The application of Deep Uncertainty approaches for strategy design in possible dynamic, high dimensional futures

The world is growing less predictable and more complex. The ability to design long term strategy is increasingly challenging. In recent years, this challenge has led to poor preparedness and handling of crises across finance regarding the impact of complex derivatives and inflationary forecasting; health regarding Covid-19 pandemic preparedness; energy forecasts for economic competitiveness and net zero planning, trade for supply chain planning, and geo-politics as to the status quo regarding the rules based global order evident since 2024. It is only growing as the recent geopolitical events from the blockage of the Straits of Hormuz and its concomitant geo-economic implications have testified. Within this backdrop, this presentation argues that a paradigm shift is needed in the way that analytical communities across academia, consultancy and multi-lateral organisations think about unknown and unknowable futures. Specifically, it asserts that the analytical community should augment its legacy decision support tools with 'deep uncertainty' approaches, in order to: (i) enable it to shift from static-state strategy stress testing to dynamic stress testing; (ii) enhance cross-stakeholder transparency and understanding of risk through novel visualisations; and (iii) integrate more diverse insights in the red teaming of strategy performance in possible futures. The presentation will provide examples of the novel application of deep uncertainty approaches to: net zero technology portfolio design; technology learning curve analysis; and firm level investment analysis.