This article is about changing the project performance paradigm from passive corrections to more active ones. The approach is based in behavioral and neuroscience, toward implementing behavioral project management practices to actively improve project outcomes, planning, and forecasting.
First, before we read on, we must consider the following:
- Bad planning + bad execution = high schedule/cost variance.
- Bad planning + good execution = medium schedule/cost variance.
- Good planning + bad execution = medium schedule/cost variance.
- Good planning + good execution = lower schedule/cost variance.
We cannot put together a bad plan and expect to fully recover that plan when the project starts. Meeting a project milestone is the product of two things: predict the execution outcome, then attempt to execute on that prediction.
However, in our project management discipline, we tend to see a lot of focus on what went wrong during the execution that caused the project to go awry. It is not just execution that is to blame, as the other half of meeting a milestone is how the milestone was placed on that date, to begin with.
Now let’s go a level deeper.
If predicting a project outcome (e.g., planning) determines the date and cost on which the project should land, and we are still failing our schedule and cost objectives 50 percent of the time, then why are project management methods not improving these outcomes?
This is the central question which I intend to answer.
Let’s first consider four measures that contribute to prediction accuracy (e.g., planning and forecasting accuracy):
- Visibility (passive). Planners and forecasters must be able to see what factors will impact their predictions, including the availability of resources, task obstacles, external controls, obscure risks, and predictable unknowns. Seeing these elements enables them to question optimistic and unrealistic plans and forecasts and correct their predictions.
- Feedback (passive). Forecasters and planners cannot improve on their predictions if they can’t see how those predictions ended up turning out. The more feedback they get on how accurate their plan was, and the more frequent that feedback is, the more chances they have to correct predictions and can start making adjustments in increasing their planning and forecasting (e.g., prediction) accuracy.
- Awareness (passive). Planners and forecasters, as well as all of the rest of us, have cognitive biases and some obscure thinking errors (especially in time-constrained environments) that significantly decrease our ability to predict project outcomes and plan our work realistically. However, these can be corrected. These biases and errors can be decreased simply by building bias and error awareness of them through training, and many planners will self-correct to a degree.
- Intentionality (active). This is the big one, and it consists of two parts. The first is actively and intentionally (versus passively) changing processes so that people default to making good project prediction, planning, and forecasting decisions by using methods such as Choice Architecture and coaching. The second is recognizing that people have intentionality in all their decisions, and their optimistic, risk-averse, loss-averse (etc.) intentions impact their planning and forecasting inputs into the plan (Eizakshiri et al., 2015).
Considering the active approach, we must intentionally improve project performance and recognize that passive measures rely only on a trust that we can coordinate or manage processes better and hope that everything works out (you might recall that hope is not a project management tool).
Passive measures to improving project performance are passive because:
- Visibility provides the opportunity to make the right prediction choice, and the planner/forecaster can or may not choose to use the information.
- Feedback gives the planner/forecaster information on how they performed, and they can or may not make corrections.
- Awareness of bias gives the planner/forecaster the chance to self-correct as much error as possible, but they can or may not self-correct.
Each one of these passive measures can improve planning and forecasting accuracy, but may not, depending on the choices and intentions of planner/forecasters. In project management, we tend to buy some tools, teach some method, and toss it in the ring and hope for the best. However, if we want to improve project outcomes significantly, prediction in project management must become a science we strive to excel at, especially now that we have the data to make it so.
The important thing to note here is that you need all three passive measures and the one active measure combined together in order to improve planning and forecasting, as well as project execution.
The most highly regarded planning and forecasting personnel are trained and competent in both technical methods and neuro/behavioral methods. They are, in a big way, holding a lot of the keys to whether a project succeeds or fails, and smart company executives recognize the behavioral planning and forecasting disciplines as the pivotal points of the project, and thus company success.
The big question is, do you want to continue to just passively try to improve project outcomes, or actively improve project outcomes?
Eizakshiri, F., Chan, P. W., & Emsley, M. W. (April 07, 2015). Where is intentionality in studying project delays?. International Journal of Managing Projects in Business, 8, 2, 349-367.
Josh Ramirez, PMP, MSM-PM, is a consultant at Evanclaer and is experienced in business operations management, project management, and project controls. He has worked at several national laboratories and other projects throughout the Department of Energy and is pursuing a Ph.D. in business psychology. He has a Masters’ degree in project management, is an adjunct professor of project management and conducts training courses that integrate the behavioral sciences with project management. Josh writes about culture and behavior, as well as Metrics and KPIs.