The theory, practice, and tools to help you discover high-impact products.
There’s a certain type of meme, often called “how to create a minimal viable product”, that’s been making the rounds in the product web for years. I must have seen at least 5 original versions and they all disagree with each other. Not very originally, I felt that they all missed the mark and decided […]
Skateboards, Cars, and the Return of Code-First Discovery Read More »
Why is product discovery — the practice of identifying the right things to build before switching to delivery — so hard to implement? In my previous article I described two systemic problems: must-have features and weak goals. In this article I’ll focus on three key challenges that the are down to the product org itself.
Many companies recognize it’s better to develop products through research, experimentation, and evidence-guided decisions, yet few are able to make product discovery truly work. While the concept has been around for a long time, implementation is often half-hearted, partial and ineffective. AI dev hype is making things worse. In this and the following artile I’ll
Marty Kagan and Elias Lieberich, just published an article titled “The Product Model at Google”. It’s a good article that gets many things right, but I think there’s also a more nuanced picture that’s worth talking about. I see Google as an example of a company that used to have one of the best product
The Product Operating Model at Google – A Critical View Read More »
Whenever I teach product discovery, someone will raise their hand and ask a variant of this question: “This feels slow. Wouldn’t it be faster to just launch it and see what happens?” The answer is No. If you skip product discovery you may get bits into production faster, but you’ll create value far slower. This
Generative AI is transforming product management, or so we’re told by AI companies and influencers. The vision appears to be all about output: The PM producing roadmaps, backlogs, PRDs, user stories, and prototypes faster than ever before. Some companies are accepting these claims as truth and pressuring their PMs to use AI, but in my
AI and Product Management: Becoming More Evidence-Guided Read More »
I regularly ask product people how they choose what to develop. Today, an increasingly popular answer is “we focus on the most important user problems”, or its more modern cousin “we prioritize opportunities”. Underlying these answers is a classic model that asserts that product development has to start with mapping out and prioritizing customer problems,
Product companies tend to manage the lifecycle of projects (AKA ideas) — from the moment the project/initiative is approved until it is shipped. But in a reality where most ideas fail to create value, it is far more important to manage the lifecycle of goals (what we’re attempting to achieve)— from the moment the goal
The Lifecycle of Goals: Research, Discover, Deliver, Monitor Read More »
When talking to product managers, company leaders, and customer-facing folk, a common belief surfaces: if enough customers (b2c), or an important customer (b2b) ask for something, then we should build it. This axiom is reflected in prioritization discussions as well as in many product management tools that rank ideas by “customer votes”. Customer feedback, whether it
This is an excerpt from my book, Evidence-Guided: Creating High Impact Products in the Face of Uncertainty. While the chapter references the GIST Model (Goals, Ideas, Steps, Tasks), the methods described can be used broadly. Switching to an evidence-guided mode of work is rarely easy. The people developing the product and influencing it have to
Adopting Evidence-Guided Development in Your Org Read More »