Minimum Viable Product (MVP) is one of the most misunderstood, misused, and abused terms in contemporary software development. In this talk, Jeff Patton explains the misunderstandings made by thought leaders that lead to the confusion we all deal with today. You will learn the counter-intuitive concepts hidden in the term and why really using them is so hard.
This video will provide you with practical techniques on how to build a powerful roadmap for your product or service, one that allows any Agile organization to get valuable feedback from their customers and deliver business value.
Your product roadmap can basically set your life course as a designer/researcher so why is it so often that user feedback can get lost in the discussion over “Feasibility” of implementation. Without a clear roadmap, research and design can often not have the lead time needed for activities. This leads to a state of forever catching up and being reactionary.
Shifting responsibilities from a “command and control” organization towards self-organized teams is not easy. In her article “Managing Product Teams for Success”, Teresa Torres discusses the challenges that you face when you try manage product teams by outcomes.
This talks discusses 7 deadly sins of software development, specifically relevant for Agile teams. It’s pretty clear when you fail as a start-up, where you and your friend invested last savings. The product is not ready or just doesn’t get sold, the money’s gone, you open LinkedIn to search for a job suitable for an “experienced software engineer with entrepreneurial background”. It is way more tricky in a big company with a well-established product.
If some consider Scrum as an Agile project management framework, many people consider that is is more a product management approach. Anyway, Scrum is about understanding the need of the customers to deliver value. In this context, the concept of “personas” can be used to support user-centered design throughout a product development cycle by focusing on the characteristics of key user segments.
Running an experiment is trivial: Make a change and see what happens. Running experiments at scale, however, is a different story. It is not trivial to simultaneously run hundreds of experiments across 100 million users. It’s not trivial to cover dozens of platforms and markets while staying on top of the technical and methodological complexities.