A Conversation on Post-Industrial Economics with Esko Kilpi


Seeing through the clouds

 

Esko Kilpi was the founder and principal of Esko Kilpi Oy, a research and consultancy firm based in Finland working with the challenges of knowledge work and digital work environments. I didn't know Kilpi, and his death (January 2020) means I won't be able to have the conversation with him.

The article from October 2015 I wanted to discuss is no longer online. But I had the presence of sharing it in its integrity by email. I shared thoughts about it with a friend in a short thread. To this day, email continues to be the most underutilized social network.

Before I get into the article, I wanted to report on a sidebar conversation I had about how I think differently. Rather than go on about me, I'll talk more broadly about how men and women think. My friend Peter told me about an event he organized a few years back about storytelling.

An Aboriginal elder was going to attend, and at the last minute she was called away. The security guard happened to be an aboriginal man who coincidentally was an elder. So they improvised. He began by telling the group made of men and woman a story. Then, he asked the group to separate into men and women to discuss and retell their story. Many in the group were more than a little horrified by the segregation into “men’s business” and “women’s business.” But sure enough there were different insights represented by the sexes.

Many of my conversations could remind you of this story. Neither insight was better. Just different. If there's wisdom in the ancient division of men and women’s business it is that women think differently and you should pursue that before thinking your ideas are better.

Kilpi's thinking about interactive value creation moved my thinking and work. Since value is a main vector in my work on culture, I wanted to have the conversation and you the context and see where the exploration could lead. The point, in other words, is not to agree/disagree, but to be curious about the ideas seven years on.

 

Conversation on post-industrial economics

Kilpi indented.

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.

If you've seen more birds in cities, intensive farming is the culprit. A recent Stanford study looks at the long-term effects of farming practices on bird biodiversity in Costa Rica. From the researchers: “Farms that are good for birds are also good for other species.” “Local farming practices really matter in protecting biodiversity and building climate resilience.”

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.

But simplified systems are relatively easy to change, you may say. Are complex systems incredibly hard to change or adapt? Do they ossify as people try to fix them?

For this part of the conversation on complexity, I'd like to refer to Dave Snowden. Talking things out for sensemaking works for small, contained issues. Which might be a symptom of a deeper problem. Bringing in a group to talk it out might squeeze the issue to another part of the organization. Leaving the actual problem undiscovered.

Parts could be helpful to break down the problem. Our propensity for quickly jumping into approach and tactics is how we fail to recognize the nature of the challenge. That's one part. The other part is our failure to recognize that when representations arise collectively, that gives them great power.

Physicist David Bohm worked on quantum theory, neuropsychology, and the theory of mind. His On Dialogue is my reference for the nature of collective thought. “If everybody agrees on something, we take it as evidence that it's right or it could be right.” Fact as “what has been made” or  “manufacture” (Lat.) Hence the pressure to agree.

Our view of efficiency in firms still follows the line of thinking of efficiency in 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; demand and supply.

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.

I've long talked about how our spare-parts approach to work is a problem. If homo economicus is paramount, then how do you explain forgetting the basics of trading? Something that continues to stump me: companies that will only hire people who already have jobs.

Employees are one of the highest input costs to a business. Employing only the employed puts an artificial floor on the buy price. In other words, the business stupidly pays more than it has to because its HR department uses employment as a proxy for value. 

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 the 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 gives the control over 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.

Therefore the mechanics of how the hand-offs and processes work need to do the heavy lifting. Peter Tunjic has been working on this for more than a decade. He says that before we talk about teamwork and individual talent, we need to get the understanding of the forces of direction in business right. The promise the business makes, what it is, and where it's going come before how to steer it to keep with the nautical example. 

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 do 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.

Algorithms seduce us with the promise of scale. But the story isn't the whole story. Does the algorithm solve the human bias problem, or does it compound it? Are there unintended consequences associated with heavy reliance on algorithms for decision-making? How do we decide where to draw the line?

Taking a philosophical stance: Is it possible to encode ethics in objective statements? Whose moral code do we select to judge value? What are the cultural implications?

On the platforms, what can we do about their sameness? What does a platform economy do to people? If you're curious about economics as if people mattered, I put a few thoughts in a conversation on this topic. What if we were to apply the guiding principles that have endured over centuries?

Which would lead to some form of entrepreneurial ecosystem. On this topic, perhaps netonomics, a word I made up for network economics, will replace destructive economies of scale. The idea is not new: Cooperatives and networks of specialized firms connected into a system of production have been the backbone of economies of scale in my region of the world for centuries.

I believe that the future of human work is situated. Even after the captains are automated, the pilots may still be human beings. Even after the surgeons are robots, the nurses may still 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, I believe 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, 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.

The cooperative system in Emilia-Romagna has been the reference point for companies around the world. I agree wholeheartedly on the connection with the territory, also a very strong cultural component of smart Italian business people for this reason.

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

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

We're at a time of “not anymore,” and a time of “not yet.” Mathematician and physicist Freeman Dyson made an observation about human society that can help you grasp what working at different time scales involves (emphasis mine):#

“The destiny of our species is shaped by the imperatives of survival on six distinct time scales,” said Dyson. “To survive means to compete successfully on all six time scales.  But the unit of survival is different at each of the six time scales. On a time scale of years, the unit is the individual. On a time scale of decades, the unit is the family. On a time scale of centuries, the unit is the tribe or nation. On a time scale of millennia, the unit is the culture. On a time scale of tens of millennia, the unit is the species. On a time scale of eons, the unit is the whole web of life on our planet. Every human being is the product of adaptation to the demands of all six time scales. That is why conflicting loyalties are deep in our nature. In order to survive, we have needed to be loyal to ourselves, to our families, to our tribes, to our cultures, to our species, to our planet. If our psychological impulses are complicated, it is because they were shaped by complicated and conflicting demands.”

He reduces the problem of complexity to its essence. Imagine each time horizon and stakeholders represented by a crystal ball, if you like. You have six of them to keep going at all times. Drop one, and it breaks. “Don't drop the ball” takes a whole new meaning.

How do we get better at now? That's where our experience determines what we do next.

I'll leave you with a final thought from Esko Kilpi: Our humanity needs to develop at the same speed as our technology.

 

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