How should we define MVP?

A million dollar question every product manager faces, “how should I define Minimum Viable Product (MVP)?” As a PM, I always like to think about how can I design my product so that I can make it Most Valuable Product with minimum efforts?

I face following questions when I think about MVP every time:

  • There is a higher bar for quality now than ever before. It means I can not compromise on quality and performance. If that is the case how should I consider quality, performance and all functional requirements in a given timeframe?
  • Dictionary meaning of ‘Viable means: capable of working successfully; feasible. But what does ‘Viable’ means in MVP? Is its development cost, is it possible to build the product or is it usage by customers?
  • What are the essential requirements should I consider?
  • Is there a way I can capture customer feedback before I build MVP?

Continue reading “How should we define MVP?”

Connect before you build and Connect before you lead

Every individual in an organization has a different motivating factor. As a product manager, we deal with engineering, professional services, support, training, documentation, and QA. Thus it is crucial to comprehend common ground to understand motivating factor among people with different attitude, behavior, values, and culture. Product manager’s job is high touchpoint job, and it touches every department in the organization. Thus, I firmly believe key to the success of this role is to connect before you build and to connect before you lead.

Continue reading “Connect before you build and Connect before you lead”

Machine Learning/AI/Big Data Products – Whether to Ship or to Learn is the Question?

Google displays personalized search suggestions, Netflix populates recommendations for shows, and Amazon provides products you may like widget are notable examples of machine learning or big data products. These product features will not show accurate results until algorithm understand end-user pattern. Therefore, the fundamental question for machine learning/AI/Big Data product managers is whether to ship or to learn?

Continue reading “Machine Learning/AI/Big Data Products – Whether to Ship or to Learn is the Question?”