Basic Decision Analysis and Modeling

Factoring in Decisions and Outcomes

A process map engages stakeholders to visualize and quickly understand what a process does, showing its steps as boxes connected by arrows. An arrow pointing to a box triggers the step, and an arrow coming out of a box indicates the step’s outcome.  A step can have more than one outcome, depending on what happened in it. For example, a step could have an expected outcome and a different one if something goes wrong in the step.

Sometimes a process step includes a decision with many outcomes based on one or more factors. The sketch diagram below shows a lead qualification activity with six possible outcomes:

Two factors determine the qualification decision: the lead’s interest level and purchase timeframe, each having three values.

Interest Level	Timeframe
Informational (cool) Interested (warm) Ready to purchase (hot)	None More than a year Less than a year (urgent)

The decision factors have nine combinations of values: 3 Levels of Interest x 3 Timeframe values.

Growing a Decision Tree

What’s the decision process to arrive at one of the six lead qualification outcomes from the nine possible factor values? A process map can show it as a decision tree:

The decision tree takes a lot of vertical space to show all possible outcomes. It repeats the “Evaluate timeframe” activity three times, once for each Interest Level value. If the process adds another Interest Level value, the tree gets another “Evaluate timeframe” activity connected to three more results taking even more diagram space.  

Adding another decision factor multiplies the number of outcomes by the number of values in the new factor.  For instance, adding a “yes/no” factor doubles the number of results in the decision tree from nine to eighteen. Decision trees work well with fewer than eight outcomes but require a lot of space to scale up, making them hard to fit on a screen.

Building a Compact Table from the Tree

The arrows connected to the “Evaluate timeframe” activities in the decision tree represent all decision factor values. These values can form a table, with the Timeframe factor values as column headings and the Interest Level values labeling the table rows. Abbreviating the outcomes produces a compact table:

	Timeframe
Interest Level	None	More than a year	Less than a year
Informational	Discard	Drip campaign	Email check-in
Interested	Qualification call	Qualification call	Sales call
Ready to purchase	Qualification call	Sales call	Schedule presentation

This matrix table works OK for a decision with only two factors, but decisions often have more factors than that. How can a table contain three or more factors in only two spatial dimensions?

Exploring New Dimensions

A basic decision table can show multiple factors, with each one in a column. The table also has one column for the outcome. Here are the lead qualification outcomes in an expandable table:

Interest Level	Timeframe	Lead Disposition (outcome)
Informational	None	Discard lead.
	More than a year	Send to a drip campaign.
	Less than a year	Check-in via email.
Interested	None	Call for further qualification.
	More than a year	Call for further qualification.
	Less than a year	Assign sales rep to call.
Ready to purchase	None	Call for further qualification.
	More than a year	Assign sales rep to call.
	Less than a year	Schedule presentation.

Adding another decision factor involves inserting a new column for the factor and duplicating all rows except the heading to accommodate all possible values of the factors, including the new one. A spreadsheet makes the duplication process very easy by copying rows and pasting them multiple times.

Setting the Decision Table

A decision tree or table ensures that the process covers all possible outcomes. Without a tree or table, a stakeholder could overlook or make an incorrect assumption about a result, leading to questions from the development team at best or unexpected behavior from the solution at worst.

A decision tree diagram illustrates the path to each outcome, working well with less than eight outcomes. With more outcomes, a decision tree becomes hard to follow and fit on a screen.

A basic decision table shows all combinations of factor values and their resulting outcomes. The table has a more compact format than a decision tree. 

Putting a decision table into a spreadsheet with filters makes it easier to look at a few factor values at a time. For example, management stakeholders only care about leads with “Interested” or higher Interest Level with a specified Timeframe. That reduces the table to show four outcomes:

Interest Level = Interested or Ready to purchase	Timeframe not = None	Lead Disposition (outcome)
Interested	More than a year	Call for further qualification.
	Less than a year	Assign sales rep to call.
Ready to purchase	More than a year	Assign sales rep to call.
	Less than a year	Schedule presentation.

A complex decision with many factors could have hundreds of rows to cover all possible scenarios. Filtering the rows for specific factor values enables stakeholders to zoom in on the factors that interest them.

Decision trees and tables show all possible outcomes of a decision, ensuring coverage of every scenario.