. The argument behind is a circular, self-fulfilling prophecy. People who are not made responsible tend to avoid responsibilities and therefore never become responsible. Skilled people acquire more skills because of the higher cognitive demands of their work. Less-skilled work roles give less opportunities for learning, leading in fact to a slow but certain de-skilling. This is something we see in many industries today. The phenomena and the causes of the problem become the same.

The organizational system of skills and responsibilities has been made on the assumption that all that has to be done can be known and managed with efficiency and insight. In mass-production, work corresponds mainly with what has been planned and budgeted. But today, in more contextual problem solving, work corresponds mainly with complex engagements with the customers.

The focus changes from generic skills to contextual presence, empathy and interaction.

The most modern definition of work is “an exchange in which the participants benefit from the interaction”. Interestingly, cooperation is also described as “an exchange in which the participants benefit from the interaction”.

The technological environment of work has changed fundamentally, but we haven’t yet developed a new mode of economic space design, neither have we escaped the pull of the traditional industrial system. Our relations at work are still asymmetrical involving status differences based on systems of responsibility and systems of skills. This inbuilt systemic fault generates increasing social distance and inequality, as we have now seen.

Due to the variety of contexts people work in, work requires interpretation, exploration and negotiation. The interpreter with the best situational awareness is the worker, working together with the customer, not a manager. The relations are built on symmetry.

What defines most problems today is that they are not isolated and independent. To solve them, a person has to think not only about what he believes the right answer is, but also about what other people think the right answers might be. Work, then, is exploration both what comes to defining the problems and finding the solutions. Again, the relations need to be based on symmetry.

Most decision makers are still unaware of the implications of the complex, responsive properties of the world we live in. Enterprises are not organized to facilitate interactions, only the actions of parts taken separately. Even more, compensation structures normally reward improving the actions of parts, not their interactions. This is why conventional jobs are increasingly inhibiting flexibility and contextual responses to new problem definitions or new technological solutions to old problems.

To succeed in the new economic spaces we need symmetric relationships, open assets and very open organizations.

When customers are identified as individuals in different use contexts, also the sales process is in fact a joint process of solving problems. You and your customer necessarily then become cooperators. You are together trying to solve the customer’s problem in a way that both satisfies the customer and ensures a profit for you. The industrial make-and-sell model required (explicit) skills as we still know them. The decisive thing was your individual knowledge and individual education. Today, in new economic spaces you work more from your presence and network than your skills. Work is interaction.

The really big objective of digital transformation is to reconfigure agency in a way that brings these relationships into the center. Success today is increasingly a result of skillful presence: it is about empathy and interaction. Through new technologies and ubiquitous connectivity, we have totally new opportunities for participation and communication in the new economic spaces

These economic spaces are about interdependent individuals and groups defining and solving problems in shared contexts utilizing smart contracts.

Individuals competing on job markets may be one of the historic mistakes we have inherited from the early industrial era. It made sense a very long time ago but now we should think differently.

Interaction creates capability beyond individuals. Cooperative performance can be more than what could ever be predicted just by looking at the performance of the parties involved. It is not about individual skills any more. Skills, performance and resilience are emergent properties of cooperative interaction. They are not attributable to any individuals. Higher performance is more a result from the quality of interaction than the quantity of training and education.

Networks provide problem-solving capability that results directly from the richness of communication and the amount of connectivity. What happens in interaction between the parts creates a reality that cannot be seen in the parts or even seen in all of the parts.

This is why it does not make sense any more to talk about skill levels and just managers being responsible. Either you are present in a relevant way or not. Neither can responsibility be somewhere else. You can only be present and contribute if you are response able.

Credits Nick Hanauer and Katri Saarikivi

From transaction costs to network effects

Resonance occurs whenever two things vibrate in tune. If you strike a tuning fork, an identical fork on the same table will begin to vibrate. Energy is continuously exchanged between the forks, which are in resonance. Resonance is such a powerful phenomenon that soldiers marching across a suspension bridge break stride just in case their coordinated marching should resonate with the natural vibrations of the bridge. If this would occur, the bridge would absorb the energy of the marching soldiers and the structures could even oscillate out of control and break.

Quantum theory says that each (quantum) entity has both a wavelike and a particle like aspect. The particle like characteristic is fixed but the wavelike is a set of potentialities that cannot be reduced to the existing parts of the entity. If two or more of these entities are brought together, their potentialities are entangled. Their wave aspects are interwoven to the extent that a change in the potentiality in one brings about a corresponding change in the potentiality of the other. A new shared reality emerges that could not have been predicted by studying the properties or actions of the two entities. It is really about learning that scales.

The famous experiments with the fundamental entities of visible light have proven that we cannot claim that a photon is a wave or a particle until it is measured, and how we measure it determines what we see. “If you change the way you look at things, the things you look at change” as Max Planck put it.

The basic units of the industrial era were transacting entities enabled by market, price and coordination mechanisms. It was a world of particles separated from other particles.

As a social innovation the industrial era enterprise was born when the volume of economic activity reached a level that made administrative coordination more efficient and more lucrative than market coordination of these particles.

The important innovation of the modern firm was to internalize activities by bringing many discrete entities under one roof and under one system of coordination. The multi-unit business corporation replaced the small, single-unit enterprise because administrative coordination enabled greater productivity through lower (transaction) costs per task than was possible before.

Managers essentially carried out the functions formerly handled by price and market mechanisms.

The practices and procedures that were invented at the dawn of industrialism have become a standard operating system and are still taught in business schools. The existence of this managerial system is not questioned. It is the defining characteristic of the business enterprise.

But two aspects of work have changed dramatically.

The most successful firms are themselves multi-sided markets in interaction with entities “outside”, customers and network partners. These firms are the new platforms.

Secondly, the products/services the platform firm sells to its clients are not offerings of the firm per se, but offerings created by specific network players in specific situations of “local” network interaction.

Thus, aiming to become a platform requires a vision that extends beyond one’s firm and aims to build and sustain an ecosystem that benefits from more partners joining the network. During the industrial era, economists called this phenomenon network “externalities”. Now it is more properly called network effects.

This conceptual difference is hugely important because what assets were for the industrial firm, network effects are for the post-industrial firm.

We all have mindsets of the world that serve as maps that guide what we see and how we understand the world around us. The maps can be helpful but also outdated and incorrect. The approach that managers do the coordination is just too slow and too costly in the low transaction cost environments we live in. It is now more expensive to internalize than to link and network.

Traditional business economics focus on supply side economies of scale derived from the resource base of the company. It scales much more slowly than the demand side network effects the new firms are built on. Network effect based value can increase exponentially at the same time as costs grow linearly. If you follow the valuations of firms today there is an ever-widening gap between the network-economy platforms and incumbents driven by traditional asset leverage models. Investors and markets have voted.

People participate based on transparent information and high quality communication systems enabling “resonance”. The contributing individuals are not managers but customers and other network partners. The more of them there in active “resonance” the more assets there are.

The main mission of digital platforms is to make network effects possible. Platforms are (just) means to tackle network effects the same way the industrial corporations were (just) means to tackle transaction costs.

The big shift is from market transactions to network interactions. The world of business looks very different when we change the way we look at things from transaction cost economics to network effect economics.

The complex future of work

We live in an age of simplistic explanations. We build simple systemic models and crude abstractions. As a result, both our sense making and our decisions are built on an inadequate appreciation of the complex systems we are part of.

We have seen what it can lead to: industrial farming has caused a radical reduction of variety in nature in order to meet the goals of productivity. The simplification of crops was economically very efficient, allowing specialization in machinery and lowering the cost of learning, but it often damaged the local ecology in an irreversible way. The result was a fragile ecosystem, with a growing dependency on artificial fertilizers.

Every time we replace natural, complex systems with simplified mono-cultures we gain in short-term productivity, but at the cost of long-term resilience and viability. The less diverse a system is, the more vulnerable it is, and the more unsustainable it becomes.

Farming is now changing. New voices within agriculture say that “all farming takes place in a unique space and time”. These scholars claim that a mechanical application of generic rules and principles that ignore these contextual particularities is an invitation to catastrophic failure.

The principles of simplification still apply to the social systems of work: most of our firms can be described as mono-cultures. We also do our best to productize humans to fit the job markets. Many organizations are productive in the short term, but fragile in the long term. As long as the environment remains the same, simplified systems are very efficient, but they immediately become counterproductive when the environment changes even slightly. And it always will.

Our view of efficiency in firms still follows the line of thinking of efficiency on farms.

Job markets need standardized workers who are uniform in their skills and motivations. People are interchangeable labor. These people have no uniqueness. They have no original ideas to contribute to work. The focus is on the price of work; supply and demand.

In classical economic theory, markets are assumed to tend to a state of equilibrium. If there is an increase in demand, prices rise to encourage a reduction in demand and/or an increase in supply to match the demand. This is the principle behind Uber’s surge pricing. A market, then, is a simple cybernetic system: any significant change is self-regulating adaptation. There is no learning.

One-dimensional social designs have the same inbuilt risks as simplified natural designs. Simplified social systems can cause the same kind of damage to the human ecology as simplified farming systems have caused to the natural ecology. People become dependent on artificial motivation systems, the human equivalents of fertilizers. We call them incentives.

Just as all sustainable farming is now seen as taking place in a unique context, all human work takes place in a unique space and at a unique time. Human work is situated and context-dependent. It just hasn’t been understood that way. The digital architecture of this kind of work might resemble Amazon Dash buttons more than Uber.

Technological intelligence helps farmers to be more context-aware. Technological intelligence can do the same for human work. Mass systems were built on general knowledge and generic competences. Perhaps post-mass systems are going to be built more on situated knowledge and contextual competences.

An example of this might be the difference between the general knowledge of seamanship in open waters and the contextual knowledge of piloting. When a ship approaches land, the captain often hands over control to a local pilot, who then navigates the ship to the port. Pilots know well the dynamic peculiarities of the area, the winds and the currents. Much of this situated knowledge would be irrelevant somewhere else, at another harbor entrance.

A job market, as a concept, is a radical abstraction of human work. Every time we replace practical, local knowledge with general, standardized knowledge we gain in productivity, but at the cost of more environmental adaptation in the future. Learning debt is created and the whole system (of jobs) is less resilient and may even become dysfunctional. Short-term gains turn out to be extremely expensive in the long run!

The post-industrial era is too complicated to boil down into a single slogan describing work, but three scenarios seem to be emerging: (1) processes are automatized and robotized, leading to an algorithmic economy: (2) generic work is found through platforms, or turned into tasks circling the world, leading to a platform economy, and (3) context-specific value creation takes place in interaction between interdependent people, leading to an entrepreneurial economy.

I believe that the future of human work is contextual. Even after the captains are automated, the pilots may still be human beings. Even after the surgeons are robots, the nurses may still be human beings. Some people doubt this because there is some very advanced research going on that explores sensor technologies and responsive algorithms. The collaboration between sensors and actuators is getting better and better. Despite that, if you are a human being, it is better to be a tour guide than a travel agent.

It is a more profound change in work patterns than what the present platforms offer. It is not about employees becoming contractors. It is about generic, mass solutions becoming contextual and about interchangeable people who are now, perhaps for the first time, being seen as unique. The case for networked small units, such as human beings working together in responsive interaction, is stronger than ever. Local, contextual knowledge is needed not only for sustainability in farming but also at work.

What is most desperately needed is a deeper understanding of the complexity of life.

Farming is starting more and more with a true understanding of the particularities of the land. Work should also start with an understanding of the particularities of human beings.

Thank you Doug Griffin and James Scott

Digital Cultures

A friend who works with Artificial Intelligence told me: “It is possible that there are complex and conteaxtual things about humans, but in terms of intelligence it does not look that way. With the brain there is nothing that isn’t computable. The brain is a computer like any other.” I begged to differ and claimed, a bit flippantly, that our brains do much more than solve differential equations.

Our present digital culture is oriented towards the objective and the quantifiable more than the subjective and the qualitative. The software we work with reflects the analytical minds of the people who built it, such as my friend. The downside of all this is a possible failure to understand and capture the paradoxical elements of life.

Traditional science was a project that aimed to get closer and closer to certainty. The new sciences of complexity are making it clear that this is not possible. Complexity sciences present paradoxes as being normal in everyday life. The dominant scientific way of thinking tries to eliminate paradox. An encounter with paradox, such as seeing the same thing differently from different points of view, has been understood as a sign of not thinking properly and thus has led to attempts to resolve or eliminate the paradox. What the new sciences are suggesting is that the dynamic patterns of knowing are inherently paradoxical and context-dependent.

A new language is appearing as scientists attempt to describe the complex dynamics in which phenomena are no longer perceived as certain. Things are both predictable and unpredictable, knowable and unknowable at the same time. To force this complexity into a reduced number of cognitive patterns would be enormously repressive.

The question of what technology dealing with Artificial Intelligence is doing to our cognitive patterns has been the subject of strong opinions but few robust studies. Some scholars claim that the brain has always been adapting to new tools. New neural patterns emerged when people began speaking, reading or writing. Digital tools and software code are just the next step, they say. Man is seen as his or her own maker — a maker of life through new tools and new practices created by those tools.

The real question here is whether modern society is in effect de-skilling people in the conduct of the practices of everyday life because of our tools. We have more machines than our ancestors, but less idea of how to use them well. We have more connections with people, but less understanding of people who are not like us. Our social tools have in a way helped to re-create tribalism: solidarity with others like yourself (in your own echo chamber) and aggression against those who differ. Tribalism involves thinking you know what other people are like without really knowing them. Lacking direct, time consuming face-to-face experiences, it is easy to fall back on fantasies and stereotypes.

Digital tools have increasingly become our senses, our eyes and ears. Digitalization has given us amazing access to the world. But there are things it does not capture. The more people have superficial information about the world, the less they actually put themselves in the shoes of others. The psychological problem is that when we don’t know the history and the context behind something, we project those ourselves. When the context is stripped away, we add it back. We fill in the gaps in information when they are not there. It is so easy for us to comment very negatively on Twitter posts without any understanding of the context of the discussion. We don’t know much about the refugee crises, but we think we know, as we project our beliefs, fears and worries onto what is going on.

I am one of the people who claim that the new social technologies can also be used to solve these problems.

The concept of social skills often means that people are good at telling stories or accomplished at party talk, but there are social capabilities of a very serious sort. The social capacity of cooperation is more the foundation of human intelligence than differential equations are.

The next digital tools dealing with intelligence need to be more “dialogic”. The concept of dialogue has a very precise meaning. It is a discussion which does not resolve itself by finding common ground. Though no shared agreements are reached, people often become more aware of their own views and learn through expanding their understanding of one another and the different contexts of different people. We become more intelligent if the paradoxes are kept alive.

Cultural homogenization is a theme of our time. It is apparent in fashion, food, music, and many services with a unified user experience. Everything is made to be basically the same everywhere. According to some psychologists, the desire for this sameness arises from anxiety about differences. This is one of the reasons why Gregory Bateson argued that the history of our time can be perceived as the history of malfunctioning relationships. More homogenization leads to more anxiety (when experiencing differences) which leads to more homogenization and the “differences that make a difference”, as Bateson put it, are lost.

Unless you genuinely value the perspectives of others, and not just the ones that conform to your own, you are not going to understand them. Truly intelligent thinking is not just a means to an end: it has to be rooted in what we see as ends in themselves, the values by which we live.

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Work is solving problems and learning is answering questions

Studies predict that nearly half of all jobs and over 70% of low-skill jobs could be susceptible to computerization over the next two decades. Our chances of creating work for human beings in this new, demanding environment will be very limited if old and unjustified assumptions about what people can or can’t do are not examined. If we continue to assume that some people are born intelligent, while most are not, and continue to see intelligence as a fixed, personal possession, the options for large-scale systemic changes will be few.

If, on the other hand, we were to visit recent findings of neurosciences, relational psychology and computational social science, we would see intelligence as something more fluid. Then a whole different set of opportunities would become visible. Perhaps a bigger problem than low-skilled people would be the low-skilled occupations we have created.

There is a misunderstanding of the relationship between “nature” and “nurture” as causes of our intelligence. In most cases, genes do not establish limits that determine the space for personal growth. Recent scientific findings show that everyday life plays a role in defining how and when the genes themselves are expressed in us. Genes, the nature, take their cues from nurture. Environmental influences can be less reversible than genetic ones.

There is another argument than the science of genes about whether intelligence is fixed or can be expandable. Many people tend to think that they live their life with a fixed-capacity. Some people think differently. They have a growth mindset, as Stanford professor Carol Dweck calls it. They think that minds are like bodies: people come in different shapes and sizes, but everyone can benefit from exercise.

Individuals who believe that they can grow, tend to enjoy challenges. They like pushing themselves because they think that struggling leads to something good. People who think that their minds are fixed often see challenges as a threat to their imagined level of ability. They don’t like having to try new things, or making mistakes, because they interpret that as evidence of inadequacy.

These mindsets come from the way people around us respond to our successes and failures. Belief systems are contagious. If, over an extended period of time, people are treated as if they are intelligent, they actually become more so. The opposite can also be true.

Success in life has been seen governed by two concepts: skills and effort; how bright you are and how hard you work. Recently, researchers have claimed that there is a third and decisive concept. It is the practice of lifelong curiosity: “knowing what to do when you don’t know what to do” as Piaget put it.

The collective intelligence of our societies depends on the tools that augment human intelligence. We should welcome the fact that people today are smarter in large measure because they have invented and use smarter tools. Making tools is what human beings have always done. The interactions between tools and human minds are so complex that it is very hard to try to draw a line between humans and technology. Neither is it a zero-sum game where the human brain is losing to technological intelligence, but as technology changes, people and what people do, are necessarily changed.

To benefit from technology, we need resourcefulness. It means to be constantly looking for new tools with which to augment our intelligence. It also means new services: if you have a smartphone in your pocket, you should have an easy access to education in your pocket. Smarter and smarter tools surround us, but if we don’t want to learn the new practices and take up the new roles that the new technologies make possible, they might as well not be there. It is sometimes not easy, because the challenge with new technologies is, what is called “functional fixedness”, our inability to see more than the most obvious use cases.

There is more to being intelligent than using the latest technologies; how we interact with others is a crucial element of how smart we are in practice. Intelligence is social and arises in communities and communication. The world has never been a more networked place, and yet schools and workplaces still focus on individuals. That needs to change.

Human behavior is learned in relations. Our brains are wired to notice and imitate others. Computational social science has proved that behavior can be caught like a disease merely by being exposed to other people. Perhaps you can catch intelligence from others the same way? Learning and also non-learning can be found in communication. It is not that people are intelligent and then socially aware. Social intelligence is not a separate type of intelligence. All intelligence emerges from the efforts of the community.

Work starts from problems and learning starts from questions. Work is creating value and learning is creating knowledge. Both work and learning require the same things: interaction and engagement.

Scientists have discovered that learning is learnable. With the help of modern tools, we can create ways for very large numbers of people to become learners. But learning itself has changed, it is not first acquiring skills and then utilizing those skills at work. Post-industrial work is learning. It is figuring out how to solve a particular problem and then scaling up the solution in a reflective and iterative way — both with technology and with other people.

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Not firms but commons and market networks

Many people see peer-to-peer platforms as game changers in the world of work with the potential of reinventing the economy and giving individuals the power of the corporation. Others are sceptical and warn that the new architectures of participation and choice are in reality architectures of exploitation, giving rise to a new class of workers, “the precariat”, people who endure insecure conditions, very short-term work and low wages with no collective bargaining power, abandoned by the employee unions, rendering them atomized and powerless.

I have just finished reading “PEERS INC”, an excellent book by Robin Chase. It is both a practical guide and a textbook that explains what is happening today in the (almost) zero transaction cost economy, the digitally enabled new world that has given rise to peer-to-peer platforms as the most modern iteration of the firm.

Robin Chase explains well how the patterns of work and the roles of workers are becoming very different from what we are used to: the industrial production of physical goods was financial capital-intensive, leading to centralized management and manufacturing facilities where you needed to be during predetermined hours. The industrial era created the employers, the employees and the shareholder capitalism we now experience.

In the network economy, individuals, interacting voluntarily with each other by utilizing the new platforms/apps and relatively cheap mobile devices they own themselves, can create value, and, even more importantly, utilize resources and available “excess capacity” as Robin Chase calls it, in a much more sustainable way than was possible during the industrial era.

Work systems differ in the degree to which their components are loosely or tightly coupled. Coupling is a measure of the degree to which communication and power relation between the components are predetermined and fixed or not. Hierarchies and processes were based on tight couplings. The new post-industrial platforms are based on loose couplings following the logic of the Internet. Some people will work on one platform every now and then, while others will work simultaneously and continuously on many different platforms. The worker makes the decision about where, with whom and how much to work. The old dichotomy of employers and employees is a thing of the past.

In creative, knowledge-based work it is increasingly difficult to know the best mix of capabilities and tasks in advance. Recruiting is becoming a matter of expensive guesswork. Matching the patterns of work with the capabilities of individuals beforehand is getting close to impossible. What, then, is the use of the organizational theater when it is literally impossible to define the organization before we actually do something? What if the organization really should be a process of emergent self-organizing in the way the platforms make possible?

Instead of thinking about the organization let’s think about organizing as an ongoing thing. Then the managerial task is to make possible very easy and very fast emergent responsive interaction and group formation. It has to be as easy as possible for the best contributions from the whole network to find the applicable contextual needs and people.

Instead of the topology or organizational boxes that are often the visual representation of work, the picture of work is a live social graph. In markets the signalling may change; It is not just a system of prices that brings people together, but purposes, capabilities and reputation .

If you follow the valuations of firms today there is an ever-widening gap between the network-economy platforms and those companies driven by traditional asset leverage models. Investors and markets have voted very clearly. Traditional business economics focus on economies of scale derived from the resource base of the company, which scales much more slowly than the network effects the new firms are built on. The start-ups have a huge advantage over the incumbents.

In practice this means that the peer-to-peer platforms can attain the level of customer reach and network size required to capture almost any market, even as the size of the core (firm) stays relatively small.

The principles behind these trends are crucially important for the future of firms and society. It used to be argued that goods for which the marginal costs, the cost of producing one more unit of customer value, were close to zero were inherently public goods and should be made publicly available. Before the digital era, roads and bridges were commonly used as examples of these platforms. The maximum societal benefit from the initial investment is gained only if the use is as unrestricted as possible. People should have free, or almost free access to the – “platform”. Once the capital costs have been incurred, the more people there are sharing the benefits, the better it is for the whole value system.

This was the economic explanation for why roads were, and still are, under public ownership. The same logic applied to public libraries: a book can be read repeatedly at almost no extra cost.

A platform (company) should therefore be as open, as accessible and as supportive as possible to as many users as possible. This is unequivocally the route to optimum value creation. The scale of the Internet can create almost boundless returns without the core company growing at all. And against mainstream thinking, services do scale now as much as products did yesterday. One person can have a million customers and ten people can have a hundred million customers. The sheer size of an enterprise will tend to mean less in the digital network business than in the world of physical goods. The flip side is that companies don’t grow and create jobs in the way they used to. It is the networks that grow creating new earnings opportunities for people who are part of the network!

The central aggregator of enterprise value will no longer be a value chain, but a network space, where these new firms are fully market-facing and the customer experience is defined by apps. Our management thinking is slowly shifting towards understanding the new kernel of work: participative, self-organizing responsiveness.

Platforms are a valuable, shared resource making interactive value creation possible through organizing and simplifying participation. Sociologists have called such shared resources public goods. A private good is one that the owners can exclude others from using. Private was valuable and public without much value during the era of scarcity economics. This is now changing in a dramatic way, creating the intellectual confusion we are in the midst of today. The physical commons were, and still often are, over-exploited but the new commons follow a different logic. The more they are used, the more valuable they are for each participant.

The ongoing vogue of business design transforms asset-based firms to network-based platforms. Perhaps the next evolutionary step in the life of the firms is a transformation from platforms to open commons with shared protocols. Perhaps Bitcoin/Blockchain is going to be part of the new stack, the TCP/IP of business.

In the new commons and market networks, people with more potential ties become better informed and have more signalling power, while those outside and with fewer ties may be left behind. This is the new digital divide. Network inequality creates and reinforces inequality of opportunity.

In the age of abundance economics, public is much more valuable than private. Governments have always been platform creators. I sincerely hope they understand the tremendous opportunity we all face. The old demarcation line between public and private does not make any sense any more.

The principles of digital peer-to-peer commons can also enable the massive multi-stakeholder participation that is urgently needed to meet the challenge of climate change, as Robin Chase writes in her important book “PEERS INC”.

Are markets the future of firms?

Amazon has joined Uber, Lyft and many others in redrawing the lines between independent contractors and employees. On March 30th Amazon announced an expansion into the “on-demand” economy. Amazon Home Services is a service marketplace that connects customers with builders, plumbers, cleaners and even teachers. Amazon has successfully made it very easy to buy books and goods. It now plans to do the same for professional services. It does so through (1) standardizing offerings so that prices can be agreed in advance, through (2) promising that the workers are trustworthy. Amazon scrutinizes workers through searches, interviews and reference checks and (3) providing a great interface experience for employers to a world that is very cumbersome: one-click hiring of workers and easy payments through Amazon.

Businesses are concluding more and more often that there are no reasons why certain activities should be performed by employees rather than contractors. The skills of these workers are seen as generic, making it easy for non-permanent workers to fit in quickly. This has created the Internet-based service platforms, the new job markets and the huge trend of on-demand work.

But hold on. A firm is essentially about creating long-term contracts when short-term contracts are too costly, or don’t make sense for other reasons. So is there a place for long-term contracts in the world of the Internet and these new markets? Is there a role for the firm, as we have known it?

One way to understand a firm is as a contracting mechanism between providers of financial capital (the principals) and managers (the agents). Principal-agent models are still extremely influential in corporate governance and  in reality continue to form the basis of mainstream compensation structures up to this day. In principal-agent thinking, employees are viewed as generic labor and agents for the managers. The managers are understood as having firm-specific skills and are viewed as agents of the shareholders.

The economist Brian Arthur from the Santa Fe Institute argues that the ever-increasing role of knowledge in value creation makes the foundations of economics and our thinking around firms badly outdated. Likewise, Peter Drucker predicted that “knowledge may come to occupy the place in the society which property occupied over the last three centuries.” As early as 1964 Gary Becker coined the term “human capital” to refer to the fact that many of the skills and knowledge required to do knowledge work could only be acquired if “some investment was made in time and resources”.

In his seminal work, Becker also considered the implications of the fact that some of the knowledge and skills acquired by employees have a much higher value in some relationships, some contexts, than they do in others. The labor services of employees with specialized skills thus cannot be modeled as undifferentiated generic market inputs, for which wages and quantity, the number of people, and the number of hours of work are determined. With context-specific human capital, the creativity and productivity of a particular individual depends on being part of a particular group of people engaged in particular assignments. Knowledge work is relation-specific and contextual.

More importantly, once acquired, knowledge and skills that are specialized are assets that are at risk following the very same logic as that by which financial assets are at risk. In practice, this would mean that knowledge workers should explicitly bear the long-term entrepreneurial accountability for the success or failure of the company, and additionally benefit from any possible upside, just as shareholders do today. From the point of view of corporate governance, it would mean that companies should be run in the interests of all their investors.

In firms where employees embody the critical capabilities, they must be encouraged to make creative decisions about how to act, interact, learn and innovate. One way to do that is to give them sufficient claims on the long-term returns, in other words to give them ownership rights and responsibilities.

The puzzling thing about the on-demand trend is that when it comes to actual work practices, there is really nothing new despite the powerful technologies and great new interfaces. It is a replication of the industrial model that separated labor, management and shareholders. If we believe Gary Becker, the big societal problem we are about to face is that on-demand work limits the value potential of human effort.

But there is an alternative conceptualization. Knowledge work is defined as creative work we do in interaction. The price of technology is going down rapidly and the cost of starting a company has decreased dramatically. These trends give knowledge workers more power relative to employers. If knowledge is more important than money, it gives human capital more power relative to financial capital, potentially changing the concept of the corporation.

The future of capitalism depends on whether firms create a much larger number of capitalists than they do today. Everybody will benefit if, in the future, a larger number of workers think like owners and act like long-term investors. A sense of ownership could be and should be the difference between firms and markets.

We should use the Internet to create the new, not to repeat the old.

Work in the Machine Age  –  Humans Need to Apply

The oft-quoted proof of the rise of machines making human work obsolete is games in which humans lose to computers. This happened in checkers in 1994. It happened in chess 1997. Now computers match humans in Scrabble, backgammon, poker, and even Jeopardy. There is still one exception, “Go”. Why is that? What is so special about Go? The game is similar to Chess in many ways, it is a “deterministic, perfect information game”, meaning a game where no information is hidden from either player, and there are no built-in elements of chance, such as throwing a die. But there are some interesting differences.

For the first move in chess, the player has twenty choices. In typical chess positions there will be around 30-plus possible moves. A typical game lasts about 40 moves before the resignation of one party.

Go players begin with a choice of 55 possible moves. This number rises quickly and soon almost all of the 361 points of the board must be evaluated. Some are much more popular than others, some are almost never played, but all are possible. That makes for 129,960 possible board positions after just the first round of moves. A typical game of Go lasts about 200 moves. As a game of chess progresses, as well as in many other games such as checkers, pieces disappear from the board, simplifying the game. Go begins with an empty board. Each new Go move adds new complexities and possibilities to the situation. The key here is the number of choices available.

The more choices there are, the harder it gets for computers.

The industrial logic was most vividly captured in the idea of the value chain. Value-creating activities were sequential, unidirectional and linear. Those performing the following task must comply with the constraints imposed by the execution of the preceding task. The reverse cannot normally take place. The architecture consists of tightly coupled tasks and predetermined, repeating activities. The output of one task was the input of another. If-this-then-that. Work was algorithmic.

Workers in industrial-age firms were used to the rules that limited choices. The burden of decision making, with the consequent need to communicate and gather costly information, was minimized. Furthermore, by narrowing the scope of choices, the learning requirements for workers were limited. In part, the efficiency-enhancing contribution of mass-production was derived from these lower learning costs.

Work has been designed as a very, very simple game.

Is it then fair to draw the conclusion that the microchip may well replace the human race? Or have we just designed human work plain wrong? Could we, and should we, change the rules of our game?

The most important reason why we need a new concept of work/games is because the players and their contributions in the real world are, at best, too diverse to rank. They are, and should be, too qualitatively different to compare quantitatively as labor. Unlike mechanical systems, human systems thrive on variety and diversity. An exact replication of behavior in nature would be disastrous and seen as neurotic in social life.

The problem we face today is not in the capabilities of humans but in the outdated and limiting conceptualization of work. Work as we know it is mainly designed for machines, not for human beings.

Human life is non-deterministic, full of uncertainty, unknowns and surprises. Creative learning is the fundamental process of socialization and being a human. For a human being, the number of choices or moves in the game of life, in any situation, is unlimited. This is the very hard to copy difference between men and machines.

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From jobs to tasks and from the value chain to the Internet

Economic theories are derived from the era of the production of tangible goods and high-cost communications. These mind-sets are not only unhelpful, but wrong in a world of information products and ubiquitous, low-cost/high-quality connectivity.

New communication technologies have always had a strong impact on industries and the logistics around production. But this time, with information products, the societal changes are potentially even bigger than before.

The Internet is the first communication environment that decentralizes the financial capital requirements of production. Much of the capital is not only distributed, but also largely owned by the workers, the individuals, who themselves own the smartphones and other smart devices, the new machines of work. When computers were expensive, the economics of mass industrialization and its centralized management structures ruled them. Not any more!

The factory logic of mass production forced people to come to where the machines were. In knowledge work, the machines are where the people are making it possible to distribute work to where they are. Architectures of work differ in the degree to which their components are loosely or tightly coupled. Coupling is a measure of the degree to which communication between the components is predetermined and fixed or not. It was relatively easy to define in repetitive work what needed to be done and by whom as a definition of the quantity of labor and quality of capabilities. As a result, management theory and practice created two communication designs: the hierarchy and the process chart.

In a hierarchy the most important communication and dependence exists between the employer and the employee, the manager and the worker.

Manufacturing work is perhaps amazingly not about hierarchical, but horizontal, sequential dependence. Those performing the following task must comply with the constraints imposed by the execution of the preceding task. The reverse cannot normally take place. The architecture consists of tightly coupled tasks and predetermined, repeating activities. Communication typically resembles one-way signals.

Creative, highly contextual work creates a third design. It is about loose couplings and modularity, about networked tasks. In creative work, any node in the network should be able to communicate with any other node on the basis of contextual interdependence and creative, participative engagement.

The architecture of the Internet is based on the very same principle of loose couplings and modularity. Modularity is the only design principle that intentionally makes nodes of the network able to be highly responsive. The logic of modularity and ubiquitous communication make it possible for the first time to create truly network-based organizations.

Creative network-based work in the future is not about jobs, but about modular tasks and interdependence between people. You don’t need to be present in a factory any more, or in an office, but you need to be present for other people.

In an economy, people essentially produce goods and services for people. Companies are theoretically intermediary organizational forms that arrange the development, production and delivery processes. Companies can perhaps be in some cases be replaced by apps? Or managers can be replaced by apps? Or perhaps the new companies look a lot like apps like Uber or Airbnb already do. Many of these new companies see themselves as market makers rather than as service providers.

The modern firm has developed into a perfect vehicle for financial contributions and as a toolkit serves the needs of financial investors well, at least in good times. As creativity and knowledge define success today, access to capabilities is at least as important for a firm as access to money. The Internet may prove to be an extinction-level event for the corporations as we have known them. In the network economy, individuals, interacting with each other by utilizing the new apps together with relatively cheap mobile, smart devices, can now create information products.

But many things need to change!

We are as used to the employer choosing the work objectives as we are used to the teacher choosing the learning objectives. The manager directs the way in which the employee engages with work. This image of work is easy to grasp because it has been taught at school where the model is the same.

In contrast to the above, creative, digital work and the Internet have brought about circumstances in which the employee in effect chooses the purpose of work, voluntarily selects the tasks, determines the modes and timing of engagement, and designs the outcomes. The worker might be said to be largely independent of some other person’s management, but is in effect interdependent. Interdependence here means that the worker is free to choose what tasks to take up, and when to take them up, but is not independent in the sense that she would not need to make the choice.

The interdependent, task-based worker negotiates her work based on her own purposes, not the goals of somebody else, and negotiates who her fellow workers are based on cognitive complementarity and her personal network, not a given organization.

The architecture of work is not the structure of a corporation, but the structure of the network. The organization is not a given hierarchy or a predictive process, but an ongoing process of organizing. The Internet-based firm sees work and cognitive capability as networked communication.

The effects of Moore’s law on the growth of the ICT industry and computing are well known. A lesser-known but potentially more weighty law is starting to replace Moore’s law in strategic influence. Metcalfe’s law is named after Bob Metcalfe, the inventor of the Ethernet. The law states that the cost of a network expands linearly with increases in the size of the network, but the value of the network increases exponentially. When this is combined with Moore’s law, we are in a world where at the same time as the value of the network goes up with its size the average costs of technology are falling. This is one of the most important business drivers today. The implication is that there is an ever-widening gap between network-economy companies and those driven by traditional asset leverage models. The industrial economy was based on economies of scale inside the corporation. The new focus is outside, in network economies.

The most important model is a network structure where the value of all interactions is raised by all interactions; where every interaction benefits from the total number of interactions. These are the new network businesses.

In practice this means that digital services can attain the level of customer reach and network size, required to capture almost any market, even as the size of the company stays relatively small. This is why network-economy based start-ups have such a huge advantage over asset leverage based incumbents.

The key understanding is that it is now the customers or members of the network who create value, not the network owner.

Yes, customer focus has been the dominant mantra in business. Up to now, business has focused on the customer as an audience for products, services and marketing communications. In the world of digital networks, the customer will be transformed from being an audience to an actor.

The central aggregator of enterprise value will no longer be a value chain. The Internet is a viable model for making sense of the value creating constellations of tomorrow.

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The two faces of digital transformation

Have you ever wondered why you don’t see anyone reading a book when you visit companies? We associate reading with finding information and learning, but we also include qualities such as contemplation, solitude and mental privacy when we think about books.

There is a mental framework that is used when dealing with books, and another distinct mental framework regarding information-related practices in the corporate world. Basically, you are not allowed to read a book, but you can read a document.

Documents and word processing are part of the framework of management today. Documents were born from the needs of a hierarchical, systemic approach to management. Top-down information was in the form of PowerPoint slide decks containing vision statements, Excel sheets with goals and Word documents explaining corporate procedures. Bottom-up information was used mainly to provide reports and data for managers, helping them to keep their employees accountable and to ensure the smooth operation of the business process.

Computerized word processing is associated with terms such as information flows and the sharing of information. This is not something you normally talk about when discussing a book. While a book provides a view of the contemplative mind, documents create a view of controlled content.

Are you still asking why you can read a document but you are not allowed to use Facebook?

Instead of predictive process flows, creative work follows a different logic. Work is about community-based cognitive presence. But cognition is just part of the answer. Work tomorrow will be even more about social presence. To work and to manage is to participate in live conversations. A dramatic shift is needed in the mental framework of information, communication and work. Without this changing mindset, no efficient digital transformations can be made in the corporate world. Work is communication. Conversations and narratives are the new documents.

The first face of digital transformation is about new ways to be present and new ways to communicate

You cannot design live interaction. Conversations cannot be controlled. The only way to influence conversations is to take part in them. You cannot plan in the traditional sense of specifying a structure or a process and then implementing it. As many have experienced, communities seldom grow beyond the group that initiated the conversation, because they fail to attract enough participants. Many business communities also fall apart soon after their launch because they don’t have the energy to sustain themselves.

Communities, unlike business units need to continuously invite the interaction that makes them alive.

Community design is closer to iterative, creative learning than to traditional organizational design. Live communities reflect and redesign themselves throughout their life cycle. This is why design should always start with very light structures and very few elements.

What is also different is that a good community architecture invites many kinds of participation. We used to think that we should encourage all the community members to participate equally. Now we know that a large number of the network members are, and should be, peripheral. In a traditional meeting we would consider this type of participation half-hearted, but in a network a large percentage of the members are always peripheral and rarely contribute. Because the boundaries of a live community are always fluid, even those on the outer edges can become involved for a time as the focus shifts to their area of particular interest.

Because conversations and communities need to be alive to create value, we need an approach to management that appreciates passion, relationships and voluntary participation. Rather than focusing on accountability, community design should concentrate on energizing, enriching participation.

The new structures and new designs are about communities continuously organizing themselves around shared contexts, meaning shared interests and shared practices. The focus of industrial management was on the division of labor and the design of vertical/horizontal communication channels. The focus should now be on cooperation and emergent interaction based on transparency, interdependence and responsiveness.

The really big objective of the social side of digital transformation is to reconfigure agency in a way that brings relationships into the center. Success today is increasingly a result of skilful participation: it is about how we are present and how we communicate. Through new technologies, applications and ubiquitous connectivity, we have totally new opportunities for participation and communication – potentially changing the way we work together.

The customer of the industrial age was seen as a recipient of value, or a consumer of value. Enterprises also viewed customers through the lens of a fairly uniform set of features, leading to customers being seen as having relatively uniform needs. But even commodity products are always a bundle of use contexts, buying patterns, complementary goods and delivery options. Just because a product is a commodity doesn’t mean that customers can’t be diverse in the ways they use the product. Different customers use products that are manufactured in the same way, with the same product features, differently. This is why customers are today understood to be active contributors to value creation. Without their part, the value of the product could not exist.

Companies used to have no mechanisms for connecting with the end users in order to understand and influence what was going on. Digital technologies are now changing this. When a customer teaches a firm what she wants or how she wants it, the customer and the firm are also cooperating on the sale of a product, changing the industrial approach to sales and marketing. The marketing and sales departments used to be the customer’s proxy, with the exclusive role of interpreting changing customer needs. Internet-based business necessarily transforms the marketing function and sales specialists by formally integrating the customer into every part of the organization. The customer of tomorrow will interact with, and should influence, every process.

As the goal is to create more value together, a critically important new element is embedded computing, the integrated intelligence that is attached to the “things”, the offerings, the products.

It is about creating new software code. It is about two new digital layers for all products: (1) an algorithmic layer, which can mean sensors or location and usage data allowing totally new kinds of data analytics and (2) a network layer.

As the customer’s need set is expanded beyond the pre-set features of the physical offering through software, the definition of the product changes and becomes more complex. The more complex the product, the more opportunities there are for the company to learn something that will later make a difference.

The value of the code may determine the value potential of a product more than the physical product itself. The effectiveness of an offering is related to how well it packages the learning from past activities and how it increases the users options for value creation. A product or a service should be pictured as a node in a network with links to other use cases, supplementary services and complementary features surrounding the product. The more relevant the links are considered to be, the richer the product will become. The task today is to visualize the product in the broadest sense possible.

The study of isolated parts offers little help in understanding how connected parts work in combination and what emerges as the result of network connections. What new relational technologies are making possible for manufacturing industries is a much, much richer repertoire of potential futures than what we were used to in a traditional industrial firm.

The ability to create value in a remarkably more efficient and resource-wise way corresponds to possibilities for interaction with other relevant parts and actors. If interdependent links are few, poor, or constraining, the activity and value potential will be limited.

Interestingly, the same principle applies both to things and to human beings!

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More: The product is the medium.