Solve Just Enough Of Your Worst Problem
This session can run as a public conference tutorial or as a private in-house training session.
Many change campaigns fail because we don’t see the results we expected from the change. We can attribute this failure to a variety of issues: attempting to solve the wrong problem, attempting to solve the right problem with the wrong skills, or failing to measure progress towards solving the problem. Most organizations overlook a key possibility: wasting time solving too much of the right problem.
Voltaire once said that the perfect is the enemy of the good, and that principle applies here. While we find it comforting to completely solve a well-understood problem, we sometimes spend weeks or months continuing to solve a problem even though another has risen to the level of the most immediate problem. While you tweak your build to perfection, you might forget that it still takes two weeks to deliver upgrades to your customer, or that your customer needs a month to install the upgrade. Stop wasting time solving a problem when you’ve already solved it enough.
In this session, J. B. Rainsberger introduces concepts from the Theory of Constraints and Lean Software Development to help attendees uncover their biggest problems, and decide how much of that problem to solve before another biggest problem takes its place. From there, we work together to formulate a plan to solve just enough of your worst problem.
This session includes An introduction to Agile Through the Theory of Constraints in a full day tutorial aimed at people who want to explore their software delivery system for problems and solutions.
- Understand how to uncover your biggest problem by identifying productive and wasteful activities.
- Formulate a plan to solve just enough of your biggest problem.
- Walk away with a deep understanding of the various activities that contribute to the time it takes for you to deliver features once they’ve been requested.
Please inquire about booking this session by emailing the address at the top of this page.