Example: Core Product Discovery Team
A cross-functional approach to Product Discovery is meant to include a wide variety of perspectives in the early stages where ideas are most flexible.
The Core Product Discovery team consists of the Product Manager, the Designer, a curious Engineer and a few others as needed.
This graphic shows a sampling of job roles that have participated in Product Discovery teams that I’ve facilitated.
For ongoing Product Discovery the group should have no more than 5 participants. With more than 5 people, it becomes too hard to schedule sessions. And in Product Discovery, everyone needs to be present. If a team member is missing, I just cancel the meeting. Trying to recap missing participants takes up too much in the next meeting and it’s a waste.
For one week Product Discovery Sprints, I will include up to 10 participants since everyone is locked in to attending all week. Above 10 people, it becomes too hard to share and participate. Since these Sprints are hands-on and based on participation, we limit the number to 10 folks.
Jim knows how to build successful teams and products from scratch.
He co-founded PowerReviews, a B2B2C product reviews SaaS platform, that had an exit in 2012 for $168 million at a 13x multiple. In the early days of the web, he product managed and architected one of the original ecommerce sites that had a $66 million IPO in 1999, online sporting goods retailer Fogdog.com.
For his Product teams, he’s created a curriculum and training program that pulls from his 20+ years of experience and the best minds in Product Management. In addition, he relies on his software engineering background and experience to bridge the gap between their Product and Engineering teams. He graduated from Stanford University with a degree in Computer Science.
Jim is based in San Francisco and works with clients from 2 to 20,000 employees in a variety of industries and business models. Previous clients include VSP Global, PagerDuty, Dictionary.com, and Hallmark. He’s also worked with startups in machine learning, API development, computer vision, payments and digital health.
