I gave a talk recently about how I’ve been using data and analytics to guide my decisions in product management. I’ve edited the transcript a little and split it into bite-size parts for your entertainment. This bit is about expensive and risky assumptions (and why you should check them).
I was recently asked this question:
How would you recommend working with organisations who are used to a traditional / waterfall approach, transition towards agile / iterative development?
Here’s my response:
I was recently asked this question:
Can you make suggestions of how best to distil users’ wish lists of requirements/outcomes to a core handful that will encompass most people’s problems?
Here’s my answer:
I share my tips for beating writer’s block. In an article I used to beat writer’s block. How meta.
A talk I gave in November 2016 for Logi Analytics about why building products should be data-driven, and how to do it.
The interview covers things like:
thinking about outcomes, not outputs; alignment with broader goals; finding and measuring leading indicators; and the 5 most important metrics for product managers.
We have many product-minded people in the Government Digital Service (GDS) and across government, but we’re only just beginning to operate as a product community. I’m currently helping GDS out and have written a post for their blog on how we’re beginning to improve things.
There are several common dysfunctions plaguing product teams in B2B companies the world over. How can you stop them? Read on for suggestions.
Product-market fit is one of those concepts that seems relatively straightforward in theory but ends up being elusive in practice. But what does product-market fit actually look like when you get there?
On my arrival in Australia I was initially impressed by the slick service design of their automated SmartGate immigration process. Until I found myself back to having to fill in declaration cards with a pen, that is.
