Power Kanban: Mastering project uncertainty through improved information awareness – Cuypers
Abstract:
In 2023, a Spanish region spent $276 million on new trains too big to fit in the tunnels, causing a major scandal. How could this happen? Intentional blindness is when we miss obvious information while working on a task. Our ability to focus comes at a price; the more we concentrate, the higher the likeliness of missing other information.
Psychologists Chabris and Simons conducted experiments showing a short film where two basketball teams make passes to one another. The viewers are instructed to count the number of passes. A person dressed in a gorilla suit walks through the scene, and although in plain view, most audience members are so engrossed that they fail to spot it.
Imagine the consequences of essential project information like problems, risks, decisions, opportunities, and solutions that are in plain sight getting overlooked by an entire team. The good news is that when people are warned, most do spot the gorilla. This is the principle behind PowerKanban: Our information awareness significantly improves by making a meta-data model of essential project information, triggering detections.
Creating a meta-data model acts as a pre-warning. While focusing on the necessary project tasks, you keep a keen eye on any monkeys passing through the scene, like dependencies, constraints, working assumptions, and prerequisites that require plans to be adapted based on emerging information, thus enhancing the chances of project success.
Using Kanban applications like JIRA, we can log, disseminate, and visualize this information across multiple boards and SCRUM teams. Sharing boards enables communication to build a shared picture essential for coordination between project teams. By keeping the team’s kanban boards up to date, there is no need for tedious status meetings or waiting for scrum-of-scrums to take place. PowerKanban is a generic technique made for scaling non-software projects.
PMI Talent Triangle: Power Skills
