Balancing Your Bias

Everyone has a bias.  A bias is generally understood as a preconceived position on a subject often viewed as unreasoned by others.  The reality is the bias is generally not developed through unreasoned mental programming, but rather built out of causal reasoning.  Our experiences in our own life are the anecdotal evidence for much of the judgements we make during the day.  Sugar flakes will be sweet.  Potato chips will be salty.  Some people’s causal reasoning has them jumping the train tracks and believing that there’s floating spoons on mars.

In projects qualitative risk analysis and reliance on expert judgment can also lead to false conclusions.  A project manager with a short list of failures may believe he can will project success simply by forceful demands.  I’ve also seen PMs who grossly misinterpret the difference between a minor risk and a slightly higher risk.  In this situation they exaggerated the difference to the point where they felt the project was in severe jeopardy.  This lead to more worry and significantly lowered the productivity of the team.  

One way to balance a bias is with quantifiable information.  In the case of the PM who over exaggerated risk we were able to show him that the chances while still higher than the norm he was used to were so unlikely that it was a nearly negligible increase.  Using the hard data was only part of the equation.  Communicating the data in a way that allows the PM to be corrected while still saving face is also important.  Publicly disempowering a PM may create a dramatic situation that functions as a hand grenade to product progress.  Sometimes it makes sense to just leave a Lenore Skenazy quote on their desk and walk away.  “All the worry in the world doesn’t prevent death. It prevents life.”

Charting the Project Ocean

Navigating the risky waters of a project requires the same tools that helped navigators travel across the ocean, good charts.  In this post I review the usefulness of using tables and charts in communicating project risk.  Two common types of charts used in communicating about projects are Pareto diagrams and Probability & Impact Matrix.  Risk in projects occurs in some combination of four interconnected areas, Project Scope, Budget, Schedule, or Resources.

It’s important first to understand that scope, budget, schedule and resources are all interconnected.  One way to look at these is to consider them as parts of the same object.  If scope increases so will the budget and the schedule for the project.  Similarly, if any of the others increase it will affect the other three.

Scope is one of the more difficult things to chart because it may not include all of the project’s requirements.  The requirements it does capture can be charted and both the Pareto Diagram and Risk Probability & Impact Matrix can be useful in visualizing and communicating about the project’s risk.  

The Probability & Impact Matrix visualizes information based upon two scores, the probability and the impact.  These scores can be recorded qualitatively or quantitatively.  The PMBOK recommends qualitative analysis prior to a quantitative analysis.  When used as a qualitative tool this matrix’s inputs are usually in the form of rough descriptions.  When used quantitatively the descriptions of the risk become matched with a numeric value based upon their likelihood and severity.

Whether used qualitatively or quantitatively this matrix can be useful to identify parts of a project’s scope that communicates risk.  The process of building this matrix forces those involved to have a thoughtful conversation about different aspects of the project without worrying immediately about which risk is more prominent than another.  Because of the simplicity of its design this communication tool requires very little training for teams to discuss and build.  Similarly it requires very little explanation for the audience who it will be presented to.

Pareto Diagrams are solely quantitative.  Its input requires a dataset comprised of a frequency or similar sets of values.  This dataset must be arranged in descending order from largest to smallest.  Once the data is organized in this way, each datapoint must be calculated as part of its contribution to the whole.  The Pareto Principle is based on the philosophy “that roughly 80% of the effects come from 20% of the causes.”  So the goal is to find where the 80% mark lies on any given dataset.

If used to analyze risks in a project’s scope the Pareto Diagram can quickly focus the group on the largest 20% (known as the vital few) and monitor, but not be distracted by the trivial many.  The Pareto Principle requires a valid dataset and an audience familiar with the principle and the format.

Any project is likely to hit some rough seas and choppy waters.  Good charts can be crucial in helping the team navigating past them and safely arrive at the intended destination.