Decision-making for many people is more like a process of guessing or betting on an outcome, from what to eat in a restaurant to choosing a job or investing in the stock market. Many also inform themselves, ask the right questions, but when it comes to the actual decision, they cheat their way through, decide somehow and hope for a good outcome.

When people are asked about the decision-making process, even high-ranking managers are more likely to list a list of actions than to name a comprehensible process. People also often invent a story according to which the decision somehow makes sense in retrospect. What is curious is that this story depends heavily on the outcome of the decision: If you have succeeded, the decision-making process is told quite differently than if you have failed. Cognitive scientists call this phenomenon of experiencing a decision as coherent in retrospect 'retrospective coherence'.

It is usually assumed that a positive outcome of a decision-making process automatically means that a good process has been used. This is not necessarily the case. That weight is often given to the outcome rather than the process is not uncommon in our society, where mistakes in the outcome are penalized. However, if the process itself is not sound, learning from mistakes becomes difficult, intuition is not trained, and the factors of chance and luck are given greater importance than they deserve.

The best way to make a good decision is actually a solid decision-making process(Russo & Schoemaker: Winning Decisions):

• Goal andframing: the decision maker's overall goal, including how they think about the knowledge on which they base their decision;
• A realistic approach to gathering information;
• Deciding: Organizing information and weighing different perspectives;
• An approach to communicating and implementing the decision made;
• Learning from experience, including a way to measure the effectiveness of a decision so that adjustments can be made

Now the decision-maker faces further challenges: Depending on the degree of complexity or uncertainty factor, these steps not only look different, but are also subject to completely different laws.

We distinguish between ordered domains and complex domains(Dave Snowden: The CYNEFIN Framework). Ordered conditions include everything that may be complicated but is computable, with known cause-effect relationships, such as repairing a car or building an airplane. In the vast majority of decisions, there are aspects that belong in the calculable domain and those that require a different approach. Most decision researchers advocate a good mixture of both.

The following aids, among others, can be used as decision-making aids under orderly conditions:

• Manuals, procedures, instructions
• Probability calculation, calculation models and algorithms
• Analysis and expert knowledge, logic
• Formal evaluation models, scenario planning

What if it's complex?

Complex conditions and uncertain circumstances prevail, for example, wherever we are dealing with natural conditions or with people and their relationship dynamics rather than with algorithms. There are so many unknown factors and their interrelationships that we cannot plan ahead or predict outcomes.

As a rule of thumb, if there are several hypotheses for the way forward or the decisions to be made that appear to partially or completely contradict each other, approaches and methods other than calculation or logic(if-then links) are required. It is astonishing how often people mistakenly try to use purely mechanistic methods to make complex relationships manageable and plannable, an approach that always has unintended consequences.

Probe-Sense-Respond

If the hypotheses and advice on how to proceed with a decision or challenge contradict each other, it is advisable to test ideas first. As a general decision-making aid for the complex domain, Dave Snowden calls the approach "probe - sense - respond": test - perceive - react/decide.

Ideally, several small test projects can be carried out in parallel and with contradictory basic assumptions, the result of which in the worst case is a learning experience and in the best case a dynamic way forward: 'safe-to-fail experiments'. In this way, various assumptions can be tested without basing the decision-making process on blind spots or overly narrow mental models - preferably before a lot of money, time and effort is invested in the further development and scaling of new approaches. This can avoid errors in thinking such as the Hawthorne effect(it was not the new approach that led to increased productivity, but the mere fact that it was new), confirmation bias(you only see evidence that confirms what you already assume, but not the evidence that confirms the opposite), or choosing the wrong frame of reference(the Encyclopedia Britannica almost went bankrupt because they kept the "sell books" frame of reference despite the emergence of new CD-ROM technology. Only very late did they switch to the "sell information" reframe). This is especially true when decisions concern scaling, growth or innovation.

Intuition and pattern recognition

Intuition is indispensable for making decisions under complex conditions. Curiously enough, decision researchers have discovered that our gut feeling sometimes delivers brilliant results, but usually produces appallingly mediocre results. The decisive factor here is probably the training of intuition.

When researchers investigated the decision-making processes of successful firefighters, they were initially puzzled to find that they neither followed set procedures nor seemed to make conscious decisions. Further investigation revealed that, after years of experience, incident commanders "just knew" what to do. They were able to intuitively recognize even the smallest patterns of fires, decide accordingly and act(recognition-based decision).

The German decision researcher Gerd Gigerenzer explains that experienced experts are better off relying on their (trained) intuition or simple heuristics than on complicated algorithms and calculation models when faced with a high level of uncertainty. Instead, beginners should first train their intuition before relying on it.

Use heuristics

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

Learning to deal well with complexity

Finally, it is important to develop your ability to work effectively with decisions under VUCA conditions (volatile, uncertain, complex and unclear). According to Theo Dawson, good decisions are most likely to be made when the complexity of a person's thinking matches the complexity of the challenges in the workplace. The most effective and agile decision makers rely on additional skills, including the ability to think and communicate clearly, and to learn to understand increasingly complex relationships. This includes the ability to distinguish between complicated domains and complex domains and their different requirements for decision making. Recognizing the inevitable complexity of our day-to-day decision-making requires, not least, the accompanying rejection of the temptation to want to make everything safe, predictable and plannable.

Sources:

Dawson, Theo: LDMA - Lectical Decision Making Assessment

Gigerenzer, Gerd : Risk-aware: How to make good decisions. Penguin Books, 2014

Gigerenzer, Gerd : Gut Feelings: The Intelligence of the Unconscious. Penguin Books, 2008

Klein, Gary: Streetlights and Shadows - Searching for the Keys to Adaptive Decision Making. MIT Press, Camebridge, Massachusetts

Russo, J. E.; Schoemaker, P.J.H.: Winning decisions: Getting it right the first time. 2002

Snowden, Dave: The Cynefin Framework

The author: Anne Caspari

Anne Caspari is a specialist in change and transformative processes. © Anna Caspari Photography

Dipl.-Ing. Anne Caspari is a specialist in change and transformative processes, in the context of personal development, leadership training and cultural development. She works with executives to support them in their quest for effective leadership and career development (Executive/ Developmental / Leadership Coaching). The focus is on developing the critical skills required to navigate the complexity and uncertainty that characterize today's business environment.

Ms. Caspari is co-owner of Entz von Zerssen, Caspari & Partner Coaching & Consulting(www.ezc.partners) and partner of Leadership Choices(www.leadership-choices.com).