Decision-making in the real world

Prediction markets and other “wisdom of crowds” approaches attempt to forecast the outcome of complex events based on probability estimates.  This is the classic “guess the number of jellybeans” approach. “Will people buy this product” is a prediction question. Understanding why, and what you can do about it, is an insight question. This is more useful in situations that require nuance, perspective, and interpretation; in other words, almost all important decisions in the real world.

A new WAY OF BUILDING strategy and foresight

Futurescaper builds upon decades of research about how people see the the world (through metaphor, mental models, frames, and cognitive biases) and about how decisions are made (through trade-offs, group bargaining, and communities of influence). We start with stakeholders’ awareness and perspectives, then use advanced visualisation techniques to represents them as collective mental models. This reveals a picture of the complex cause and effect behind difficult issues, helping you converge on the most important areas of uncertainty and influence.

Human insight, not big data

Complex strategic decisions often have no right answer. The most important questions require an understanding of who thinks what, why, and how they might respond. Leaders need to understand how people perceive an issue, in addition to how that issue actually works. Futurescaper’s unique approach maps these perceptions onto strategic options, providing unparalleled understanding of fast-moving, real-world challenges at speeds never before possible.

A decade OF RESEARCH & development

Futurescaper's inception began in 2006 as a PhD research project at MIT by Futurescaper's co-founder Dr Noah Raford, with sustained software development since 2011. Read the below journal article on the impact of networked approaches on strategic foresight and policy development that summarizes Futurescaper's research origins.