People & Teams

Are you puzzled about why your estimate turned out wrong, or stressed from working to meet an impossible deadline? Some teams on inaccurately estimated projects suffer stress, burnout, and poor quality as pressure is applied to stick to an unrealistic schedule. Such project teams also descend into irrational decision-making—with potentially catastrophic consequences. Frustratingly, even when teams perform well, they are often judged by their failure to meet impossible deadlines. Andrew Brown will show how estimation errors are caused not just by new technology or intentionally manipulated estimations, but also from limitations in the way we think. Andrew will explain how cognitive biases contribute to estimation errors and show how to mitigate these biases. Learn how the planning fallacy, anchoring effect, and optimistic bias contribute to estimation errors and lead to irrational decision-making.

United Flight 232 should have crashed with all 296 lives lost. Asiana Flight 214 should not have crashed at all. But the reality is very different. Peter Varhol and Gerie Owen explain that the critical difference between the two flights was the interactions of their respective aircrews. United Flight 232 divided up responsibilities and worked as a team, using Aircrew Resource Management (ARM) to guide how the crew behaved during the flight, and especially in a crisis. Asiana Flight 214 deferred to the captain, neither communicating nor questioning his decisions in crisis. ARM helps cockpit crew members work together to best utilize the whole team’s skills to make flights safe. Using ARM principles, a testing team can bring their project safely home. The leader of a team is the final authority, but leaders must acknowledge team members’ knowledge and experience. This can make the difference between success and failure.

Sometimes we allow ourselves to drown in work… Mary Thorn hears it all the time: testers complaining at retrospectives to their teams that they do not have enough time to test everything. She often sees testers work overtime the last week of a sprint to ensure the definition of done is accomplished. Why do they do this? Why do we, as testers, enable the bad behaviors of “Scrummerfall” or a lack of whole-team ownership of quality? Mary aims to arm testers with techniques that allow them to test smarter, not harder, and enable the testers and the team to have better conversations that make it clear what they are testing in the sprint. Most importantly, she wants you to come out of her session being able to answer the question, “What are you not going to test this sprint?” Take home some approaches that allow you to swim, not sink, by focusing your own and your team’s efforts.

Ashwin Desai has faced the daunting challenge of using measurements and metrics to assess and improve product quality through process change. Join him as he shares what he learned on the journey to move the sports technology firm Hudl from a reactive approach to quality to quantitative, data driven, proactive means to improve product quality. Just as Hudl itself provides the ability for coaches and teams to analyze and improve their performance based on data, they wanted to move the teams building Hudl to use the same approach to improve quality. Ashwin shares how they selected measurements, the work agile teams completed to get buy-in for the measurements, and how the data was normalized to provide understanding of the quality of each initiative and the variance between them.