What will happen
On 30 May 2014, under the headline ‘An astonishing record – of complete failure’, the Financial Times opined: “In a  report . . . there were 77 countries under consideration, and 49 of them were in recession in 2009 [as the world slipped into the depths of the global financial crisis]. Economists – as reflected in the averages published [in that report] – had not called a single one of these recessions by April 2008.”
This is extraordinary . . . the crisis was firmly established when these forecasts were made. The Financial Times had been writing exhaustively about the ‘credit crunch’ . . . Northern Rock had been nationalised . . . Bear Stearns had collapsed . . . Predictions from multinational organisations such as the IMF and the Organisation for Economic Co-operation and Development have [been] . . . similarly bad . . .
The newspaper continued that, “We should not blame economics alone for our inability to peer into the future of a complex world” and drawing from the bestselling political author Philip Tetlock’s book Expert Political Judgement, said that “[he] found that throughout the 1980s and 1990s, political and geopolitical forecasts had been scarcely better than guesswork. It made little difference whether the forecaster was an academic, journalist or diplomat, a historian or a political scientist. Forecasting is difficult, it turns out.”
Consider that, on 16 November 1929, the Harvard Economic Society held that ‘[a] severe depression like that of 1920–1921 is outside the range of probability’ – and the Great Depression ensued and lasted through much of the 1930s. As Assistant Secretary of the Navy, Franklin D Roosevelt in 1921 told the Kiwanis Club of New York that ‘It is highly unlikely that an airplane, or fleet of them, could ever successfully sink a fleet of Navy vessels under battle conditions.’ Twenty years later, on 4 December 1941, his eventual successor, Frank Knox, said, ‘No matter what happens, the US Navy is not going to be caught napping.’ The attack on Pearl Harbour came three days later.
Business Week got it wrong in 1968 when it wrote, ‘With over fifty foreign cars already on sale here, the Japanese auto industry isn’t likely to carve out a big slice of the US market for itself.’ And 20th Century Fox got it very badly wrong in 1946 when it predicted that, ‘Television won’t be able to hold on to any market it captures after the first six months. People will soon get tired of staring at a plywood box every night.’
Add to that nearly every subsequent major global shift, from the end of the Cold War to the 9/11 attacks, the Arab Spring, the 2009 global financial crisis, and Donald Trump succeeding Barack Obama in the White House, and you might ask whether we are kidding ourselves that we can get the long prediction about South Africa right.
Three years ago, the answer to that question became the subject of a course we designed and now teach to the MBA class at a South African university. Built on our own experience in advising firms on South Africa’s future and our exposure to Clem Sunter and his work on the High Road – Low Road scenarios, the course teaches young executives how to anticipate events in volatile emerging markets.
A feature of that course is to understand the theoretical basis of change – in other words, why does change happen? The answer is found in complex systems theory, which is the theory of systems made up of vast numbers of actors that compete with one another in pursuit of their varied interests. Such systems have what is called the ‘emergent property’, which dictates that small changes in their initial circumstances will bring about exponential shifts in their future circumstances – or what has been popularised as the ‘butterfly effect’. A consequence of that property is that traditional, single-point forecasting (getting an analyst accurately to identify a single future point in time and space) becomes little better than guesswork when applied to very complex environments such as countries and economies. The course steers students away from such traditional forecasting approaches, and teaches them how to apply different futures methodologies that account for the emergent property of complex systems.
We are not going to go into the deeper methodology in this book, other than to say that we teach students how to identify the trends that will have the greatest influence on the decisions they need to take and how to plot these against the trends that are most uncertain – to form a matrix with four quadrants. As an example, if you were to apply that approach to the future of the mining industry in South Africa today you might plot geology, as the trend of greatest influence, against the trend of mining policy, as that of greatest uncertainty. The result would be a matrix with four quadrants.
- The top-right quadrant would suggest a future of generous geology matched with enabling mining policy.
- The bottom-right quadrant would suggest a future of generous geology matched with hostile mining policy.
- The bottom-left quadrant would suggest a future of hostile geology matched with hostile mining policy.
- The top-left quadrant would suggest a future of hostile geology matched with enabling mining policy.
Each of these would be a plausible future mining environment, and a mining house commissioning such scenarios could then develop all manner of dashboards and markers to hedge itself against downsides and exploit upsides – in the process, revealing the future for which it should be adopting strategy. Through rejecting the certainty promised by a traditional single-point forecast and instead becoming aware of alternative futures, the mining house will be hedged against unanticipated changes in the environment in which it operates (the inescapable consequence of emergence). Should it then go further and develop proto-strategies for each alternative future, while implementing the strategy that aligns most closely with the strategic environment it is in, that mining house will be positioned to turn on a dime and implement a new strategy in real time when the strategic environment changes – thereby allowing it to turn uncertainty from a strategic risk into a strategic asset. Its competitors – caught off-guard by the changed environment – will need to figure out first what just happened, and then what they should do about it, a process that would take months. The key to it all is not to try to overcome key uncertainties, but to identify and embrace them as units of analysis.
Once they have been sketched, scenarios must pass three tests. The first is that there can be no fifth scenario. If your initial socioeconomic and policy analysis was very thorough, your matrix will contain all plausible future outcomes. The second is that each scenario you describe must be plausible. Could the circumstances you are describing come to pass? Is there precedent for them? The third is that each scenario must be sufficiently distinct from the others to make a significant difference for decision-makers. The mining scenarios above pass all three tests very well.
When applying this methodology within our own team with a view to understanding the likely future trajectory of South Africa, the trend, or driving force, with greatest influence on that future will be the national psyche of the country. At its one extreme, that psyche may come to reflect all the characteristics of the chosen glory psychology that was set out in the opening chapter of this book. Alternatively, that psyche may evolve to become a chosen trauma case study.
The greatest uncertainty facing South Africa, in our estimation, will be the ideological evolution of policy. Will a future government embrace liberal structural reforms or rather persist in executing NDR ideology?