LATEST POSTS

Why Machine Learning Products Should be Managed Differently

BY Mark Barlow on January 17, 2020

Machine learning (ML) based products have particular characteristics and challenges, from data quality to counterfactual problems and explainability. What then are the implications of ML products for team structure, focus, and hiring? Data science jobs are increasing at around 30% year on year, and if you don’t already have a data scientist in your ranks […] Read more »

Ground Rules for Applying AI to Product Management

BY Patrick Tsao on January 6, 2020

The hype around artificial intelligence (AI) and machine learning has led to lots of jargon, so that this very powerful technique has become more difficult to understand. The tips below have all helped me, so I hope this article will help product managers to cut through the noise and better understand how AI can fit […] Read more »

Product Management and the Internet of Things

BY Jock Busuttil on May 2, 2014

April’s ProductTank London considered the question of how to manage devices in an increasingly interconnected world. Marc Abraham (@MAA1) brought us three great speakers to share their experience of the Internet of Things (IoT), product management and connected devices: Usman Haque (@uah) from Umbrellium; Yodit Stanton (@yoditstanton) from Opensensors.IO; and Patrick Bergel (@goodmachine) from Animal […] Read more »

Presenting Data—The Rabbit Hole Method

BY Simon Cast on August 23, 2011

Being a product manager in a data startup offers some interesting challenges. As more and more PMs work for data startups understanding these challenges will help PMs survive the strange world of data. There are two challenges that product managers in data startups face: Translating customer problems into analysis Presentation of data to customers Translation […] Read more »