Abstract: “When will it be done?” That is the first question your customers ask you once you start work for them. And, for the most part, it is the only thing they are interested in until you deliver. Whether your process is predictable or not is judged by the accuracy of your answer. Think about how many times you have been asked that question and think how many times you have been wrong. Now think about how much harder it is to answer that question when practicing Agile at scale. Your customers most likely feel like they have better odds of winning the lottery than they do of your next Agile project coming in on time. That you don't know your odds of success is not necessarily your fault. You have been taught to collect the wrong metrics, implement the wrong policies, and make the wrong decisions. Until now. This session will introduce how to utilize the basic metrics of flow to more effectively manage the uncertainty associated with very large scale software development. In it, we will discuss how to leverage the power of advanced analytics like Cumulative Flow Diagrams, Cycle Time Scatterplots, and Monte Carlo Simulations to drive predictability at all levels of the organization. Your customers demand better predictability. Isn’t it time you delivered?
Learning Outcomes: - A meaningful understanding of the basic metrics of flow (WIP, Cycle Time, Throughput)
- How to apply flow metrics at all levels of the organization
- How to visualize flow metrics in advanced analytics like Cumulative Flow Diagrams and Scatterplot
- How to interpret those analytics as guides for process intervention for predictability
