Creating Early Warnings Scenarios & Thinking About the Future


In her speech and conversation with Stuart Crainer, Rita McGrath talks about how strategic inflection points can take your business to new heights if you get it right and if you miss them, they can cause your business to go into decline.

The first point of departure is thinking about what is a strategic inflection point and what does it do for our business. An inflection point is a reflection of pressures which grows on the existing business model over time. As one goes through an inflection point, some things that used to be possible no longer are and things that were never possible are then possible. 

A strategic inflection point can then be defined as an event or series of events that cause the assumptions underlying an existing business to no longer reflect reality. If you get them right, they can take your business to new heights and if you miss them, they can cause your business to go into decline. Contrary to popular belief, the history of most strategic inflection points shows that they have been building up for some time. They were anticipated to some extent and there were warning signs long before people started paying attention to them. In the context of this current pandemic, Bill Gates famously said in 2015 that we should be preparing for a pandemic, and apparently in the George W. Bush administration this was a huge issue that he felt that the states needed to be much more prepared than we were, and to the extent that there has been some coordinated response. But of course, there has been a big gap between what they suggested and what the response has been so far.

Developing early warnings

When we think about early warnings, the first principle to think is looking at the data we use to process an early warning. Much of the data that we have access to is lagging. It’s great information but the information is about something that has already happened. More valuable in terms of strategy is looking at current indicators, such as employee engagement score, net promoter score, etc. that tell you where you are right now. The hardest indicators to act on are the leading indicators. Leading indicators are difficult because they are often stories for starters, so reasonable people can disagree about what they tell. The second problem is that the metric for a good leading indicator is not necessarily whether it was predictive of what was to happen but whether it caused us to take action in time.

However, after taking the lead indicator seriously and making the investment in resilience to prepare for something, it may be the case that nothing happens. One very pragmatic thing we can take away from this is that there is a pretty sizable amount of information we have on how you create resilient systems but it is a different way of preparing than when you prepare optimised or very efficient systems. Resilient systems have redundancy, so if one part of the system stops functioning, other parts of the system can pick up the slack. Resilient systems have excess talent, so if you look at high-performance workforces, for example, you will find that people have been trained to do multiple tasks and we are seeing the dangers of not doing this right now in our healthcare systems. Healthcare workers are currently being laid off because the work they have specialised in is not coming in use right now, so they are suffering because their knowledge is so specialised they are not in a position to help in this pandemic. This is one example of how not having people with a broad knowledge base can make the system less resilient.

Finally, resilience systems have slack resources because the reality of an event like this pandemic is you don’t know where and when but you do know that it is not a question of ‘whether’. So, experts would tell you to stockpile resources early, you want more than you need and you want that to be built up right now. An example of this right now is Bill Gates telling people that we need to develop nine different vaccines right now for tackling this virus and if even one of them succeeds, we will have wasted the resources used to build the other eight. But thinking about it from a system’s level, getting even one solution after nine or ten failed attempts is more than worth what we put into it. It’s a classic example of options reasoning or options thinking. That is how we need to be thinking when we think of resilient systems.

The Early Warnings model

The early warnings model wrestles with a fundamental challenge that we are all dealing with. The strength of the signal or the quality of the information that we have to work with gets stronger and stronger until you get to the moment of truth or the time zero event when the anticipated things finally happen. But the problem is that our degrees of strategic freedom, our ability to do something about what our signals were telling us is inversely related to the quality of the information we have to work with. As strategists, a constant issue faced is that by the time one has the information that is needed, the data have moved on.

Hence, in a crisis like this, the first thing we need to be thinking is how can we learn as quickly as possible and create hypotheses and learning experiments to help us identify as quickly as we can what might be happening. So, at the ‘time zero event’, we need to be thinking about what the next challenge can be. It can be done by taking two uncertainties, assign different values to each one, and create a 2×2 matrix, which will give you four quite distinct possibilities that you could start preparing for. The goal here is not to forecast but to chart out four viable potential futures and see how your strategies map out against those. 

As an example, we can take the scourge of the United States’ financial system, which is now revealing how brittle our economy is, which is based on the ideology of maximizing shareholder value and prosperities are not being spread widely. This may be the moment where people push for shared prosperity and a greater role for the government by recognizing that capitalism left to its own devices is not going to solve some of these greater good tragedies of the commons, or it may not change anybody’s minds and we go back to the way we were before. The other uncertainty relates to whether the economy would bounce back or not.

These two uncertainties give us the opportunity to tell a different story about what each of those areas looks like. If there is a prolonged global slowdown and our values remain that shareholders matter more than anybody, it is going to be a likely unstable future situation to have, that is, profound economic insecurity for the majority, which is going to lead to economic instability and conflict over resources. In the second scenario, if the economy bounces back and our values remain fixated on maximising shareholder value, it is a rinse and repeat of the last 40 years. We are still going to have inequality, we won’t have dealt with some of these societal issues, but that is a familiar place and we know how to operate there.

if our values shift to stakeholder capitalism alongside prolonged global slowdown, it would give us grass-roots protests, an extension of safety net programs, higher tax rates on the wealthy, and even wealth appropriation. No society has ever sustained these levels of income inequality for the long term, so we had better be ready for it. Nick Hanauer, famous for his work pitchfork economics says that money is sitting in offshore accounts, in people’s banks, and in investments, so it is not inconceivable that a populace would not get the money they think have been ill-gotten. In that framework, we are also going to see far more credence and credibility in governmental players. We are going to be looking to some source that is not an economically motivated market and that is not just doing things for the sake of doing things. We are going to be recognizing that governments have a role to play and that well-governed societies do better than societies that are not well-governed. 

Lastly, if we have stakeholder capitalism, all those social changes happen coupled with the economy bouncing back, then we have the potential for a return to a post-war consensus, the distribution of societal wealth, and the gradual narrowing of inequality. We could even have a moment to make social goods like healthcare, education, infrastructure, and such other things we all benefit from. The goal here is not to forecast but to chart out four viable potential futures and see how your strategies map out against those. 

The next step after this is to create headlines, which sums up that world in a quick and efficient way. In the given example, for the first scenario, the headline would be “Why economic equality leads to collapse”. If we have a rinse-and-repeat model, the headline would be “Extreme poverty returns to America”. We will have not just inequality but extreme poverty, and that was the condition that the New Deal and then the Great Society programs were put in place to address. 

If we have stakeholder capitalism and prolonged global slowdown, we will go right back to the great depression and take inspiration from something like Franklin D Roosevelt’s “Rendezvous with Destiny” in which he said that we are going to combat economic tyranny, and by that he meant the privately held means of production and wealth creation. A lot of the New Deal programs were hated by the wealthier classes, but we could see a return to that kind of premise and that kind of experimentation. If there is stakeholder capitalism and the economy bounces back, we could start to see the “Great Society 2.0” where we would start to say there is more to the economy than just markets; there are other stakeholders to be taken into account, and we need to be thinking about how we meet their needs as well.

Next, we need to position each of these events as a ‘time zero event’ and start a pattern recognition, start collecting data that would tell you, us or the other was likely to become more realistic. By way of this, we are trying to move the decision-making framework back in time, so somewhere close to where the degrees of freedom line and signal strength line cross is where we need to be making strategic choices. Making the choices earlier than that is not advisable as at that point one would not know what is real and what is not and making them later than that, you would be unable to take the actions you want to.

Contrary to popular belief, the history of most strategic inflection points shows that they have been building up for some time. They were anticipated to some extent and there were warning signs long before people started paying attention to them.

Strategy + Innovation + Digital

Strategy, innovation, and digital were three separate worlds that have come together now. Innovation used to be a niche thing but today, it has become central to strategy. You cannot think about strategy without thinking about how you consider innovation, and you cannot think about innovation without it fitting into your strategy. In the last 15 years, a layer of ‘digital’ has come up on that, touching everything. Initially, digital was part of marketing as the way we were introduced to it is through digitized books, music, and eventually movies. Today, we are right on the brink of seeing digital entering mainstream by getting into business models, so things are becoming possible that could never be possible and radically changing the way we deliver goods and services, and so on.

Concluding thoughts

  • Inflection points feel that they happen overnight but going back in time will always show you that early warnings were building up over long periods.
  • Being successful in a particular technological regime will almost always create blind spots.
  • Unfortunately, most of us are basing our strategic decision on lagging indicators, so we should get out beyond what we can see right in front of us and think about what the future might hold.
  • The better your information, the harder it is to change it.
  • It is not about prediction but preparedness.
  • We need systems to identify early warnings, and the more systematic we are about it the more quickly we will be able to recognize patterns, and the faster we will be able to take action.

Stuart Crainer in Conversation with Rita McGrath

Stuart Crainer: Is the “great society 2.0” some sort of combination of being digitally enabled and vaguely communist?

Rita McGrath: The great society 1.0 was an initiative under the presidency of Lyndon Johnson in the United States, and he professed that the US was wealthy enough to be able to eradicate the worst consequences of poverty. That’s what a great society should be able to do. A lot of what they tried didn’t work and some of the things they tried did work, so things like the Head Start program in education was widely regarded as having massively improved opportunity for many underprivileged youths. It centred around the idea of having a safety net, pathways to work, the dignity of life, and so forth.

We are not going to get back to that idealistic great society, but we are starting to see strong evidence that people are saying the system is rigged. We have workers striking at companies like Amazon and Instacart because they see themselves being wrongly put in harm’s way and not being appropriately led. All this churn that we are in right now may cause people to reflect on that and the ability of the government to play an important role in creating a better society, That is what I meant by the great society 2.0.

Crainer: We all know Germany is a well-governed country, but it seems one of the issues is our inability to learn from best practice, which seems to be particularly acute at the governmental level.

McGrath: I agree. The politicization of everything has become a cancer, certainly in our society and in various countries over the world. We are at a point where we can’t agree on anything whatsoever. We need politicians who can forge more common beliefs. I mean, none of us believe children should be starving, none of us believe that people who have worked their whole lives, have saved, and have been diligent about it should be looking to be wiped out by a catastrophe that is beyond their control. So, let’s find some common ground, some building blocks that we can use as a platform and start to reimagine things. 

One of the wonderful, if horrible, aspects of this is that a crisis like this forces our hand, and it has forced our hand on the environment and on social safety nets, and it is like a great unfreezing. Things that we would have never decided to do if it was up to us to choose are now on the table. We can begin to lead in the sense of what do we want the rules to be, what do we want our society to look like, and things are now possible that were never possible six months ago.

Much of the data that we have access to is lagging. It’s great information but the information is about something that has already happened.

Crainer: If data is lagging, does it mean that judgement, the old-fashioned managerial and leadership judgement is more important, and that we have been blindsided and seduced by big data? 

McGrath: It always has been. People always say that they make data-driven decisions, but a lot of times, they don’t. They are operating on gut or instinct, so the first thing to recognize is that we don’t make a lot of data-driven decisions in companies, in general. The mind of the strategist has always been about pattern recognition, seeing a weak signal before it is fact, and picking up on the indicators that we should be paying attention to today that would lead us to a more fruitful future down the road. Those are the kind of questions that data cannot answer yet because different people think differently. 

Hence, those four scenarios I went through earlier are right now perfectly plausible, and which one we end up in would be a function of our decisions, how we collectively chose, and what our goal is, as a society. We are at a really interesting moment where we get to pick which of the futures we want to end up in.

Crainer: What needs to be done in education? There are two sides to that- to prepare for an inflection point and to know what to do to educate people about what they are and how to respond.

McGrath: To the question of how we teach people about this, I think that is where I hope we have a return to faith in science and expertise. A lot of it is building that muscle, getting accustomed to asking what could this mean, what are the key warnings, and so on. Secondly, what does this mean for education? All of us are embarked on a massive social experiment, wherein university campuses may not open up even in the fall, and we will be seeing how education is administered. 

We are going to start to see credentialing, which is separate from the granting of a degree, as one of the trends. So, as we are all now operating digitally, I can hire people based on the knowledge about what they can do and what they accomplished, and have them get more things done than I ever used to be able to. Hence, a degree, in many cases, was a very poor proxy for other things that I care about. If I can get to the level of the skill and not the degree, I have now got a workforce that can have access to far more opportunities because now there is not the barrier of three-four years of university degree between them and opportunity. 

The way we deliver education is surely going to change radically because we have got professors on-screen now all over the world, even those who didn’t want to do it. It is not as good as the in-person connection, but for a lot of youth, it is better than nothing. We will start to see how giving education in a much more distributed way turns out to be. Finally, a lot of our educational infrastructure is going to come under depression. At least in the US, the rate of the cost inflation in education has far outstripped general inflation in the GDP, and that is not sustainable. So, we are going to start to see innovators coming into the education sector. There is going to be a lot more experimentation with that.

Crainer: Your work on inflection points has echoes of Kuhn’s notion of paradigm shifts or scenario planning, which are ideas from the past. What are those echoes and how has inflection points related to those ideas?

McGrath: My Ph.D. is in social system science and that was a branch of management that started in WWII as a formal body of study, and they were interested in the behaviour of complex systems. What we are going to be drawing from the past is an insight into how you deal with complex systems. Complicated systems like a Boeing 747 is a very complicated machine, but we know what it is going to do in the face of certain instructions, so it’s complicated but it’s predictable. 

Complex systems influence each other because they are inter-dependent, and it can’t be predicted what is going to happen by knowing what the initial conditions are. Hence, a lot of the principles of systems thinking are things like ‘equifinality’, wherein you have an end and a destination, but you could get there through multiple plans. It almost does not matter what choice you make because the destination does not change. Ideas like reducing a system to its component parts to understand it and my remarks on systems resilience all come from systems theory.

Crainer: Our appetite for simplicity is in organization and leadership thinking, so we seem to be naturally uncomfortable with the notion of complexity and uncertainty. To some extent, doesn’t your idea fight against human nature?  

McGrath: Absolutely. My work historically has been in that place where there is a lot of uncertainty, and a lot of assumptions have to be made relative to the knowledge one has. Learning is very important because there is no data or information. One of the things that a crisis like this does is that it shoves all the things that we used to think of as the core business or the stable part of the company into this high uncertainty space, and there are a lot of people who are desperately uncomfortable with that. Those people should try to think about what they could learn next and try to put together an inexpensive simple way to learn something next. 

For example, if your business depends on human beings sitting in some physical facility, what could you learn about how that behaviour would change once the restrictions are eased up again? You could begin to do some experimentation around that, and maybe it changes your business model. One has to avoid trying to grasp the whole hairball because it is beyond our cognitive ability, and instead hone in on what are some things we could test so that the whole becomes clearer.

Crainer: Kodak had very good people, well-meaning people, and very smart people and you can say that in organizations after all and in governments of the world, in general, there is a lot of good, smart people who are missing these inflection points. 

McGrath: In the case of Kodak, they didn’t miss it. They saw it coming but didn’t like the message. After all, they invented the digital camera. The contrasting case to Kodak is Fuji, and Fujifilm looked at digital coming and decided to change their strategy to survive. 

They started by looking at their capabilities. They learned that their tools developed to handle coloured film processing were very relevant in the medical area, so they leveraged that capability in the medical field. It wasn’t a huge overnight pivot but gradually they moved their capabilities into these new areas, and today they are a thriving company, and Kodak is on life support.

Crainer: How do you fight data biases within an organization when you are trying to use leading indicators? 

McGrath: You need to have processes in place which make challenging the biases acceptable. One of the reasons that we use so much biased data is first, confirmation bias which means we make up our minds about something and then we go out and find data that supports our already established point of view. Hence, organizations need to make somebody’s job to go out and look for data or information that could disconfirm those established beliefs. This is a structural issue because we all know we have this bias, and someone can find counterfactual information that could discredit those biased assumptions. 

The second thing to do is to get people out of that groupthink mode. As human beings, if we are in a group of, say eight people, and everybody thinks green is a great idea, we all go around frantically agreeing with each other. You can take two or three people from the group and ask them, “how would we undermine green if we were an opponent or competitor?”. It permits those people to think differently. 

A third exercise to do is called The Brand Takeover exercise. This is an exercise in imagining that your company has suddenly been taken over by a bigger brand. The next step is to ask yourself, “What are the things we are working on now that the company would decide to stop doing and what are we not working on that the company could ask us to start to do? What decisions would we make if they increased or decreased our marketing budget by 10 times?”. The idea of being owned by a different corporate brand frees up many degrees of freedom and helps people think and act differently.

Crainer: We seem to be leading to the uncomfortable tension between simplistic efficiency driven by algorithms and binary solutions driven by math against a dynamic ecosystem organism that is fit for purpose, driven by humans. It seems that the simplistic efficiency side has been winning for the last century.

McGrath: I agree. One of the things that have been concerning is the rise of digital serfdom of sorts. We are going back to a piecework system, which was regarded as a horrible anachronism of the 18th century, and we have returned to that, just in digital form. Part of the dilemma is that it is extremely hard to grasp measures of the system by only looking at a piece of the system, and that is one of the things that came out of social system sciences, which is that you could have each little piece of it optimised within an inch of its life but if you let a systemic issue happen, all those things dissipate. 

We can see this today with the global supply chain. America basically allowed its organizations to greatly outsource the manufacture of simple things like hospital masks, and nobody bothered to ask what would we do if we have a global pandemic, and those countries suddenly decide they do not want to export those particular products. We didn’t give a lot of thought about asking those questions.

Crainer: There are a lot of business thinkers who are spreading their net beyond business and drawing examples from the political world. Your work is part of that, I think.

McGrath: Part of it, yes, because for capitalism to function, there need to be rules of the road. You can’t have a capitalistic system without property rights, without the guaranteed ability to benefit from the fruit of your labours, without a common point of view about what resources are there to be protected, because they are common goods versus what resources can be exploited by individuals for their benefit. The rules of the road are unfortunately in a variable political process so those of us who are looking in that direction are saying that a capitalistic system needs to have a certain level of governance for it to function. Ungoverned capitalism is economic terrorism. 

Crainer: What are the qualities of a leader in society 2.0? 

McGrath: An analogy that can clarify it comes from Bjarte Bogsnes, the chair of the Beyond Budgeting Round Table. He says we think about leadership like a stoplight, a mechanism for regulating traffic. A stoplight has been pre-programmed by someone, it is dumb and doesn’t know what is going on. It behaves the same whether it is three in the morning or whether it is rush hour. It is programmed by rules, and in many ways, our traditional perspective on what a leader does is that, which is, setting up rules. 

Instead, Bjarte says to think about a traffic circle. In a traffic circle, especially one which does not have a lot of indications of what you are supposed to do, the drivers slow down immediately. All of the cars, cycles, and pedestrians have to interact with each other, have to bring their conscious selves to work, there is no presumption they have the right to go, and so they have to negotiate through the traffic circle. Research shows that when stoplights are replaced with intersections that signal where the pavement is and so forth but require that drivers navigate it on their own, there are fewer accidents and drivers are more responsive to what is going on in the moment.

Similarly, leaders need to set up proper parameters, have a plan, have the ability, but also have to be able to create within their organization lots and lots of traffic signals where people can see what is going on, and they have the freedom to make decisions in that moment. That’s the kind of leadership we’re going to be looking for at a systems level because one of the principles of systems is that you cannot break it down to understand how it works; you have to let it organically be moved in certain directions.

Crainer: You are optimistic that these lessons would be learned?

McGrath: Every generation seems to have to learn them over again. The generation that lived through the tail end of the great depression, World War II, and the subsequent building up, are horrified at the decisions that were made. A lot of those things have been disassembled, and now we are coming back to those bad ideas. When you have been prosperous for a while, we move one regulation or make small changes here and there, and it doesn’t seem like anything at the time, but these things are cumulative and path-dependent. So, the idea that you could buy a 2% share of a publicly-traded company and promptly dominate the agenda of its management, demand board seats, demand change in business strategies, and in many cases, for the short term, is legal but makes you question if it should be. I think it is the cumulative effect of these things that get to be problematic.

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