Thu, 28 May 2020

IAN MANN REVIEWS: Making chaos work for you

12 Jul 2019, 23:43 GMT+10

'Deep Patient' is a type of 'artificial intelligence'. It is artificial because it is a type of machine learning, and machines know nothing about what data represents. All they can do is find relationships among millions of pieces of data.

Deep Patient could discover that a particular patient being treated by her doctor has a 72% chance of developing schizophrenia, a diagnosis that would be an impossible task for a doctor. It would require internalising millions of points and each of their connections and weightings, to arrive at the same conclusion. This would be an unimaginable task for any human being, let alone one with a waiting room full of patients to attend to.

That 11 by 5-centimetre cell phone in your pocket is a navigation system, can handle type-ahead predictions, language translation, music recommendations, and much more. You are already relying on machine learning.

A professor of philosophy memorably told me when I was a graduate student that any society that doesn't respect both its philosophers and its plumbers, will find that neither its ideas nor pipes hold water. This book is philosophical: it is intended for plumbers and the CEOs of multinational plumbing parts manufacturers.

Our imperfect knowledge about the world has for centuries rested on the assumption that if we work hard enough and think clearly enough, the universe will yield its secrets. It won't, and it cannot: there isn't a box of secret rules.

That does not mean we cannot act intelligently: we can and must. However, the fundamentals of our thinking and decision making must change in the light of the chaos we now experience and are beginning to understand and internalise.

That insight is the profound value of this book. The volume of data and information that we can access, is immense beyond all possible comprehension. This leads to the conclusion that the "true complexity of the world far outstrips the laws and models we devise to explain it."

READ: WATCH: Robot uses machine learning to harvest lettuce

In an age as chaotic and unpredictable as this, strategy should be more important than ever. It is, but only if we adapt how we think about strategy, profoundly.

As long ago as the Socratic era, strategy was understood as finding tricks to get one out of one's military (or business) funk. Odysseus, for example, ended the Trojan War through the 'strategy' of stuffing warriors into a gift wooden horse. I hear much the same underlying request from many people who engage me in my work as a strategist.

To understand strategy as 'planning for the long-term', requires a future that's orderly and predictable enough for it to make sense. To varying degrees and in different ways, this would require that the strategy enables the company to narrow the possibilities down to the ones that the company is going to pursue.

The complexity required of this linear type of thinking, inspired a very different approach to strategy making-scenario planning. In a scenario process, managers invent and then consider, in depth, several stories of equally plausible futures for the business. While this is undoubtedly helpful in opening minds to a variety of possibilities, it is limited by a view of the world that is wrong. It is fundamentally too simplistic. No matter how sophisticated and complex the linear thinking, the world does not have a rule structure.

In her book , Professor Rita McGrath debunks Michael Porter's idea that you can ever have a "sustainable competitive advantage". Just ask any inventor of a now defunct piece of technology. Rather she promotes a "strategy of continuous reconfiguration".

This understanding requires that companies must be alerted to changes anywhere in their environment. They must have in place an organizational structure and culture that enables them to respond by disengaging from the current trajectory, to creating a new one. This is a 180-degrees flip from the outdated view of strategy as a lengthy plan, leading into an essentially knowable future.

Planet-scale changes

Scenario planning looks for planet-scale changes, whereas McGrath's approach is to be aware of small changes. This is a more appropriate response to the delicate interrelationship of every aspect of life, any bit of which might affect our business terminally, or at best give it an economic limp.

This alertness to possibilities is one example of the response for a business to a changed view of the way the world works. There is no end of implications for other areas of understanding and decision making.

If you need to be reminded of the insights of this book, you only need to think of the tiny pebble that hit your windshield and shattered it. Energy can come from tiny changes distributed throughout the system, if the system is large, complex, and densely connected enough.

The title of the book comes from "Chaos Theory". This theory provides mathematical tools for modelling highly complex, nonlinear systems, making it possible to rigorously analyse everything from the flow of water around a boulder, to climate change. Altering one element can have surprising and dramatic effects on entire enmeshed systems, just like the tiny pebble on your windscreen.

Behavioural economics demonstrated just how irrational we are in our behaviour and changed economic thinking, so must 'everyday chaos' thinking change our understanding of strategy and our business decisions.

We need to lose our naive confidence that we can understand how things happen, or that we can we can make things happen by pulling the right levers. It is far more complex than that, as this fascinating book explains.

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