Is There a Method for Decision Making?

We make small decisions every minute without even thinking about it, we just go with the gutfeel. Most small decisions are made based on the heuristic’s technique, an approach used when finding an optimal solution is either impossible or impractical, and when we need answers in short order while working with a lot of information. However, there must be a more methodical way to arrive at decisions especially when dealing with big complex issues.

Here is one such method. In principle, the following are the main steps in decision-making process -

1) Determine the problem and its nature: First and the most important part of the decision-making process is identifying exactly what needs solving, i.e., defining the problem itself. The second part then is to determine the nature of the problem objectively. The decision makers must obtain all the relevant facts and data about the problem as much as the time permits.

If the problem is generic in nature, then there should already exist a predetermined choice of actions available from the past similar encounters. Also, existing known patterns and best practices can be leveraged in such case. However, if the problem is unique or has not been seen before, then one should follow the steps below -

2) Classify the problem: Using the data, the problem should be classified in one of the categories described below based on its level of complexity.

• Simple – this is a self-contained and trivial issue. It easy to comprehend.
• Complicated – this issue involves multiple independent components. It is possible to separate these components and deal with them in a systematic, logical, and orderly way that relies on a set of simple rules or algorithms. This fixed order may be difficult to detect at first and may look complicated, but it does allow one to identify a repeatable pattern.
• Complex – this is an issue involved multiple intertwined components and one cannot get a firm handle on the parts and there are no apparent repeatable patterns to deduce rules, or algorithms. Problems that are complex can be much more challenging since they have no obvious order, control, or predictability. This type of issue is more than the sum of its parts because its individual parts are interdependent and interact in unpredictable ways. For example, problems affecting many people is a complex issue as it inherently requires managing interests of many people at once where the interests of people can be interdependent, this is a complex challenge. Another example of this is integrating two merging businesses. One may have figured out this problem before, but whatever the solutions they applied in the previous situation may not generate the same constructive result the next time. In any case it is advised to break the complex problem into manageable parts that are reasonably isolated such that they have minimal interdependence on each other. These individual parts then can be treated as separate problems to solve.
• Chaotic – this type of issue is rare, unpredictable, fast evolving, with dynamic interdependencies, and virtually unsolvable. This requires careful analysis to see if the problem can be broken down into more manageable and relatively stable patterns. One must iterate through various ways to slice the issue until it can be broken down into reasonably independent parts that appear more predictable; when one succeeds in such breakdown then, like in the previous case, one may treat those parts as separate problems to solve.

3) Draft a clear problem statement: once the problem is categorised and dissected, by this step there should be a clear understanding of the problem and its components. A clear and objective problem statement should be drafted so everyone is on the same page with regards to the issue at hand.

It is very important to frame the problem correctly so proper solution alternatives can be found. For example, car brakes were invented as one of the solutions not just because it allowed the drivers to stop the car, the real problem the brakes solved was that it allowed the cars to be designed to move quickly and go faster.

4) Determine the scope: This step involves scoping and sizing the issue to identify the impact radius. This helps focus on the boundary conditions, that is, what must be fixed versus what may be nice to fix. The scoping step also involves identifying and assessing the risks of not solving the problem.

5) Decide what is the right vs acceptable action: This step is to investigate first what practical solution alternatives are available to address the problem. Again, it is worth emphasizing here that if the problem is not identified correctly then every solution alternative tabled most likely will miss the mark.

A solution defines a set of actions that must be undertaken to resolve the problem. At this step one should determine which solution will fully satisfy the mandatory part of the requirement specifications before attention is given to the compromises, adaptations, and concessions needed to make the solution acceptable based on its risk profile. All facts, data, risks, and benefits for each solution alternative should be evaluated for analysis preferably based on well-defined objective set of criteria. All assumptions and constraints should be identified for each solution alternative. All solution alternatives should be evaluated, and a decision should be made to select the solution option that meets most of the criteria. All the evaluated solution alternatives and the selected option should be documented along with the rationale for their rejection and selection, respectively. At this stage the decision is made.

6) Determine the plan to carry out the actions: This step is to determine the detailed plan to carry out the actions for the decision, by identifying the people who will carry out the actions and listing the details of their assigned activities. At this step communication plan should be created to inform all stakeholders about the action plan and its progress.

7) Test the validity and effectiveness of the actions: To ensure the decision and action plan are correct, they should be reviewed by the relevant stakeholders. The assumptions, actions, and anticipated results should be verified through simulated but realistic scenarios to check for validity and effectiveness of the plan. And finally, the stakeholders should monitor and oversee implementation of the action plan.

Common Decision-Making Biases

Just following a decision-making process does not necessarily guarantee one to arrive at a good decision. Everyone is susceptible to pre-conceived notions and natural biases, and these can and do interfere with one’s ability to make right and objective decisions. It is therefore always good to be mindful of biases especially when tasked with making the big and important decisions.

Here are some common types of biases. This is not a complete list but already by looking at the number of biases should signal warnings about innate fallibility of our minds.

• The Confirmation Bias: It is the tendency to listen more often to information that confirms our existing beliefs. Through this bias, people tend to cherry-pick the data and favour information that reinforces the things they already think or believe.
• The Hindsight Bias: It is a common cognitive bias that involves the tendency to see events, even random ones, as more predictable than they actually are. One with this bias has the tendency to say, "I knew it all along".
• The Anchoring Bias: It is the tendency to be overly influenced by the first piece of information that is seen or heard.
• The Actor-Observer Bias: It is the tendency to attribute our actions to external influences and other people's actions to internal influences. The way we perceive others and how we attribute their actions can be heavily influenced by whether we are the actor or the observer in a situation. For example, you might say you flunked a test because there were too many trick questions. However, when it comes to other people failing the same test, you may say they failed the test because they lack diligence and intelligence, etc., and not because they had trouble with those trick questions.
• The Self-Serving Bias: The self-serving bias is a tendency of people to give themselves credit for successes but lay the blame for failures on outside causes. When you do well on a project, you assume that it is because you worked hard. But when things turn out badly, you are more likely to blame it on circumstances or bad luck or even on other people’s failures.
• The Optimism and Pessimism Bias: It is a tendency to overestimate the likelihood that good things will happen to us while underestimating the probability that negative events will impact our lives. And you might have guessed, the pessimism bias is the reverse of optimism bias.
• The Misinformation Effect: It is the tendency for memories to be heavily influenced or even altered later by things that happen after the actual event itself. Memories are fickle and researchers have found that they are surprisingly susceptible to even very subtle influences.
• The False Consensus Effect: It is our tendency to overestimate how much other people agree with our own beliefs, behaviors, attitudes, and values. We tend to overestimate that most people agree with and share our preferences.
• The Halo Effect: It is the tendency for an initial impression (good or bad) of a person to influence what we think of them overall. Also known as the "physical attractiveness stereotype.
• The Availability Heuristic: It is the tendency to estimate the probability of something happening based on how many examples readily come to mind. For example, after seeing several news reports of car thefts in the neighborhood, one might start to believe that such crimes are more common than they are.
• The Survivorship bias: Survivorship bias or survival bias is the logical error of concentrating on the people or things that made it past some selection process and overlooking those that did not, typically because of their lack of visibility.

A well-known example of how to avoid this bias is captured in a World War II story. A statistician named Abraham Wald rightly avoided the survivorship bias when considering how to minimize bomber losses to enemy fire.

He inspected the planes that were returning to the airbase and instead of attributing all the credit to the pilots’ survival skills, he correctly determined that the returning planes survived because the weakest areas of the plane were not hit and the areas that needed more protection were those that had the least amount of bullet holes (the engine, for example).

In conclusion, it is a good practice to adopt and follow a methodical approach like the one described in this article for making decisions especially within a group setting. A methodical approach can help break down a complex problem into manageable units and can then be defined succinctly with a clear problem statement. The methodical approach can also help eliminate subjectivity. It provides the opportunity to avoid biases that might be reflected in the opinions expressed during the discussions so they can be challenged and discussed openly to minimize their impact on the final solution selection.

Author: Sunil Rananavare, IT Strategy Planning and Architecture (CIO Advisory)

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The views in the article are author’s own and not necessarily of his employer.?