A Simple Method for Smarter Decision Making

Humans, like you and me, make decisions every day, however small or large. In today’s world with numerous options and factors, it becomes more important to make decisions in a methodical way rather than relying on our “gut feeling”. In fact, some decisions we make require deep thinking due to potential consequences and irreversibility (“you can’t unring a bell” once you make certain decisions). Beyond the two important factors, we may have limited and dynamic contextual information that can easily overwhelm us.

To make structured, analytical decisions, we can leverage a very simple yet powerful tool known as Multi-Criteria Decision Matrix, as described in the book, “Psychology of Intelligence Analysis”, by a former CIA veteran Richards J. Heuer, Jr.. Before I introduce it, let’s understand the problem context to which it is most relevant.

Problem: Buying a house is complicated

Let us imagine the following scenario; let’s say we would like to buy a house. There are many factors involved in buying the house: obviously its price, square footage, where it is located (e.g., close to or far from work?), the crime levels in the surrounding neighborhood, quality of the building, future maintenance fees, and so on.

We often buy the houses with our partners, and that can lead to conflicting preferences. For example, what is more important: having a backyard, but paying more, or perhaps vice versa? There is no “right” or “wrong” decision, just different set of consequences (higher vs lower price; there is a backyard vs there is none).

Buying a house, in general, is a high-stakes situation due to the amount of money that we need to spend. We also often consider how long we are going to live at that place, along with “investment” opportunities, as in how much it is going to appreciate or depreciate over the next decade.

In short, it is a complicated and stressful process that takes weeks, if not months. However, there is a way to simplify it by approaching the process from the analytical mindset.

Solution: Multi-criteria Decision Matrix

The essence of making a good decision is to gather and structure available information at hand (the known knowns). Humans are not good at holding a lot of information at the same time in their head. Thus, we need to externalize the information onto a visible form, such as an A4 paper. In addition to the externalization, we break down complex information into its simpler constituents.

One way to externalize and break down the information in a structured way is known as Multi-Criteria Decision Matrix (MCDM). It is a hands-on, paper-based method for making a decision that considers multiple constraints (criteria). Let’s see how it applies to the housing purchase situation above.

First, we come up with a list of attributes, such as:

• Location
• Price
• Square footage
• Estimated maintenance costs
• Whether there is a garden or not
• etc.

Next, we both assign relative importance to each of the attributes:

The ranked list of attributes helps focus on what matters most and leave out things that do not matter. For example, is garden really important to us or can we live without it? Are we okay with paying more but get a better location, or vice versa, get a house further away but for a cheaper price? Should we include Maintenance in the Price attribute rather than keeping it separate? Hence, we can now make a more structured decision on what matters to us before searching for a house. On top of that, we will immediately notice the difference in our preferences and that of our partners, be able to quantify that difference, and discuss it in detail.

Now that we have visited a few houses, we are ready to apply the structured analytical method to make a decision. You now need to quantify each house’s “score”: distribute (imaginary) 100 points among the options we have. For example, in the table below, House A gets 50, House B gets 10 and House C gets 40 points for the same Location attribute. Simply put, we liked House A the most, and House C is close enough to it, but we did not like House B as much; all in terms of the “goodness” of location.

Having split 100 points across our options for each attribute, we can now calculate the total score by multiplying the %-ge importance by the score of the house and sum it up:

Voila! In the table above, House A is the winner with total of 36 points. House B and C have the same total scores despite scoring wildly differently in some attributes, such as Location and Price. Note that the points themselves only matter in relative terms, i.e., what house is better than another and by how much.

We can also compare each of our results with our partners (if done separately). The separate result will show the difference in both of our preferences and help re-evaluate houses in case there is a vast difference between our results.

You can extend the matrix and do sensitivity analysis to determine how much change in one attribute’s score can swing our decision from one house to another. For example, we can calculate the amount that the House B’s price has to go down for us to make it our primary choice rather than House A. This kind of add-on can help us understand how sensitive our choices are (firm on one option vs being open to consideration of alternatives).

Conclusion

In summary, we broke down a problem (“buying a house”) into smaller sub-problems (attributes & their relative importances for each option) and externalized it onto a paper. These steps helped us evaluate and rank the options, and ultimately make a decision.

Multi-Criteria Decision Matrix is one among many approaches to structured, analytical decision making. It can be applied anywhere where the stakes are high and a good enough decision has to be made, whether at home, in our career, in relationships, or elsewhere. I highly recommend to read Richard Heuer’s book, as it is packed with valuable and insightful information on how to effectively make sense of a vast amount of information in today’s world.

References

• Heuer, Richards J. Psychology of intelligence analysis. Center for the Study of Intelligence, 1999.