Learning from scenario thinking – what can go wrong?
An insightful short book from Peter Schwartz, author of the seminal book “The Long View”, was given to me by Napier Collyns, a co-founder of Global Business Network (now part of Monitor). It is called “Learnings from the Long View”, and as well as presenting three scenarios for 2025, it discusses three successful case studies and four “bad calls”. When I teach scenario thinking it is always the “lessons learned” that are most valued, so here is a summary of the reasons behind each of four “bad calls” that he describes.
• Anticipating the start of war: the day of the invasion of Kuwait, this scenario was not being considered – why? Because the mental model based on the history of the oil industry was not challenged. Lesson – experience can mislead.
• Anticipating the Mexican peso crisis of 1994: of eight scenarios developed two weeks before the crash, none included it – why? The group of people who created the scenarios were not diverse enough, and none pointed out that a new president was often accompanied by a devaluation of the peso. Lesson – ask about history.
• After a scenario workshop on the future of mining, many of the team who took part were fired by the CEO – why? The scenarios work had been at the instigation of the Board and the CEO used it to find people who were not “100%” aligned to his Official Future. Lesson – scenarios are about people as much as intellectual challenge.
• Anticipating the financial crisis: scenarios developed for Singapore in spring 2008 did include an extended recession but did not anticipate the magnitude of it: why? Two factors – lack of understanding of the interconnectedness of the global economy, and perhaps more important in this case, the fact that much of the global GDP was “shadow”, so did not appear on balance sheets: and even the Bank of International Settlements and the International Monetary Fund did not have a complete view of the size of the shadow economy. (Nouriel Roubini, http://www.roubini.com, who did, was thought to be a outlier). Lesson – question the data – could there be systemic gaps or errors?
“Learnings from the Long View” is available from Amazon.