Esko Kilpi on Interactive Value Creation

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

A pattern language of post-industrial work

At the core of the post-industrial era is the idea that people should design for themselves. This principle applies also our value creating entities. This may sound radical but comes from the observation that most of the value on global scale is not created by firms but by people. People, then, should learn to be better designers. When designing something we always rely on certain patterns. We are in the midst of a shift from the industrial pattern of supply and demand to social, interactive patterns.

The customer is now seen as being directly and actively involved in the key moments of value creation as opposed to passively consuming value. There are profound implications that result from this change of thinking. Products and services are not reproducible as such any more. Solutions are by default contextual, but they can be starting points for someone else to create value. Creative, connected learning is at the core of the post-industrial business.

The most important principle is to build the organization around three design patterns: (1) Relations, (2) Network effects and (3) Solving problems /Asking questions.

Relations

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.

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. 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.

To succeed you need relationships and interaction. When customers are identified as individuals in different use contexts, the sales process is really 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 expert skills. The decisive thing was your individual knowledge. Today you work more from your network than your skills. The decisive thing is your relations. 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 digital transformation is to reconfigure agency in a way that brings relationships into the center. Success today is increasingly a result of skillful 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.

Network effects

The new platforms can be a valuable, shared resource making 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. 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 supply-side economies of scale inside the corporation. The new focus is outside, in demand-side 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. 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. 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.

Solving problems /Asking questions

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.

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. 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.

The new design patterns create new opportunities. It is not about having a fixed job role as an employee or having tasks given to you as a contractor. The most inspiring and energizing future of work may be in solving problems and spotting opportunities in creative interaction with your customers.

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

Työ on toisiaan tarvitsevien ihmisten vuorovaikutusta

Tietointensiivinen työ on erilaisten ajatusten ja tarpeiden kohtaamisia ja yhteisvaikutusta. Työ on myös sopimista: sopimuksia siitä mistä puhutaan ja mitä teemme, mistä pitäisi puhua, mitä pitäisi tehdä? Mikä on tärkeää ja mikä on vähemmän tärkeää? Työ on sopimista siitä kuinka edetään yhdessä, kuinka tehdään valintoja ja mitä valitaan. Puhumme yhteiskuntasopimuksesta tai paikallisesta sopimisesta, kun tarkoitamme yhteistä etenemistä yhteiskunnan tasolla tai yritysten ja työntekijöiden tasolla.

Ongelmat syntyvät siitä, että uskomme että juuri meidän näkökulmamme ja meille tärkeät merkitykset ovat jaettuja. Emme näe seiniä ympärillämme ja siiloja joista kaikki katsovat maailmaa, myös me. Koska omat ajatuksemme ovat meille selkeitä ja perusteltuja omista lähtökohdistamme, niin kai ne ovat sitä kaikille muillekin?

Kognitiivinen tietotekniikka (cognitive computing) on nostanut esille merkitystietoisuuden ja kielitietoisuuden käsitteet pyrittäessä ymmärtämään yhteisöllistä työtä, informaation tehokkaampaa käsittelyä ja kun halutaan  edistää tietotyön tuottavuutta. Monelle on ehkä yllättävää, että kieli ja sen säännöt tulevat olemaan tietotekniikassa yhtä tärkeässä asemassa kuin matematiikka ja sen säännöt.

Tuotamme työssä koko ajan sisältöjä joiden merkitys voidaan ymmärtää hyvin monella tavalla. Mikään tuotos ei ole objektiivinen fakta vaikka mediateollisuus on pitkään näin omista sisällöistään väittänytkin. Tarvitaan merkitystietoisuutta. Ongelmaksi nousee se, että olemme parhaimmillamme hyviä ilmaisemaan itsellemme selviä asioita itsellemme selvästi, mutta ilman vuorovaikutuksessa tapahtuvaa sopimista ne merkitykset joita herätämme muissa ovat jotain aivan muuta kuin mitä kuvittelemme niiden olevan. Voimme puhua jostain asiasta yhdessä kuukausia pääsemättä yhtään minnekään kuten yhteiskuntasopimuksen kanssa on nyt tilanne. Paikallinen sopiminen saattaa silloin tarkoittaa käytännössä vain paikallista riitelyä. Työ on sopimista ja sopiminen voi olla työn tärkein sisältö ja siinä onnistumisen tai epäonnistumisen mittari.

Kielitietoisuus on kognitiivisen tietotekniikan näkökulmasta ymmärrys niistä vaihtoehtoisista rakenteista, sanoista ja tavoista kommunikoida joita meillä on käytettävissä ja joista valitsemme. Emme useinkaan tiedosta valintojamme jonka takia ne ovat valitettavan usein vanhaa toistavia automaatioita. Eräs työmarkkinaveteraani sanoi minulle: ”Tässä samassa tilanteessa sanon aina nämä samat lauseet koska minulta odotetaan niitä. Puhun julkisuudessa enemmän omille taustajoukoilleni kuin pöydän toisella puolella istujille” Sama malli on erityisen tyypillistä poliittiselle puheelle.

Emme useinkaan tiedosta omaa kommunikaatiotamme ja sen roolikeskeisyyttä. Puhumme kuten oletamme että roolissani tulee puhua emmekä kuten tässä tilanteessa voisi puhua. Valinnat ovat sidonnaisia johonkin käsitykseen todellisuudesta joka useimmiten on sosiaalisesti ja historiallisesti määrittynyt. Haasteeksi muodostuu mukaillen Albert Einsteinia: ongelmia ei useinkaan voida ratkaista samanlaisella kielenkäytöllä mikä on luonut ne.

Kognitiivisen tietotekniikan alueella tehdään tänään ehkä mielenkiintoisinta perustutkimusta liittyen tietotyön käytäntöihin ja tiedon johtamiseen (knowledge management). Tämän alueen tutkijat korostavat, että tapamme kommunikoida muovaa meitä itseämme enemmän kuin kuvittelemme kielemme muovaavan muita. Omat viitekehyksemme määrittävät sitä mitä havaitsemme, mitä näemme, mitä nostamme tarkasteluun, miten käsittelemme tarkastelussa olevia asioita ja miten lopulta tulkitsemme maailmaa. Emme kuitenkaan ole koskaan yksin. Opimme ”oikean” tavan kommunikoida tullaksemme hyväksytyksi yhteisöön ja sen täysivaltaisiksi jäseniksi. Opimme sen oikean tavan yliopistoissa, järjestöissä ja työpaikoilla. Kielen kautta liitymme ja säilymme heimon jäsenenä.

Mitä pidempään olemme olleet saman yhteisön jäsenenä sitä vähemmän kyseenalaistamme ajatusmallejamme ja sitä vähemmän ymmärrämme niistä poikkeavia lähestymistapoja. Sama ryhmäytymisen mekanismi toimii niin, että koska ”Me” olemme lähtökohtaisesti oikeamielisten joukko ja koska ”He” eivät ole meitä, heidän täytyy olla väärässä, kaikissa tapauksissa.

Mitä vahvempaa heimoutuminen on sitä vaikeampaa on erilaisuuden kohtaaminen ja myös asioista sopiminen ”heidän” kanssaan. Sosiaalinen hyväksyntä omien taholta menee aina muiden, ulkopuolisten, kanssa yhteisen ajatuksen liikkeen edelle. Vallitsevien ajatusmallien pönkittäminen ja ylläpitäminen on keino pitää yllä yhteisöä, vaikka kaikki ympärillä olisikin muuttunut.

Tässä tilanteessa erilaisten ihmisten ja näkemysten luovaa yhteistyötä ei voi syntyä. Kommunikaatio on televisiokeskustelujen tutuksi tekemää raivokasta puolustustaistoa jolla yritetään ylläpitää uhan kohteena olevaa yhteisöllistä ja henkilökohtaista identiteettiä.

Vuorovaikutuksen tavoitteena ei voi olla lähtökohtaisesti toisen osapuolen näkökulmien kyseenalaistaminen, mutta ei myöskään toisen näkökulmien  omaksuminen. Tavoitteena on erilaisuudesta lähtevä uuden tiedon luominen ja olemassa olevien uskomusten rakentava tarkastelu.

Työ on toisiaan tarvitsevien ihmisten vuorovaikutusta. Kompromissien sijaan sopiminen (voi) tarkoittaa uusien mahdollisuuksia ja vaihtoehtojen luomista yhdessä.

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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The past and the future of work

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 way we view work life is influenced by the way we view the world. This view rests on the most fundamental assumptions we make about reality. In the present competitive view of the world, we often think that the most capable are those who are the most competitive, and accordingly that competition creates and secures capability and long-term viability in the world (of work).

But what if high performance is incorrectly attributed to competition and is more a result of diversity, self-organizing communication and non-competitive processes of cooperation?

Competitive processes lead to the handicapping of the system that these processes are part of. This is because competitive selection leads to exclusion: something or somebody, the losers, are left outside. Leaving something out from an ecosystem always means a reduction of diversity. The resulting less diverse system is efficient in the short-term, competition seems to work, but always at the expense of long-term viability. Sustainability, agility and complex problem solving require more diversity, not less.

As losers are excluded from the game, they are not allowed to learn. The divide between winners and losers grows constantly. Losers multiply as winning behaviors are replicated in the smaller winners’ circles and losing behaviors are replicated in the bigger losers’ circles. This is why, in the end, the winners have to pay the price of winning in one-way or another. The bigger the divide of inequality, the bigger is the price that finally has to be paid. The winners end up having to take care of the losers, or two totally different cultures are formed, as is happening in many places today. Psychologically, competitive games create shadow games of losers competing at losing. These start-ups are trained in jails and the pitching takes place on streets very far away from the Sand Hill Road.

The games we play have been played under the assumption that the unit of survival is the player, meaning the individual or a company. However, at the time of the Anthropocene, the reality is that the unit of survival is the player in the game being played. Following Darwinian rhetoric, the unit of survival is the species in its environment. Who wins and who loses is of minor importance compared to the decay of the (game) environment as a result of the actions of the players.

In games that were paradoxically competitive and cooperative at the same time, losers would not be eliminated from the game, but would be invited to learn from the winners. What prevents losers learning from winners is our outdated zero-sum thinking and the winner-take-all philosophy.

In competitive games the players need to have the identical aim of winning the same thing. Unless all the players want the same thing, there cannot be a genuine contest. Human players and their contributions are, at best, too diverse to rank. They are, and should be, too qualitatively different to compare quantitatively. Zero-sum games were the offspring of scarcity economics. In the post-industrial era of abundant creativity and contextuality, new human-centric approaches are needed.

Before Adam Smith wrote “The Wealth of Nations” and came out with the idea of the invisible hand, he had already written something perhaps even more interesting for our time. In “The Theory of Moral Sentiments” he argued that a stable society was based on sympathy. He underlined the importance of a moral duty — to have regard for your fellow human beings

Cooperative processes are about interdependent individuals and groups defining and solving problems in a shared context. Individuals competing on job markets may be one of the historic mistakes we have inherited from the industrial age. It made sense a 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 in a competitive game. The higher performance and robustness are emergent properties of cooperative interaction. They are not attributable to any of the parts of the system or to functioning of the markets.

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 all of the parts. What we have called the “whole” is an emergent pattern of interaction, not the sum of the parts.

The same principle explains why we have financial crises that no one planned and wars that no one wants. On the other hand, the great societal promise is that interaction in wide-area networks, with enough diversity, can solve problems beyond the awareness of the individuals involved.

What defines most problems today is that they are not isolated and independent but connected and systemic. 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. Following the rhetoric of game theory: what each person does affects and depends on what everyone else will do and vice versa.

Most managers and 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 management of interactions, only the actions of parts taken separately. Even more, compensation structures normally rewards improving the actions of parts, not their interactions.

Work that humans do used to be a role, now it is a task, but it is going to be a relationship: work is interaction between interdependent people. The really big idea of 2016 is to reconfigure agency in a way that brings relationships into the center. The mission is to see action within relationships.

Amyarta Sen has written that wealth should not be measured by what we have but what we can do. As we engage in new relationships and connect with thinking that is different from ours, we are always creating new potentials for action. In competitive/cooperative games the winners would be all those whose participation, comments and contributions were incorporated in the development of the game.

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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From the industrial economy to the interactive economy

Over the past years, mobile technologies and the Internet have laid the foundation for a very small size, low-cost enterprise with the potential for managing large numbers of business relationships.

The impact of these new actors has been hard to grasp because we are used to thinking about work from a different perspective. Our thinking arises from a make-and-sell economic model. Most managers still subscribe to this and think that the core of creating value is to plan and manage a supply chain. A supply chain is a system of assets and transactions that in the end make the components of the customer offering. At the beginning of the supply chain are the raw materials and the ideas that start the sequence leading, hopefully, to a sale.

This is now being supplanted by a different paradigm; a relational, network approach enabled by new coordination technologies. The manufacturer may even be just one of the nodes in the network and the customer is not a passive consumer but an active part of the plan.

The old model companies are ill equipped for this digital transformation. Mass-production and mass media organizations are still much more prepared to talk to customers than to hear from them, not realizing that one-way communication was just a fleeting accident of technological development. It is not that customers didn’t have needs and reflections they would have liked to communicate.

We are passing through a technological discontinuity of huge proportions. The rules of competition may even be rewritten for the interactive age. The new interactive economy demands new skills: managing the supply-chain is less important than building networks and enabling trust in relations. You could perhaps call the new reversed sequence an on-demand-chain. It is the opposite of the make-and-sell model. It is a chain of relationships and links that starts from interaction with the customer and leads up to the creation of the on-demand offering. As Steve Jobs put it in a different context: “you start with the customer experience and work backwards to the technology. You can’t start with the technology and try to figure out where you’re going to try to sell it.”

Adapting the interactive model is not as easy as identifying customer segments or a niche market because communication can no longer be confined to sales and marketing, or to the ad agency, as in the make-and-sell model. Also to talk about a “segment of one” is misleading because one-way communication changes here to true two-way dialogue. The interactive enterprise must be able to integrate its entire network around the needs of each individual customer context. The on-demand-chain means continuous on-demand learning and continuous change. Your dialogue with an individual customer will change your behavior toward her and change that customer’s behavior toward you. People develop together in interaction.

A learning relationship potentially makes the whole network smarter with every individual interaction creating network effects. Accordingly, the enterprise increases customer retention by making loyalty more convenient than non-loyalty as a result of learning. The goal is to create more value for the customer and to lower her transaction costs. This kind of relationship ensures that it is always in the customer’s self-interest to remain with the people who have developed the relationship to begin with. The main benefit for the network partners may not be financial. The most valuable thing is to have access to “community knowledge”, a common movement of thought. It means to be part of a network where learning takes place faster than somewhere else.

In the mass-market economy, the focus was to create a quality product. With increased global competition and with so many quality products around that is not enough any more. To succeed you need high-quality relationships. When customers are identified as individuals in different use contexts, the marketing process is really 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 relational approach is the third way to work. It is not about having a fixed job role as an employee or having tasks given to you as a contractor. The most inspiring and energizing future of work may be in solving problems and spotting opportunities in creative interaction with your customers.

The industrial make-and-sell model required expert skills. The decisive thing was your individual knowledge. Today you work more from your network than your skills. The decisive thing is your relations.

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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”.

Collaborative and Competitive Creativity

Pablo Picasso visited Henri Matisse often during the spring of 1946. Matisse was pleased to see him. Matisse was 76 and had endured arduous colon surgery. Much of his work was now done either in bed or from a wheelchair. Simon Schama tells the story that after one of these visits Henri Matisse wrote to his son Pierre: “Picasso came to see me with a very pretty young woman. He could not have been more friendly and said he would come back and have a lot of things to tell me. But he saw what he wanted to see, my works in cut paper, my new paintings. That’s all he wanted. He will put it all to good use in time.”

Art historians claim that the relationship between Picasso and Matisse was by turns collaborative and competitive. It was a kind of an on going sparring match between two great masters.

The new technological environment of business has something in common with the world of Picasso and Matisse. It is marked by conflicting constraints, variables that shift very rapidly and value-creating relationships that change constantly. It is a complex environment.

In complex environments, the way to proficiency is to recombine successful elements to create new versions, some of which may thrive.

As a result, not just the user interfaces, but the operating system of work is starting to change in a radical way. The traditional industrial approach to work was to require each worker to assume a predetermined responsibility for a specific role. The new approach represents a different logic of organizing based on neither the traditional market nor a process. Whereas processes involve relations based on dependence and markets involve relations based on independence, the new networks involve relations of dynamic interdependence. A bit like the relationship between Matisse and Picasso. Minimal hierarchy, organizational diversity and responsiveness characterize these architectures. They are a necessary response to the increasing fuzziness of strategic horizons and short half-life of designs. Because of greater complexity, coordination cannot be planned in advance. Authority needs to be distributed; it is no longer delegated vertically but emerges horizontally. Under distributed authority work teams and knowledge workers need to be accountable to other work teams and other knowledge workers. Achievement depends on learning by mutual accountability and responsiveness.

Management and strategy used to be about rational choice between a set of known options and variables. The variables of creative work and complex environments have increased beyond systems thinking and process design. Under circumstances of rapid technological change, the management challenge is to create openness to possibilities and plausible options.

Success is based on continuous redefinition of the organization itself. It is about recombining options and contributions in a competitive and cooperative environment. Creativity is the default state of all human work. Even the most creative people are more remixers of other peoples’ ideas than lone inventors. Technology and development in general are not isolated acts by independent thinkers, but a complex storyline.

The democratization of technology that is taking place at the moment does not determine social and organizational change, but does create new opportunity spaces for new social practices. The opportunity we have is in new relational forms that don’t mimic the governance models of industrial firms. Network theory suggests that what the system becomes emerges from the complex, responsive relationships of its members, continuously developing in communication.

Like Henri Matisse and Pablo Picasso.

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Thank you Simon Schama

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