Chapter 1. Forget Strategic Plans!

In autumn 2020 I had a meeting with executives from a leading retailer. While waiting for them to arrive I studied their strategy which was, unusually, printed on three large sheets of paper and pinned to one of the walls of their conference room. Here laid out was the company’s vision, mission, values, key performance indicators (KPIs) for their various business lines and a GANTT chart detailing actions and deadlines for all agreed projects. It was a big piece of work and had clearly taken a lot of time and (judging by the logo of the management consulting firm embossed on the paper) a lot of money to create. The retail executives arrived and sat down. As an ice-breaker I pointed to their strategy on the wall behind them. None of them looked round:

Me: I was admiring your strategy

Executives: Mm [one of them mumbled]

Me: It’s very detailed

Executives: Yes, it is

Me: [unable to contain my mischievous side] Where’s COVID on there?

Executives: [after a slight delay] That was done before COVID

Me: Did the plan help much?

Executives: [after another slight delay] Not really

Me: Are [X] doing your strategy again next year?

Executives: No. I think we might need something different.

I couldn’t agree more!

This book is about finding a different way to cross the river.

The World Uncertainty Index[⁠1] suggests that felt uncertainty — a feeling that we don’t know what will happen next — is increasing (see fig. 3). People point to political turbulence, financial crashes, wars and natural disasters to explain this uncertainty but even a cursory glance at the history books reveals that such events are nothing new. So something else must be driving this rising level of felt uncertainty. Could it be that in the modern Age of Information and Telecommunications, (starting around 1971 when the Intel microprocessor was announced) we have more information, or ‘signals’ we can use to help us make sense of what’s happening around us — but that these signals are also accompanied by more ‘noise’ (interference) that means the information we have is:

Unreliable — because the credibility of the source is perceived as low

Ambiguous — because there’s more than one way to interpret information

Complex — because different pieces of information are difficult to integrate

Missing — because information has not been received or can’t be located when needed.

Does the greater amount of information we produce lead to greater uncertainty?

Fig. 3: World Uncertainty Index (WUI) 1990–2021

The World Uncertainty Index (WUI) is computed by counting the percent of word “uncertain” (or its variant) in the Economist Intelligence Unit country reports. The WUI is then rescaled by multiplying by 1,000,000. A higher number means higher uncertainty and vice versa. For example, an index of 200 corresponds to the word uncertainty accounting for 0.02 percent of all words, which — given the EIU reports are on average about 10,000 words long — means about 2 words per report.

Humans have an acute aversion to uncertainty. Researchers at University College London asked volunteers to play a computer game. They had to turn over rocks that might have snakes underneath and if there was a snake they’d receive “a mildly painful electric shock on the hand”⁠[2]. The volunteers quickly worked out which rocks were more likely to harbour snakes so the researchers changed the game’s parameters to make it harder to predict. The surprising insight from this research was that the fluctuating levels of uncertainty were causing the volunteers more stress than shocks were: Those with a 50 percent chance of receiving/avoiding an electric shock were more stressed than those who knew, 100 percent, they were going to receive a shock. The researchers concluded that it’s “much worse not knowing you are going to get a shock than knowing you definitely will”.

This acute human aversion to uncertainty explains why we’re often so susceptible to those peddling certainties: Economists who confidently predict how the economy will fare in the future, or management consultants who confidently assure us that taking steps A, B and C will lead to compound annual growth rates of X% for your organisation⁠[3]. The current obsession with getting ever bigger datasets for these predictions, combined with the shiny lure of artificial intelligence (AI) — despite the obvious flaws of using past data to predict uncertain futures⁠[4] — suggests that before we arrive at the oasis of a true artificial intelligence that can remove uncertainty from our world we will have to cross a wide desert of artificial stupidity first.

Seeking certainty about the future drives the annual planning cycle in many organisations today. The promise is that, by performing a clearly-defined series of steps correctly — inputting and analysing key data, determining strengths and weaknesses, brainstorming initiatives — a reliable strategic plan for the organisation will emerge. This then needs only to be rolled out to those responsible for executing it — with their outputs measured against key performance indicators (KPIs) — for the plan to be realised. This ‘assembly line’ approach — where known inputs produce knowable outputs — worked well enough for organisations in the fourth industrial age [5] (the Age of Oil, the Automobile and Mass Production, starting in 1908) where the key assets were predictable machines. But in the modern Age of Information and Telecommunications, where the key asset is (uncertain) information, the organisation’s ability to produce predictable outcomes is diminished. Combined with the increased volatility of the modern business environment — due to seemingly accelerated rates of technological change and increased numbers of competitors playing the game globally — planning has become a sub-optimal way to run an organisation. Yet ‘strategic’ planning not only remains the dominant way of “managing the organisation’s future but [for many] the only conceivable one”[⁠6]. Simply put, the practice of strategy has not kept up with the changing times.

Strategy is about making choices from available options about what to do next. But, in many organisations, strategy has become more of an annual dance designed to reduce the stress and anxiety that uncertainty causes leaders. Rolling plans out to ‘doers’ to implement them also serves to reduce their stress, by giving them the illusion that someone (i.e. ‘thinkers’ who created the strategy) is in control. This ritual dance — where the ‘thinkers’ are often outsiders and the ‘doers’ focus on hitting targets to unlock bonuses, rather than responding to the changing needs of customers — has created a situation where most people can’t even name their organisation’s top three strategic priorities[⁠7] — and this also goes for many in the top team who are supposed to be responsible for the strategy (see fig. 4). Instead of guiding the organisation through choppy and uncharted waters strategy has become a mechanism for providing people a comforting sense of certainty in an uncertain world, even if it that certainty is an illusion (but remember, ‘uncertainty causes more stress than pain’ so the intent behind ‘strategic’ planning is to reduce the stress of uncertainty rather than mitigating probable pain from any actual shocks that will happen).

Fig. 4: No-one Knows Your Strategy

One of the main weaknesses of ‘strategic’ plans is that, once rolled out, they’re dependant on the wider situation not changing significantly for the period of the plan. But, as the 2020s have already shown us, no amount of planning — irregardless of how elaborate the process is, or the size of the datasets being used — will ever be able to forecast sharp discontinuities; where the situation changes suddenly and dramatically. Furthermore, the segmentation of people into ‘thinkers’ (who make the plan) and ‘doers’ (who execute it) creates other, critical problems. ‘Thinkers’ (especially those who rely on outside consultants) can become detached from the realities on the frontline and end up setting aspirational (and often unrealistic) targets for the ‘doers’ to achieve. The plan then becomes wishful thinking and any contrary ideas — such as those formed in response to the unfolding situation on the frontline — are seen as unnecessary disruptions to the plan and rejected.

Relying on ‘strategic plans’ undermines an organisation’s ability to respond quickly and innovatively to change as ‘sticking to the plan’ becomes the priority (in order to retain the illusion of control). This is like playing chess by planning all your moves in advance and executing them one by one without paying any attention to how the situation on the board is changing. This explains why, for some executives, the ‘strategic’ planning cycle — with its “hundreds of pages of analysis” and “flowery prose that supplements the numbers in the budget” — has become “a colossal bureaucratic waste of time”[⁠8]. Their response has been to place an ever-greater focus on execution instead. But, as the example below shows, this reliance on execution alone also has severe short-comings:

“When Hewlett-Packard, announced disappointing results in August 2004, CEO Carly Fiorina stated, “The strategy is the right one. What we failed to do is execute the strategy.” Her explanation sounded reasonable, and no one questioned her when she swiftly replaced a few key executives — it looked like an appropriate step to improve execution and raise company performance. Curiously, when Fiorina herself was fired just six months later in February 2005, a company spokesperson repeated the same line: HP was following the right strategy, but the chief executive was replaced because the board of directors wanted better execution! Again, it all sounded reasonable, and no alarms were raised about the company’s basic choices. Six weeks later, when Mark Hurd was hired as the new CEO, Hewlett-Packard stuck to its message, announcing that it had “picked Mr. Hurd because of his execution skills.” And therein lies the problem: It’s always easier to bang the drum about execution than to address fundamental questions of strategy. It’s always easier to insist we’re going in the right direction but just need to run a little faster; it’s far more painful to admit that the direction may be flawed, “because the remedies are much more consequential”[⁠9].

These ‘consequential’ remedies are a complete rethink of our approach to strategy, because better planning — even with more data, AI and smarter gurus — doesn’t address the main problem: The future remains an uncertain place. Some strategy ‘gurus’ have responded to this by shortening the time horizon for planning — from five-year plans to the annual plan today — in the hope of reducing the window of opportunity for ‘black elephants’ (high-impact/high-probability events: a combination of ‘black swans⁠’[10] and ‘elephants in the room’⁠[11]) to stomp in and mess everything up. While other ‘gurus’ have simply advocated for better execution. But executing plans faster won’t help if you’re aiming in the wrong direction — it’s merely going to take you further away from where you need to be.

The ‘discontinues’ of the 2020s have proven that even annual planning is a timeframe too wide to be certain about, while the sharp discontinuities we face require more than just winging it and hoping for the best. A different approach is now needed, one that encourages insight and flexibility, “the very things that formalisation discourages⁠[12]”. In a volatile and uncertain world we need to move away from formal processes that produce top-heavy plans that don’t survive contact with reality and instead learn how to make make better moves not in spite of the uncertainty, but because of it. For here is the key insight: You don’t have to predict the future to be able to thrive — you just have to be able to respond better than your rivals when a changing situation demands it.

1 https://worlduncertaintyindex.com

2 “Computations of uncertainty mediate acute stress responses in humans”. Nature Communications. March 29, 2016. Discussed in ScienceDaily

https://www.sciencedaily.com/releases/2016/03/160329101037.htm

3 Even perhaps the most famous management consultants of them all — McKinsey — have a checkered track record in this area: from being known as “the firm that built Enron” by advocating side pockets and off balance sheet accounting https://www.theguardian.com/business/2002/mar/24/enron.theobserver to advising AT&T there wasn’t much future to mobile phones https://www.washingtonpost.com/wp-dyn/content/article/2008/02/22/AR2008022202283.html from putting out a report that cloud computing was just an expensive niche service https://www.informationweek.com/cloud/clearing-the-air-on-mckinsey-s-cloud-report to facing criminal charges for its role in bankruptcy cases, where it used its position to redirect assets to itself or its clients https://www.nytimes.com/2019/11/08/business/mckinsey-criminal-investigation-bankruptcy.html and from its role in the US opioid crisis it helped create https://www.nytimes.com/2020/11/27/business/mckinsey-purdue-oxycontin-opioids.html to its much criticised role in the roll out of Covid vaccines in France https://www.nytimes.com/2021/02/22/business/france-mckinsey-consultants-covid-vaccine.html

4 Before the 2018 football world cup the Swiss investment bank, UBS, ran 10,000 simulations and predicted that Germany to win the world cup https://www.bloomberg.com/news/articles/2018-05-17/germany-will-win-the-world-cup-ubs-says-after-10-000-simulations

Then the US investment Goldman Sachs used AI to run 1 million simulations and predicted that Brazil would win the world cup in 2018: https://nordic.businessinsider.com/world-cup-predictions-pick-to-win-it-all-goldman-sachs-ai-model-2018-6?r=US&IR=T

Neither Germany nor Brazil even made it to the semi-finals, so Goldman Sachs re-ran its simulations with the four teams remaining and predicted Belgium. Despite having a 1 in 4 chance Belgium failed to make it to the final, which was won by France who beat Croatia: https://www.businessinsider.com/world-cup-predictions-goldman-sachs-ai-model-belgium-england-final?op=1

For a summary of this see: ubs-commerzbank-predict-germany-would-win-world-cup-wrong

5 The first was the Industrial Revolution (started 1771), the second was the Age of Steam and Railways (1829), the third was the Age of Steel, Electricity and Heavy Engineering (1875), the fourth was the Age of Oil, the Automobile and Mass Production (1908) and the fifth, the Age of Information and Telecommunications started around 1971 when the Intel microprocessor was announced in Santa Clara, California.

source: Technological Revolutions and Financial Capital. The Dynamics of Bubbles and Golden Ages. Carlota Perez (p.11)

6 Rise and Fall of Strategic Planning — Henry Mintzberg (1994) p.60

7 https://sloanreview.mit.edu/article/no-one-knows-your-strategy-not-even-your-top-leaders/

8 https://medium.com/the-innovation/strategy-as-problem-solving-5c6fb9291d87

9 Rosenzweig, Phil. “The Halo Effect”. p315

10 https://www.investopedia.com/terms/b/blackswan.asp

11 https://en.wikipedia.org/wiki/Elephant_in_the_room

12 Rise and Fall of Strategic Planning — Henry Mintzberg (1994) p.477

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