Here is the slide deck and video presentation from an online talk delivered at the Business Agility Gauteng meetup on 16 July 2020.
In this article, I’ll use a simple, easily accessible example feature to show how a feature hypothesis should evolve and how monitoring results can impact our plan and backlog priorities.
I am going to stick with the “Password Reset” example from the previous article in this “Outcomes versus Outputs” series since resetting one’s own password can be applied to almost any website and application. Continue reading “Every Feature Needs a Hypothesis”
Outcome versus Output
My very simple definition of the difference between output and outcome is:
- Output is delivering volume
- Outcome is delivering value
Theoretically, they could be the same but in practice this is seldom the case.
I can create a lot of ‘stuff’ (i.e. output) but realise very little, or even negative, value for all the time and effort spent producing said ‘stuff’. This article provides two practical examples of what normally happens (we focus only the output), why this is a terrible practice and the problems associated with ignoring the outcomes. Continue reading “Outcomes: The Forgotten Test Case”
Ron Kohavi was the Technical Fellow and VP of the Analysis & Experimentation team at Microsoft. He had a team of brilliant engineers, data scientists and program managers working under him. Kohavi’s team built Microsoft’s “Experimentation Platform.” Before the Experimentation Platform was in use, Microsoft teams were delivering well-thought out features, some small, others larger multi-month projects. Output was great – and Microsoft products like Bing, Edge, Exchange, Office, Skype, Windows, and Xbox were benefitting from the exceptional work produced.
Or were they?
One of the improvements SAFe version 4.5 introduced was incorporating practices from “The Lean Startup” into the framework – specifically the use of benefit hypothesis statements into features and epics. This is a story of how well this worked for us. Continue reading “The Power of Feature Hypotheses”