Updated: Dec 15, 2020
As a marketer, I’ve always been attracted by the psychological aspects that influence people in decision-making.
They help me understand what happens in a prospect’s mind when they are deciding whether to buy a product or service and guide me to make effective strategic decisions.
If you want to learn how to effectively evaluate alternatives, discover what disruptive elements come into play during the decision-making process and the best tools to use, then keep reading my guide!
Table of contents
THE DECISION-MAKING FRAMEWORK
Decision-making is the process which enables people to make a decision between two or more alternatives. The outcome of each alternative is associated with an expected value and a certain degree of uncertainty.
Due to this uncertainty, the decision-making process requires great attention in evaluating the alternatives.
The triangle below represents the three components of decision-making.
The new rational manager: an updated edition for a new world, published in 1997 by Charles H. Kepner and Benjamin B. Tregoe, shows how problem management should be carried out before making a decision. The information gathered in this phase can be used to perform decision analysis.
Instead, evaluating risk is necessary for future objectives or strategies.
For definition, a decision regards an action that still has to happen. That’s why decision-making needs a risk analysis of the alternatives.
Defining decision analysis
Decision analysis is a process to determine the pros and cons of all possible outcomes.
Decision analysis requires a finite number of alternatives. Sometimes, the less information, the better.
As Robert Duncan explains in his work, Characteristics of organizational environments and perceived environment uncertainty published in 1972 by Administrative Science Quarterly, a decision maker seeks information to reduce or eliminate risk (uncertainty).
On the other hand, information overload occurs every time there is a gap between volume of information and assimilation capacity. In 2007, Monash Business Review issued Decision-making: too much info! by Ambalika D. Kutty, Himanshu Kumar Shee and R.D. Pathak who explained how excessive information can negatively affect decision-making.
A simplified step-by-step process to decision analysis should be:
Listing all the possible alternatives;
Setting the parameters to evaluate each alternative;
Reordering or prioritizing the alternatives according to the degree of attractiveness set by the decision maker;
Making a final decision.
The last step may sound obvious, but analysis paralysis is very common in organizations. Over-analyzing or over-thinking a situation paralyze the outcome, since a decision is never made.
7 steps of the decision-making process
According to the two experienced business managers and educators Phil Higson and Anthony Sturgess, who published Uncommon leadership: how to build competitive advantage by thinking differently in 2014, the decision-making process can be divided into 7 steps.
A structured decision-making model, based on a rationalistic approach, can be made by 7 steps:
Identify the decision. The first step is realizing what decision you need to make and its nature;
Gather information. Get relevant information and insights about your decision: what’s relevant and what’s not? Who can influence the final event?;
Identify the alternatives. What different courses of action do you have? What different data interpretations may be possible?;
Weight the evidence. Based on the intel you have, list the pros and cons of each alternative and imagine its final outcome. Then, order the alternatives according your specific value system;
Choose among alternatives;
Review the decision and its consequences. Has the outcome satisfied the need in step one? You may want to review the previous steps and acquire more info on your options, add additional details and explore other alternatives.
The 7 steps of the decision-making process is an example of rational decision-making model. It brings logic and order to decision-making and consists of a series of steps which start by identifying a problem or opportunity and end with actions taken upon guided decisions.
What are the benefits in using a rational decision-making model?
In 2002, the professor of management Paul C. Nutt at Ohio State University published Why decisions fail: avoiding the blunders and traps that lead to debacles, a study based on over 400 strategic decisions made by top managers of different organizations.
His analysis revealed that 2/3 of all decisions are based on error-prone or controversial tactics. He said that:
[Managers] believe that following recommended decision-making practices would take too much time and demand excessive cash outlays.
He identified three main blunders:
Rush to judgment occurs when managers find an issue and patch it up with the first solution that they come across. They fear to leave concerns unanswered and feel the pressure from colleagues and supervisors;
Misuse of resources happens when decision makers spend money (sometimes millions of dollars) on an evaluation to support a hurried selected decision. They should also invest in other aspects of decision-making, like gathering information about the concern, set expectations and find who may stop action;
Failure-prone tactics occur every time a manager approaches decision-making with a wrong methodology. Nutt highlighted how critical participation is: decisions with a prior participative phase grants over 80% of success. He revealed that only 1/5 of the decisions are founded on participation.
Following good decision-making practices actually costs very little, especially when you compare it to the costs of dealing with the consequences of a debacle.
Defining problem management
Problem management is a process which takes care of the life-cycle of every problem in an organization.
It includes all the activities required to identify what caused a problem (root cause), how it can be resolved, how to implement the resolution in the organization and how to prevent the same incident over time.
Another scope of problem management is to store issues’ information and workarounds to reduce future number and impact of incidents.
It activates when something negatively affects the organization.
How can you diagnose and fix problems in your business?
You should craft a service blueprint: a detailed process flow chart.
Defining risk management
The International Organization for Standardization (ISO) codified risk management standards in ISO 31000 and gave the following definition:
Risk management represents the coordinated activities to direct and control an organization with regard to risk.
In the same document, risk is defined as:
The effect of uncertainty on objectives.
In other words, risk management is the process to decrease or eliminate risks.
Risk is composed of two elements:
The probability that something goes wrong;
The costs or negative consequences of the worst scenario. In other words, the outcome when something actually goes wrong.
How can you identify and decrease risks in a business?
In brief, the prior step to risk management is risk analysis. It includes all the activities required to identify threats and estimate their likelihood of materializing.
Then, you want to estimate the risk of each threat using this formula:
Risk value = probability of event x cost of event
To calculate the probability of a single random event with mutually exclusive outcomes (e.g. in a horse race, a certain horse wins or it doesn’t), you can use this formula:
Probability = event ÷ outcomes
Let’s consider a 6-sided die. If it rolls a 3, it can’t also roll a different number at the same time (event with mutually exclusive outcomes).
Your event is rolling a 3 and the total number of outcomes is 6 (as many as the die’s sides). The probability that the event occurs is: 1 ÷ 6 ≅ 16.7% (see image below).
Let’s now consider a jar with 5 red, 4 green and 11 blue balls. What’s the probability of drawing randomly a red ball from the jar?
You divide the number of events by the number of outcomes: 5 ÷ 20 = 25% (see the image below).
How can you calculate the probability of multiple events?
You consider each event separately and then multiply their probability together:
Probability event 1 x probability event 2 x … = probability of multiple events
Let’s consider the same jar mentioned above. How can you find the probability of drawing a red ball the first time, a green ball the second time and a blue ball the third time?
Calculate the likelihood of each event separately, but keep in mind that you are extracting a ball every time. It means the total amount of balls decreases of 1 per drawing.
5/20 x 4/19 x 11/18 = 44/1368 = 0.032 = 3.2% (see image below).
You can replicate this formula for the rolling 6-sided die. In this case, the events are separate and don’t influence each other. The probability to roll the same number for two consecutive times is:
1/6 x 1/6 = 0.0277 ≅ 2.8%
Once you have estimated the risk value, you can proceed by choosing a risk management strategy:
You would avoid the risk when there are no relevant advantages for your organization to take it;
You would share the risk with partners, team or third party organizations. For instance, when you purchase health insurance, the deductible is the risk value you are willing to take. Another example can be represented by joint-products (where multiple companies unite to produce and market a product/service) or a differentiated investments portfolio;
As a last resort, you could accept the risk when the insurance cost is higher than the value of potential losses or when the possible gain is worth the risk;
Even if you accept the risk, you should activate preventive strategies to identify possible weak points and take actions to reduce the probability of unfavorable events.
ROLE OF EMOTIONS IN DECISION-MAKING
Decisions can be divided into two categories:
They can be programmable when they regard routines or repetitive processes governed by standard procedures. They are characterized by a low degree of risk;
They are not programmable when they are related to unexpected or new situations which require specific tactics. They are characterized by a higher level of risk.
In both cases, you can use a rational approach by evaluating the possible options and analyzing them, in terms of costs and benefits, to maximize earnings and minimize losses. However, emotions will always limit the quality of logic and generate irrational decisions.
Emotion is the most disruptive factor in decision-making. They are inevitable, can mislead and alter perception. They can be:
Emotions are additional information to consider in decision-making. They guide attention towards certain aspects rather than others and can be used in heuristic decision-making strategies.
Defining heuristic decision-making
Heuristic decision-making focuses on unconscious rules and some variables of the decision rather than others.
It decreases costs and time in decision-making, resulting far quicker than step-by-step processing.
Although heuristics allows to drop evaluative elements, it can mislead and produce inaccurate outcomes.
An example of heuristic decision-making is the gambler’s fallacy, which is also known as the Monte Carlo fallacy or fallacy of the maturity of chances. It represents the wrong belief that if an event occurs more often than in the past, its probability to happen in the future decreases (or vice versa).
As I’ve already explained in risk management, the probability of an event is not related to what happened in the past (statistically independent events).
Another heuristic behavior is the compromise effect. Decision makers would prefer moderate alternatives rather than extreme ones.
In 2012, the journal of the Society for Judgment and Decision Making (SJDM) issued The effect of incomplete information on the compromise effect by Shih-Chieh Chuang, Danny Tengti Kao, Yin-Hui Cheng and Chu-An Chou who explained how, in an incomplete information scenario, the most regular decision results more appealing, because it contains elements of either extreme.
Think of a value ladder used in marketing or a simple offering. Companies should always offer three alternatives. At the movies, you can buy a small, regular or big soda. About 60% of people would pick the middle alternative. The middle alternative represents the core business of such companies.
The theory of prospect
In 1979, Econometrica (journal of the econometric society) published Prospect theory: an analysis of decision under risk by the two Israeli psychologists Daniel Kahneman and Amos Tversky.
As opposed to the rational decision-making model, they offered a more realistic key to reading based on empirical experiments of cognitive psychology. The latter studies the mental processes responsible to acquire, elaborate, memorize and eventually recover information.
The lottery dilemma, case A.
Think of being $300 richer. You must choose between:
A sure earning of $100;
50% chance of winning $200 and 50% chance of winning nothing.
The lottery dilemma, case B.
Think of being $500 richer. You must choose between:
A sure loss of $100;
50% chance of losing $0 and 50% chance of losing $200.
What alternatives did you choose?
According to Kahneman and Tversky’s research, 72% of people opt for the sure earning in case A (choice number 1). In case B, only 36% picks the same alternative.
In case A, the majority of people are risk-averse towards a potential profit. In case B, the same people are prone to risk towards a potential loss.
People perceive moderate losses almost double times more valuable than modest profits.
The two dilemmas are presented in different ways, but they share the same choice: $400 for sure or a lottery with equal possibility to win $500 or $300. According to the principle of invariance, we would expect people to choose the same alternative in both dilemmas.
The theory of prospect explains this phenomenon with three psychological aspects that affect decision-making:
Framing effect. During a decision-making process, people are influenced by their past and surrounding context. In particular, distinct dilemma formulations affect the perception of the starting point (or status quo) from which people evaluate their options;
Loss aversion. Most people are more motivated to avoid a loss than realizing a profit. For example, it’s easier to give up on a discount than accepting a price increment, even if there is no difference between the starting and final price;
Isolation effect. People are prone to isolate consecutive probabilities, instead of treating them together (see the next example). Afterwards they choose an alternative with the best utility value. Utility reveals a consumer’s preferences and, for this reason, is a matter of opinion. It’s not an objective variable.
It took me a while to understand the first part of the isolation effect. Let’s figure it out with an example.