Mastering the art of decision-making

What do we need to know to develop good decision-making for both normal and complex conditions?

Although decision-making is a critical aspect of our dailypersonal and professional lives, and despite how frequently we engage in makingd ecisions every day, a significant number of us are remarkably unaware of the underlying process involved in decision-making. And that is the case, whether the decisions are made in normal or under complex conditions. Many people just don’t know how to do it: making good decisions.

For many, making decisions resembles a gamble or an educated guess, wether it is about choosing a meal at a restaurant, selecting a job or investing in stocks. Even those who gather relevant information and ask good questions find themselves improvising when it comes time to make the actual decision, ultimately making a choice in some manner, muddling through and hoping for a positive outcome. ‍

The Black Box

Cognitive science, and here in the works of Dave Snowden and Gary Klein, have shown that people make decisions using a process known as conceptual blending. When faced with a decision, we typically review only about 5%-10% of the available information and then perform a "first-fit" pattern match with fragmented memories in a subconscious process, rather than seeking the best fit. This involves assembling bits of knowledge and blending them with memories, particularly those that have been recently activated, leading to a unique course of action that frequently contradicts logic and insight. Since we are often unaware of these internal mechanisms, we tend to describe this opaque process as relying on "intuition" or a"gut feeling."

When asked about a reliable decision-making process that others could logically follow, even senior leaders often resort tooutlining a series of actions rather than providing a clear method, as shown inour work with some UN organisations.

Retrospective Coherence

Additionally, after having made a decision, it's common for individuals to construct a narrative that rationalizes their decision in hindsight. Interestingly enough, the nature of this narrative largely hinges on the decision's outcome. Success stories are narrated differently compared to tales of failure. Cognitive scientists have labelled this tendency to view or narrate past decisions as sensible or justified in hindsight as "retrospective coherence". A very unreliable tale.

Outcome-Based Culture

Frequently, there's an assumption that a successful outcome signifies a well-executed decision-making process, but this isn't always the case. It is not uncommon in our society, that outcomes are valued more than the processes that lead to them, primarily because we don't have school systems and cultures that value learning through mistakes, errors and probing. Yet, without a dependable process, the opportunity to learn from mistakes is diminished, intuition remains untrained, and reliance on chance, speculation, and sheer luck may be unduly cultivated. It sounds like a truism, but in reality, this is not widely recognized: The best way to make a good decision rests on a solidand methodical decision-making process. ‍

Russo and Schoemaker recommend the following process (adapted):  

  • Goal and Framing: the general goal of the decision maker, including how he thinks about the knowledge on which he bases his decision.
  • A realistic approach to gathering information.
  • Organize information andweigh different perspectives.
  • The actual act of deciding.
  • An approach to communicate and implement the decision made.
  • Learn from experience, including a way to measure the effectiveness of a decision so that adjustments can be made  

So far so good.

Unfortunately, as decision-makers we face further challenges: Depending on the level of complexity or the degree of uncertainty that provides the context to the decision, these steps not only look different but are subject to completely different dynamics. For a basic context analysis, we can refer to Dave Snowden’s Cynefin© Framework. It helps differentiate between ordered domains, where things might be complicated but are predictable and have known cause-and-effect relationships (like repairing a car or building an aeroplane), and complex areas that require different approaches. The framework is a great tool for decision-making support, guiding us to recognize when conditions are ordered and when they fall into the realm of complexity. Most experts on decision-making advocate for a balanced approach that navigates between these two domains. For more insights, see Dave Snowden's article in the Harvard Business Review titled "A Leader’s Framework for Decision Making,"

The Cynefin Framework

As decision aids under ordered conditions, the following decision-making support can be used:

·      Manuals, procedures, instructions

·      Probability calculation,calculation models and algorithms

·      Analysis and expert knowledge, logic

·      Formal evaluation models, scenario planning, and some systems thinking approaches.

What if it’s complex?

Complex conditions and uncertainty prevail wherever we are dealing with natural conditions or with people and their relationship dynamics instead of algorithms and technical problems. The presence of numerous unknown factors and interdependencies means that straightforward cause-and-effect reasoning, planning, or predicting outcomes becomes unfeasible.  

A useful rule of thumb is this: When faced with multiple hypotheses for a course of action or impending decisions that either partially or entirely seem contradictory, we are navigating a complex adaptive context. Such situations demand strategies and methods beyond mere calculation or logical deduction (the if-then kind). It's remarkable how frequently there are attempts to tame and foresee complex scenarios with linear and complicated approaches—a tactic that is fundamentally flawed and bound to fail.  

Probe Sense Respond

In the realm of complexity, Dave Snowden recommends adopting a "probe – sense – respond" approach to testing ideas. Ideally, several small test projects can be carried out in parallel and with contradicting basic assumptions. At the very least, this strategy guarantees learning; at best, it paves the way for discovering a dynamic path forward. Through these concurrent 'safe-to-fail experiments,' conflicting assumptions, ideas, and hypotheses can be scrutinized without the decision-making process being compromised by blind spots or overly restrictive mental frames – and ideally, this is done before significant resources are committed to the development and scaling of new strategies.

 

Employing this strategy enables decision-makers to avoid blind spots in their perception or framing andmitigate some of the more significant cognitive biases, such as:  

  • The Hawthorne effect: This bias suggests that increased productivity resulted not from the new approach itself, but from the mere novelty of the change.
  • Confirmation bias: This is the tendency to notice and interpret evidence in a way that confirms one's preconceptions while ignoring or undervaluing evidence that contradicts those beliefs.
  • Keeping the same frame in the face of changing circumstances: An example of this is the near bankruptcy of Encyclopaedia Britannica, which clung to the frame of reference "we sell books" despite the advent of new CD-ROM technology. It was only at the last moment that they shifted to the reframe "we sell information."

Avoiding decision-making blind spots counteracts the automatic first-fit pattern match and is especially important with decisions regarding innovation, development and scaling.  

But what about Intuition?

Intuition plays a critical role in decision-making,especially under complex conditions. Interestingly, decision-makers have observed that while gut instinct can sometimes lead to outstanding outcomes, it often yields disappointingly average results, a phenomenon related to the "first fit pattern match" concept. The key to leveraging intuition effectively appears to lie in its training.

When researchers examined the decision-making processes of successful and seasoned firefighters, they were initially amazed to find out that these neither followed specified procedures nor seemed to make conscious choices. More detailed inquiries showed that after years of experience, operations managers “simply knew” what had to be done. More like masters of martial arts, they were able to intuitively recognize even the smallest patterns of fire and smoke, decide and act accordingly (recognition-based decision; see Gary Klein’s research).

German decision researcher Gerd Gigerenzer explains that when faced with high levels of uncertainty, seasoned experts tend to depend more on their refined intuition or simple heuristics rather than complex algorithms and elaborate calculation models. He suggests that beginners should focus on training their intuition before placing reliance on it, highlighting the distinction between the inexperienced and the adept in navigating uncertain situations through intuitive judgment.

Mental Short Cuts

Heuristics are mental strategies or simple rules of thumb that help us to concentrate on the essentials with limited knowledge and time and to ignore the rest to be able to make decisions at all. They are essential in the face of complexity and uncertainty. The rules should be simpler the more complex the terrain in which we want to make decisions. Harry Markowitz received a Nobel Prize in 1990 for a super-complex calculation model for investment strategies. When asked, he explained that he preferred to use a simple rule of thumb for his own investments: distribute your assets evenly across many options (1 / N).

Befriend Complexity

In the end, it's key to improve your skills for making decisions when things are complex and uncertain. Theo Dawson believes that people are more likely to make good decisions when their way of thinking matches the complexity of the problems they face at work.

The best decision-makers are not just smart; they also know how to think and communicate clearly, and they increasingly embrace complex relationships and befriend ambiguity. This includes knowing the difference between complicated situations and complex challenges and the specific needs for making decisions they require. Realizing that making decisions is naturally complex means we should let go of the hope of making everything certain and predictable.

Sources

Dawson, T.(2014): LDMA – Lectical Decision Making Assessment www.lectica.org

Gigerenzer, G. (2014): „Risikobewusst: Wie man gute Entscheidungen trifft“. Penguin Books

Gigerenzer, G. (2008): „Bauchgefühle: Die Intelligenz des Unbewussten“, Penguin Books Klein, G. (2009): Streetlights and Shadows – Searching for the Keys to Adaptive Decision Making; MIT Press, Camebridge,  Massachusetts

Russo, J. E. & Schoemaker, P.J.H. (2002): Winning Decisons.

Snowden, D.; & Boone, Mary E (2007): A Leader’s Framework for Decision Making. Harvard Business Review

Pictures: Photos by Anne Caspari; Robert Harkness and LuboMinar, and David Ownen all on Unsplash

Cynefin® Frameworkused with permission from The Cynefin Compan

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