Measuring decision-making improvement. Part 1 — resources.

What does it mean to improve the decision-making process? Let’s break this down and become a more aware decision-maker.

One can find a lot of information about decision-making and how to improve the process. We wanted to structure some of this information and decided to start with an important question — What are we actually improving? And later it would be good to know how to measure the improvement, right?

Decision-making can take various forms, from a simple selection of two alternatives to complex analysis and definition of innovative solutions. The same approach cannot be copy-pasted every time a decision needs to be made. However, decision-making is a process, and as such, can be improved. But there should be a measurement for this.

Process optimization theory defines various measurements. Those typically used define improvement as:

• the process consumes fewer resources on its input
• the quality of the final product is increased (due to the use of improved methods)
• or both, which is the ideal case

OK, so it is resources and quality. What does it mean in decision-making? Let’s break down these components, we will start from the input side.

Time

The decision-making process consumes several types of resources. First, it is time. It is probably the most precious resource as it cannot be recovered, stored for later, or borrowed from elsewhere.

Measuring the time used to make a decision should include not only the length of the process but also the number of people included. In the end, if two persons are thinking about something for an entire day, two working-days are consumed in total.

Another important addition to measuring time is the cost of missed opportunities. In legislation, there is a term describing ceased profits — lost profits resulting from damage, destruction (…) of productive assets. Time is definitely a productive asset. If we are wasting it, we are potentially missing opportunities that we could achieve otherwise. Spending two days thinking about a decision that could take only a single day, in a monetary value, means not only wasting one day of salary but also wasting profits that could be produced during that day.

How time is related to the final quality of the decision? More time is better, but it is not a simple linear relation. At the beginning of the process, quality grows, but later the growth is weaker until a certain threshold, where more time will not add additional quality. In worst-case scenarios, the quality can even decline. This happens when we believe adding more analysis will help us make the best decision, but instead, we feel overwhelmed and confused with added information. This usually ends by picking an option that felt right at the very beginning of the process or a deadlock and no decision at all.

After a certain point, we are just losing time — thinking and analyzing but not adding any quality to the final decision or even decreasing it.

Information

Information, or knowledge, is the second resource the decision-making process requires. No matter how long we think, if we have no information input, we will not be able to decide. In fact, the lengthy time is usually the effect of analyzing information and turning it into knowledge.

We need information at every stage of decision-making: definition of the problem, brainstorming viable solutions, and evaluating them. Here the correlation to quality is similar to the case of time — the more, the better. It looks like a logarithmic function — the quality of the decision grows rapidly with the new information we have, but later the growth rate slows down. The reason is simple. More information requires more analysis. We tend to analyze simple and available information first. These are structured data that require minimal interpretation — numbers like sales results, percentages, or basic opinions (recommended; not recommended). But most data around us is unstructured, which means it requires prior categorization and interpretation. The more information we invite to the equation, the more effort it will take to analyze. And more chances to commit a mistake! Also, more information means more costs — in time, if we only need to analyze it or in money, if we need to source it externally.

Decision-making is a lot about the comparison of alternatives. The more variables and unstructured data we analyze, the less possible they will be to compare. The classic example is — I like the color of this cloth, but the other will keep me warmer in cold weather. Color and the ability to keep temperature cannot be simply compared. So, we need to invite other variables that will assign importance to both scales, another to evaluate the importance, etc. until the problem becomes too complex to solve.

We can clearly see the Pareto rule — where (approximately) 80% of the final decision quality relies on 20% of the most important data. On the other hand, adding 80% more data will increase the quality by just 20%.

How to measure it?

From the above introduction we know that to optimize, our decision-making process should:

• not take more time than it is necessary to make the decision
• to analyze only the information that is sufficient to achieve satisfactory decision quality

Very often cost-benefit analysis is used to evaluate alternative decisions and define the best solution. Why not use this technique to evaluate the process that led to these decisions. Time is a cost, information is also a cost, and a good quality decision would be the benefit. And there is a simple way to perform the analysis.

Follow these steps:

1. Draft a simple plan for your decision-making process

Who would you involve in the process, how long will it take, and what information you need?

2. Estimate the value of the decision

We can always estimate how much is the decision worth. If it is a new strategy that will assure more clients, or opening a branch in a new region, or simply cutting the cost — it is always worth money.

3. Calculate the value of the time you think the process will take

man-days + lost opportunities = time value

If you cannot predict what could be lost opportunities, there is a simple approximation. Just double the time. Why? If you invite your financial analyst for a day to participate in a decision-making exercise, you pay the person daily wage, but they are not doing a regular job. The job needs to be done, so the person will require an extra day to finish it. The simplified equation is:

2*man-days = time value

4. Calculate the value of the information

internal information + external information = information value

Now, the cost of external information is the easiest to estimate. It is what you pay for research or analysis purchased from thematic institutions or subject matter experts. Cost of internal information can be approximated as the time an employee requires to present the data:

(man-days to source data + man-days to analyze data)
 = cost of internal information

5. Compare the costs of the process and decision value

time value + information value   VS.   decision value

There is no golden point to this equation. Common sense is that the value of a decision should be much higher than the costs of making that decision. If this is not the case, there is something wrong with your process.

6. Rethink the process!

Decision-making is a process like any other in your business. In the best-case scenario, it will cost you time. In the worst-case scenario, the wrong decision will cost you a failure. So, plan it correctly — this is the key message that we wanted to pass in this article. At least, planning should include the following:

• Objectives— what are we trying to achieve. These are the values that will be used to evaluate alternatives.
• Decision stakeholders — who should be involved in the process. Group people or groups of people by their roles: information and knowledge source; those that will analyze and prepare recommendations; who should evaluate them; all the people that need to be informed about the decision; and finally (and this is most often omitted group in the communication) people that will be affected by the decision.
• Information needs— this includes data sources, information, and knowledge that will be used to produce recommendations and evaluate them.
• Methods — used to gather data, analyze it, and evaluate. Depending on the decision character and data type this can vary from brainstorming exercises or surveys that include lots of employees to statistical analysis of numerical data.
• Decision implementation plans — communication, execution, and evaluation of the decision. Each decision is the beginning of a process. Even the best decision can fail in its implementation if it is not well prepared.

Part 2 will focus on measuring the quality of the decision — coming soon.

Meanwhile, if any of the challenges described in this article seem familiar to you visit the DecideX Consulting website or contact us to learn how we can help you make better decisions.