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Decision Tree Analysis

Decision tree analysis is not a scientific way to make decisions but rather a visual representation of the decision-making process that goes on inside the head of decision makers.

At first, a decision tree appears as a tree-like structure or graph with different nodes and branches. When you look a bit closer, you realize that it is the dissection of a problem or a situation in detail. It helps to clarify the decision-making process.

It starts with the statement of the problem or issue (root), then you gradually list the different decision choices (nodes), which lead to answers or results.

A decision tree provides a systematic map of a scenario and available options with a wide range of applications. Following are some of the advantages and reasons for using a decision tree diagram.

  • It helps resolve a problem by covering all the possible aspects.
  • It plays a crucial role in decision-making by helping weigh the pros and cons of different options as well as their impact.
  • No computation is needed, which makes the process universal to every sector.
  • These prediction tree diagrams can be used to represent all kinds of decision categories as well as continuous scenarios that can be tough to depict otherwise.
  • They can represent both quantitative as well as qualitative data in a visually appealing manner without applying much computation.

You Draw the Tree

Last week we looked at the complexity of decision making in a construction company that is pondering whether to bid a large and complex project. Let’s see what that decision looks like in a decision tree format.

Since decision tree analysis is a visual format, an interactive experience is the best teacher. Here is the step-by-step process of the complex decision-making process we discussed last week, and after you find a generic decision-making graph online, you can draw your first rudimentary tree of the step-by-step decision-making variables.

  • The decision tree starts with a single question: “Should we bid on this project?” From here, two branches emerge: Yes or No.
  • If “Yes,” further branches represent key factors to consider:
  • Size of the project (small, medium, large)
  • Complexity of the design (standard, moderate, highly complex)
  • Project location (local, out-of-town, remote)
  • Duration and timeline (short, medium, long)
  • Financial requirements (within budget, stretch, high risk)
  • Owner’s reputation (reliable, average, poor)
  • Company’s experience with similar work (yes, no)

Each of these branches split into more decision nodes—such as risk level of unfamiliar subcontractors, or the size of the project—allowing you to visually weigh the pros and cons, costs, risks, and probabilities for each path. The tree is followed until a “Go” or “No-go” (final decision) node is reached, selecting the most profitable or least risky project for the business.

Decision Tree Analysis is Visual Risk Management

The tree you drew should offer you a visual of the complexity of the project acquisition decision that construction people face every day.

The next step is to assign monetary values to the risk variables identified in the tree. By calculating the Expected Monetary Value (EMV) for each branch, it enables you to quantify risks, compare alternatives, and select the path that maximizes value or minimizes loss. Decision tree analysis, therefore, is nothing more than a step-by-step visual process that clarifies the complexity of project acquisition decisions and clarifies the comparative monetary impact of the project choices you make every day.

Step-by-Step

This management tool takes five steps.

  1. Define the Problem: Identify the decision that needs to be made.
  2. Structure the Tree: Map out all possible alternatives, including risks, threats, and opportunities.
  3. Assign Probabilities and Costs: Assign probabilities (must sum to 100%) to chance events and attach costs or revenue to each outcome.
  4. Calculate EMV: Work backward from right to left, multiplying outcome values by their probabilities to calculate the EMV for each node.
  5. Choose the Best Path: Select the decision path with the highest EMV.

 

Professional Business Management

I have devoted most of my career trying to communicate my belief that the missing link in the construction industry is the lack of professional business managers at the helm of former one-man startups that have grown into substantial industrial corporations. I believe that profit margins in our industry are far too low to compensate for the amount of financial risk we are required to shoulder, and that the only thing that will protect growing construction companies is an injection of professional business management.

Decision Tree Analysis is just one professional business management technique that will help improve profitability. This year we will be discussing many more.

For more information on decision trees, read more at: TREE

For a broader view of project selection, read more at: SELECTION

To receive the free weekly Construction Messages, ask questions, or make comments contact me at research@simplarfoundation.org.  

Please circulate this widely. It will benefit your constituents. This research is continuous and includes new information weekly as it becomes available. Thank you.