Chapter 4. Models – Foundations for Organizational Foresight

2. Toffler’s and Amara’s Three Foresight Skills (Thinking Styles)

Let us now revisit the Three Ps model of the three basic foresight thinking styles. Independently, Alvin Toffler (1970) and Roy Amara (1981) each proposed that there are three fundamental types of foresight work, involving discovering or creating:

  1. Probable Futures (predictable, constrained, secure, and conservative), and
  2. Possible Futures (unpredictable, creative, free, and novel),
  3. Preferable Futures (individually or group-preferred agendas for the future).

We have just explored the first two types in the Evolutionary Development model. We used slightly different words, including evolutionary (tree-like, divergent thinking and action) and developmental (funnel-like, convergent thinking and action), but we were describing the same topics: possible and probable styles of thinking, behaviors, and futures.  Note also that in Evo Devo theory, it is convention to list evolutionary processes first, and developmetal processes second. In foresight work however, it is usually best practice to try to identify developmental processes first, and then consider evolutionary possibilities in the next step. Otherwise, you can waste a lot of time and energy entertaining possibilities that are very unlikely, as they don’t fit with the expected future.

Recall that there is also a third kind of thinking that steers us toward our preferences, our goals, visions, plans, or agendas. The best preferences are adaptive, meaning they allow us to survive and thrive in the world. See Jean Russell’s excellent Thrivability, 2013, for more on what thriving looks like, in a world of constant change. It is this adaptive thinking, planning, and action that organizations value most, and it arises out of a blend of the first two types. Preferable futures are the heart of the Adaptive Foresight model, and of most organizational foresight practice. But a central claim we make in this guide is that it is only by carefully considering organizational probabilities and possibilities that our most adaptive preferences and strategies can be built.

Graphically, we can visualize preferable futures as neither trees or funnels, but as competing and cooperating preference peaks in an “adaptive landscape.” See the top figure in the picture below for an example such a landscape. Such landscapes show peaks and valleys in relation to various adaptive fitness variables (for example, efficiency, cost, consumer popularity, rate of growth or innovation). Sometimes we can see one dominant preference peak on a landscape, and at other times there are multiple peaks, representing many competing and cooperating agendas and actors. Mapping those peaks, understanding the agendas of all relevant parties, and the organizational resources available to each for executing their agendas, is the foundation of good strategy and planning.

Eleven Core Foresight Functions, and Three Core Foresight Skills

Eleven Core Foresight Functions, and Three Core Foresight Skills

Social network analysis and predictive analytics software that includes semantic analysis, like that of Recorded Future, are exciting new ways of building quantitative maps of all the preference peaks and organizational capacities operating in an industry or market. As our natural language understanding systems improve, so too will our online preference and capacity maps, and we can then expect a new type of statistical social foresight, working off adaptive landscape maps, to emerge.

The Three Ps are the core three of the Eight Skills of Adaptive Foresight. As we’ll see in Chapter 5 (The Do Loop) we can associate these three skills with fully twelve of the Twenty Specialties of foresight practice covered in Chapter 1. This helps us see that the Three Ps are the core of modern foresight work, but they are also not all the specialties we need for Adaptive Foresight, which leads to successful action.

The Three P’s Foresight Skills and Specialties are:

  1. Probabilities, aka Anticipation
    Data Science & Machine Learning,
    Forecasting & Prediction
    Investing & Finance,
    Law & Security,
    Risk Mgmt & Insurance.
  2. Possibilities, aka Innovation
    Alternatives & Scenarios,
    Entrepreneurship & Intrapreneurship
    Facilitation & Gaming,
    Ideation & Design
    Innovation & R&D.
  3. Preferences, aka Strategy
    Analysis & Decision Support
    Strategy & Planning.

Again, the Three Ps of foresight don’t cover the entirety of our field. They are just what we consider the most foundational categories. In the Eight Skills, we’ve just seen five supporting foresight skills that we also consider critical to tying foresight to action in the world, in a perception-action cycle.

There are also at least three other important foresight categories that professionals discuss in various contexts. These are plausible futures, expected futures, and wildcards (low probability, high impact events). Let’s look at each in turn and see how they can be useful enhancements to our 3Ps and Eight Skills models:

Plausible futures are those that the client believes are either possible or preferable. These may only be roughly consistent with the Three Ps. An important strategy with plausible futures is to discover the edges of your client’s mental plausibility map. Does it include all the generally acknowledged possible and preferable futures relevant to the firm’s goals? If not, a good foresight professional will help their client to expand their mental models to include the full Three Ps map, so they aren’t blindsided by futures they don’t realize exist. Another good strategy is to see if your client’s plausibility map extends past the Three Ps into fantasy. If it includes impossible or highly unlikely or widely unpreferred futures, and if they are making strategy based those beliefs, you need to help them bring their expectations back to the Three Ps map, or their incorrect mental models may lead to disaster.

Expected futures are those that the client, or the foresight practitioner, believes are either probable or highly preferable (and probable), whether or not they actually are. Again, the client’s or practitioners expectation map may be only roughly consistent with the Three Ps, and alerting them to this discrepancy can do them a great service. Does the client or practitioner expect something will happen that is in actually quite unlikely? Or vice versa? Poor expectation maps are common in big firms who believe their past performance is a guarantee of future success, or that they are too big to fail. Some form of bias, groupthink, or lack of feedback (Skill 8) is very likely involved.

It is also important to explore wildcards (low probability, high positive or negative impact events, a special subset of probable futures) when a firm is making big strategic bets and committing to path dependent (not easily reversible) decisions. Having a cognitively diverse executive team, bringing in iconoclasts (people with practical experience who reject orthodoxies and think in unconventional ways), or designating devil’s advocates in internal strategy discussions are among the ways to uncover wildcards, and improve the odds that organizational strategy will be resilient to them if they emerge. You may also need to help your client build intelligence systems that can give them early warning if a wildcard looks like it might actually occur. A few good books on wildcards are futurist John L. Peterson’s Out of the Blue (1997) and Nassim Nicholas Taleb’s The Black Swan (2010).

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