Chapter 9. The Do Loop – The Eight Skills of Adaptive Foresight

Skill 4. Strategy (Decisive and “re-convergent” thinking).

Divergent/evolutionary and convergent/developmental thinking and actions are always in balance  with and opposition to each other in the Eight Skills model. Each of these skills mixes divergence and convergence, but a few are dominantly one or the other. Skill 1, learning, is a mix. It is commonly initially divergent, exploring many possible paths to useful knowledge, then it is convergent on deep learning of a subset of what has been surveyed. Skill 2, anticipation, is dominantly convergent. While it may begin with divergent scanning, it primarily seeks to narrow learning down to the most useful, evidence-based forecasts, predictions, and certainties. Skill 3, innovation, is dominantly divergent again, as it explores many possible futures, creative options, and uncertainties, while converging on a few innovations. Skill 4, strategy, or preference foresight, can start again with divergence, weighing various strategic possibilities, but it is dominantly convergent, as the team uses strategic thinking to converges on just a few options for action. Skills 6 and 7, influencing and relating, are often an even mix of both divergence and convergence. Skill 7, reviewing, like learning, is also often an even mix. It is initially divergent (auditing, sampling), then becomes convergent on what recently worked and what didn’t, in a way that feeds us right back into Skill 1, with new learning.

We can now observe that when we get to strategy and execution, Skills 4 and 5, we come to two skills in a row that are dominantly convergent, on getting the optimal strategy and action done. Having two convergent skills in a row at the center of the Do loop helps us understand that executing adaptive strategy is the firm’s most important survival task. Execution (tactics, action) and strategy (prioritization, goals, models, plans) are intimately connected. As Sun Tzu says, “Strategy without tactics (good execution) is the slowest route to victory. Tactics without strategy is the noise before defeat.”

The Strategy function begins with activities like Values determination and Visioning (aspirational thinking that results in motivating envisioned future states, and leadership commitment to those visions). Some foresight consultancies, like the Institute for Alternative Futures, have become well known for aspirational (vision- and values-driven) strategy work. When comparing visions to scenarios, which immerse the client in options, but don’t necessarily ignite passions, IAF president Clement Bezold likes to say “Visions are futures for the heart; scenarios are futures for the head.” Finding the noble, motivating vision can be incredibly energizing for the team, as we’ve seen in many a startup and independent business unit. Think of the Bandley III, the Macintosh unit, under Steve Jobs at Apple in 1983.

Steiber (2014)

Steiber (2014)

Strategy also includes Framing (determining the scope, depth, and methods of strategy and foresight work), an activity further discussed in Thinking About the Future (2013). Next, strategy work involves Prioritization and Goalsetting (for example, using SMART goal criteria). Determining the firm’s objectives and key results (OKRs, measurable goals) with broad stakeholder engagement is one of the most difficult yet empowering activities in strategic management. Google uses OKRs extensively to manage their strategic innovation initiatives. Steiber’s The Google Model (2014) is great new book providing details on their process.

Strategy must also include some level of Analysis, a function that generates and compares a variety of future action options for the organization, using some type of criteria. It includes real options analysis and other types of decision support, methods that help the firm make chices among known options. Strategic analysis is used to make assumptions about how a system works, break the system into conceptual parts, and do systems thinking about or model how those parts interact, and their relevance to organizational objectives. There are a vast range of analytical methods and communities applicable to strategy, including those from business, economics, engineering, computing, politics, intelligence, and others. For a great article describing how executives learn strategic thinking over their career, in a developmental process, or fail to learn it, see Ellen Goldman’s Strategic Thinking at the Top (free), MIT Sloan Management Review, Summer 2007. For an excellent history of strategy consulting, and how strategy is used in modern corporations, see Walter Kiechel’s Lords of Strategy (2010).

INFORMS, the leading Operations Research/Management Science (OR/MS) Professional Association

INFORMS, the leading Operations Research/Management Science (OR/MS) Professional Association

A few business problems can be so well defined and are so repetitive that operations research (known in business as management science), and other optimization methods will get us to the “right” strategy, at least for the chosen strategic objectives of the firm. But whether those objectives are the best ones for a particular firm in a particular context is always an intuitive bet on the part of the leaders, and will ultimately be determined by the selective environment. The ultimate goal for any firm is to have a continually adaptive strategy, even as environmental conditions constantly change. Most business problems, being complex or poorly structured and defined, have no such “right” answer. It is with those problems where experience, cognitive diversity, and good use of the Eight Skills can really help the firm adapt.

Bradford & Duncan (2000)

Bradford & Duncan (2000)

The Planning function is often thought of as the last step before action, and the culmination of strategy and analysis. Whether simple or detailed, formal or informal, good plans help us to coordinate our resources and energies toward desired outcomes.  Strategic planning has been used since the 1960s by larger firms, but as Lou Gerstner says in his classic “Can strategic planning pay off?”, McKinsey Quarterly (1973), and Henry Mintzberg explains in The Rise and Fall of Strategic Planning (2000), it is very easy for a firm to over-plan, to use plans as a poor excuse for action, and to create plans that are not widely internalized or executed as written, even in the early steps. Bradford and Duncan’s Simplified Strategic Planning (2000) gives advice on how to avoid these traps with brief, fast, and continuous high-utility planning.

A firm’s plans may or may not involve broad foresight. Sometimes anticipation isn’t possible, and one instead needs strategic agility, moving as quickly as possible from strategy to action. We’ve previously mentioned several books helpful to that approach. At other times, when facing big bets and costly decision points, and when a little reflection time can be found prior to the decision, the level of ideation (alternative futures generation), anticipation and strategy in the plan can be critical. Did the team explore the most relevant probable and possible futures related to objectives as part of strategic planning? If not, the plan will be blind to the environment, and may have little long-term value.

Fitness Landscape (A fitness variable (e.g. preference, growth, profit) and a search space (strategic options)

Fitness Landscape (A fitness variable (e.g. preference, growth, profit) and a search space (strategic options)

In the Evo Devo model, a good practice guideline for Strategic Management, also called adaptation in this guide, is to learn the landscapes. The interactions of actors that are subject to both probable and convergent futures (development) and possible and divergent futures (evolution) can be roughly graphed as an adaptive landscape of constantly shifting peaks and valleys on any adaptive variables (e.g. efficiency, performance, preference, product features, growth, profit), as in the picture at right. Figuring out which variables matter the most is today an art. As Fleming and Sorenson note in Navigating the Technology Landscape of Innovation, MIT Sloan Management Review, winter 2003, leaders can often see only a little way out on their fitness landscapes from their current location (e.g. their current cost basis, product features, and price). Gaining a better view of all the possibilities available to them, and whether any would be more adaptive for the dominant goals and strategy presently being executed (e.g. growth, profitability, quality), requires careful market and technical research, followed by good ideation.

Even when quantitative graphs aren’t available to us, the landscape metaphor still helps us mentally visualize our strategy. At any point in time, some individuals, organizations, and markets will be adapting better than others (climbing adaptive peaks, by on various landscapes), and some will be losing out (falling into valleys). The lay of the relevant landscapes at any time can always be used to guide our strategies. Leaders need to know what customers think of their products and policies relative to competitors (customer preference landscape), where they are in cash flow and sales momentum (financial landscape), which of their competitors are doing well and doing poorly (competitiveness landscape), and who their best potential allies are (strategic alliance landscape). For more on the latter, see Doz and Hamel’s Alliance Advantage, 1998.

If learning is foresight’s first and most fundamental skill, and strategy is the heart of foresight, and then learning the relevant landscapes is the heart of strategy. Every manager’s central goal is to adapt enough to survive, to keep successfully riding the tiger of change. Key to that survival is knowing where the peaks and valleys are on all the relevant landscapes, then developing good competitive and cooperative strategy, analysis, and plans to navigate the present, and capitalize on what your team can see around you.

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