How to close the gap between discovery and delivery | Jenny Martin

Jenny Martin is a collaboration coach and the author of Oopsie. She spent 25 years leading software delivery teams before setting up her own training company in 2011, and now focuses on the people side of product development: psychological safety, learning design, facilitation and Lego Serious Play. Oopsie is a framework she first developed a decade ago to keep teams aligned on outcomes. It has since been picked up by a major US client of Jeff Patton, a global consultancy and a large tech company. Jenny joins Randy Silver to explain how it works.

Key takeaways
— Oopsie exists to balance thinking with doing. It gives teams enough collaboration at the right moment to build the right thing, without the analysis paralysis of the waterfall era.
— The Asteroids metaphor explains the method. Break down only the big chunk in front of you and leave the rest unexplored. Blow everything up at once and you get overwhelmed by thousands of tiny, fast-moving pieces.
— An outcome is a change in the real world that creates value for someone, usually a customer, internal or external. A number on a spreadsheet is not an outcome, though it should connect to one through a chain of whys.
— Outputs are not what the team produces. They are what a user or system visibly delivers along the way, such as a payslip or a set of search results. Roughly 20% of them deliver 80% of the value, so this layer is where teams prioritise.
— The process layer is the set of interactions that generates each output, and it maps closely to a well-sized user story. Working down from outcomes and outputs gives teams vertical slices without exploring every asteroid first.
— Scenarios and inputs borrow from behaviour-driven development and specification by example. They suit deterministic systems where there is one right answer. AI evals handle the qualitative, non-deterministic cases, and teams will need both.
— Concrete test data surfaces hidden assumptions early. On a retail project, Jenny’s team showed a customer the exact data they planned to test with, and the customer spotted a flawed assumption that would have cost three or four months of work.
— Most teams struggle with the outcomes layer. Jenny sees it as the biggest risk now that AI lets teams move fast in the wrong direction.

Chapters
00:00 Introduction
00:57 Where Oopsie came from
01:34 Who is the collaboration coach?
03:26 The problem Oopsie solves
05:52 The Asteroids metaphor
09:16 Joining up discovery and delivery
13:09 Using Oopsie at team and company level
15:46 Outcomes
19:37 Outputs
24:30 Process
28:44 Scenarios and AI evals
33:06 Inputs
34:53 Why examples matter at every layer
37:43 What teams get wrong
39:52 Wrap-up Receive SMS online on sms24.me

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