Technological Revolutions and the Governance Gap

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Technological Revolutions and the Governance Gap

The Core Problem of Management Today

Sur-veil-lance Cap-i-tal-ism, n. 1. A new economic order that claims human experience as free raw material for hidden commercial practices of extraction, prediction, and sales; 2. A parasitic economic logic in which the production of goods and services is subordinated to a new global architecture of behavioral modification; 3. A rogue mutation of capitalism marked by concentrations of wealth, knowledge, and power unprecedented in human history; 4. The foundational framework of a surveillance economy…

Shoshana Zuboff – The Age of Surveillance Capitalism

The problem that Shoshana Zuboff outlines in her book The Age of Surveillance Capitalism is one of governance. As technology races ahead, the norms and institutions that we need to support (or contain) it lag behind.

Scott Brinker frames this problem as Martec’s Law:

Scott Brinker via Neil Perkin

When technology is changing rapidly, the fact that norms, managerial practice, institutions and cultures change at a much different pace creates substantial problems. The disconnect between technological change and organisational change (norms, managerial practice, institutions and culture) can be called a Governance Gap.

Bridging this Governance Gap is one of the core problems of management today.

I’ve used this diagram in classes and lectures, but as I think about it more, I think it’s incomplete. One important missing part is time.

Innovation and Pace Layers

Stewart Brand looks at what makes ecosystems resilient, and builds a model for societies as well in his book The Clock of the Long Now. The system has layers of differing scales, with differing rates of change. Some are shallow and fast, while others are deep and slow. He says:

Consider the differently paced components to be layers.  Each layer is functionally different from the others and operates somewhat independently, but each layer influences and responds to the layers closest to it in a way that makes the whole system resilient.

From the fastest layers to the slowest layers in the system, the relationship can be described as follows:

Fast learns, slow remembers.  Fast proposes, slow disposes.  Fast is discontinuous, slow is continuous.  Fast and small instructs slow and big by accrued innovation and by occasional revolution.  Slow and big controls small and fast by constraint and constancy.  Fast gets all our attention, slow has all the power.

All durable dynamic systems have this sort of structure.  It is what makes them adaptable and robust.

Stewart Brand

The overall system looks like this:

“The fast layers innovate; the slow layers stabilize. The whole combines learning with continuity.”

When you think about it this way, then Martec’s Law makes perfect sense. Of course norms, managerial practice, institutions and cultures change more slowly than technology does – they are all part of the slower pace layers.

When new technologies or new techniques arrive, there are many different versions around as people try to solve the technical problems involved. This is technology operating at the layer of Fashion.

Once the technology becomes relatively stable, a new business model emerges – this is the conversion of the rapid, almost frantic level of innovation going at the Fashion layer into a more stable version at the Commerce layer.

Infrastructure moves even more slowly. If you were an early user of Twitter, you’ll remember the Fail Whale – this popped up every time Twitter’s servers crashed. Up until about ten years ago, just getting enough servers online to support a rapidly growing website was close to impossible. Then, Amazon came up with Amazon Web Services, and other Server-as-a-Service businesses emerged. When this happened, the Infrastructure layer had caught up with the Fashion and Commerce layers.

The problems that Zuboff outlines in her book are the ones that arise when the Governance and Culture layers have not yet adapted to the new business models generated by firms like Google and Facebook. Her book lays out the case for the problems that are being caused by the rapid technological change that is out of synch with innovation in governance – a perfect example of the Governance Gap.

Innovation happens at all of the layers except Nature. Nature is the generator of change to which all the other layers must respond. So what happens when innovation at all of the layers is synchronised? According to Carlota Perez, that’s when we see a Golden Age.

Bubbles and Golden Ages

So here’s how I think we need to use Martec’s Law a bit differently. We need to realise that it’s true over the short term, and it describes the challenge of synchronising change between pace layers.

But if we take a longer-term view, a couple of things become apparent. The first is that technological, or any kind of change, never accelerates exponentially forever. It eventually flattens out – it follows an S Curve.

The second thing is that, as discussed, once change flattens out at one of the faster layers, the slow layers innovate to stabilise, and they catch up.

This process is documented very well by Carlota Perez in her absolutely brilliant book Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages. In it, she looks at how major technological revolutions get embedded at the deeper, slower Governance and Cultural layers.

The argument in the book is summarised by this diagram:

Source: Oxfam Blogs

This process is described by Jorge Camacho in a terrific post on the future of design:

Following the so-called “big bang” of each technological revolution, there comes a period of ‘installation’, lasting roughly 20 to 30 years, in which the economy, as it were, explores the new space of possibilities. This is a period of ‘creative destruction’ marked by an increasing concentration of wealth and rising levels of inequality, i.e. a ‘Gilded Age.’ All the capital flowing into the new technologies eventually cause a bubble that bursts into a crisis and recession in the middle of the cycle. This variable period is characterized by high levels of financial speculation. After this turning point, there comes a period of ‘deployment’ in which capital finds its way back into production thus leading to a widespread application of the new techno-economic paradigm in society at large. This is a period of ‘creative construction’: a ‘Golden Age’ characterized not only by sustained growth but also, most importantly, a more equal spreading of the benefits across society.

Jorge Camacho

It’s important to remember, however, that none of this happens automatically. There are no deterministic rules that say “the slower layers always catch up to the faster ones.” We need to actively work to bring that about.

What Should We Do Now?

All this long-term thinking is fine – but right now, today, we have a lot of Governance Gaps to deal with. The technical change curves haven’t been flattening out yet for things such as artificial intelligence, machine learning, cybersecurity, robotics, autonomous vehicles and drones, blockchains, industry 5.0, the internet of things, and augmented and virtual reality.

The fact that some of these have applications are still in the very frothy Fashion layer means that a lot of the ideas around these technologies are just noise. The first thing we need to do is to get better at figuring out for which ones this is true. One clue to look for here is emergent business models – these are a sign that a new technology is starting to coalesce around a dominant design, that may well have some legs.

The second thing to do is to get better at business model innovation. This is the avenue over which new technologies get embedded into the normal function of our existing organisations. If we’re in an industry experiencing change, business model innovation is a core skill.

Finally, it makes sense to think about how to use these new technologies responsibly. It’s been well-documented that when new technologies such as artificial intelligence and machine learning are used in areas such as hiring and other HR functions, the provision of healthcare, and access to education, there is a strong tendency for the algorithms to reinforce existing social inequalities. At the personal and organisational levels, we must ensure that our use of new technologies decreases existing inequalities rather than increasing them.

At the social level, we can use these technologies and approaches to try to achieve fairer outcomes through work on increasing sustainability in management, or addressing disparities in opportunity. These are the areas that Perez has moved to now, with an emphasis on the role of the state in addressing these issues.

If we think about these issues as we deploy new technologies, and use them responsibly, it makes it much more likely that our organisation’s business model will synch with the deeper, slower layers that will ultimately determine how these technologies will be used over the long run.

And this is crucial, because, over time, slow has all the power.

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