Decision tree's are one of the core
Business Analysis techniques, showing up as part of section 9.8 (Decision Analysis) of the BABOK Guide v2.0. As with so many business analysis techniques, how you define it seems to depend on who you ask; as I have come across all of the following definitions for a decision tree:
And there are probably other definitions I have not come across yet. The key take-way is that decision trees are a model of the decisions and options to be taken to reach a specific answer (or decision).
As is also common with widely used modeling techniques, there are a number of symbols that are used by different authors. But in general, decision trees are made up of the following elements:
According to the Principles of Management
, the primary purpose of a decision tree is to have a defined set of rules that allow you to explain the conclusions drawn from the decision tree.[3] But they are also an easily understandable way to represent the possible options and results that could come from a decision. In general I see them used for three different purposes. Those are:
Business Analyst's are most likely to use them when presenting solution options to decision makers or when diagramming the logic to be automated in an application.
In the example below I will show how to build a simple decision tree that evaluates the options (in a very simplified way) for making a decision to replace the current Sales CRM (client-relationship management) application with a newer, more efficient option. And yes, I know the figures below are wildly unrealistic. {grin} They are simply used for illustrative purposes.
Decision Tree's are read from left to right, so the first step is to place the root decision node on the left.
The next step is to add the four choices that have been defined as possible project solutions. They are a cloud-based hosted CRM (we'll call it SalesForce as an example); an installed in-house CRM (we'll call it Siebel as an example); a custom in-house built CRM (that we'll call Our CRM as an example) that heavily intregrates with existing systems for maximum benefit and tailoring to our existing sales process; and doing nothing. So we add the four options to the diagram.
As part of the evaluation we are going to include estimated figures we have on the following decision points:
We are also going to explore a couple of options for the two COTS packages.
SalesForcewe are going to consider a
Basicpackage with just the core features (which can be upgraded later) and a
Fullpackage with additional components.
Siebelwe are going to consider a
Coreapplication with just the core CRM module and another scenario where in addition to the core CRM functions we are adding in 3 enhancement modules (for example, for improved lead dissemination, a meeting scheduler, and an improved analytics module).
Our CRMwe are going to include all the features our Sales department has identified that they want. This is the
dream system.
So for step 3 we are going to add "column" labels to the top of the diagram, and then extend the model to include the options discussed above. This results in a diagram that looks roughly like this:
For the next step, we are going to add the estimates we have for the estimated annual cost for each option (maintenance and licensing) and the estimated sales increase that we expect over a 5 year period based on the functionality that will be deployed to the sales team.
The numbers are totally made up, the idea is that your analysis might find that:
SalesForceoption is the least expensive to purchase and run, but the least customizable both now and in the future. While you may get the benefit of future upgrades immediately, they may not always be suitable for your Sales process. So while expected to improve your Sales results, you may not get as much benefit as you could from a more customizable solution.
Siebeloption is the next higher in cost as it is locally installed and requires dedicated servers and support staff. But because it is locally installed and managed, there are much greater options for customization (within limits) to best impact your Sales process. It will require additional training of your maintenance and support staff, so it has a higher yearly cost as well.
Our CRMoption has the massive upfront cost of development. But because you don't have to pay regular license fees, it can run in on existing hardware, and all the expertise will be built up in house, in has the lowest yearly cost option (not much more than the current annual costs).
When all of this is folded into the diagram it looks like this:
For the beneficial value column (and Net Profit column for a few items) I am including the idea of probabilities in this diagram. You use these to show the best probability that a result will occur.
In the last step we finish up the diagram by calculating the resulting values. The final value is calculated by adding or multiplying as necessary. So the very top value is calculated based on this formula: (-$250,000 + -$140,000) + $2,000,000 + *80% * $100,000) = $1,130,000.
The diagram above in Step 6 represents an example of a business choice decision tree.
An example of a simple decision tree that shows the logic for a web site login process might look like the diagram below. Note that there are no uncontrolled steps in this decision tree: