With all the talk of prioritization frameworks, product analytics, and the like, one would think by now that product roadmaps could be self-discovered and automatically planned with ML-powered technology.

As those who follow me on LinkedIn know, I’ve been spending a lot of time lately with B2B SaaS companies focused on value. Outcome-driven product management focuses on the key jobs to be done and their associated pain points and desired outcomes.

B2B SaaS Chief Product Officers (CPO) have embraced the “outcome over output” mantra. That is, outcomes are desired results the buyer or company wants to attain. Outputs are actions taken or items delivered that contribute to attaining outcomes.

I came across the term Minimal Viable Demo (MVD) when I read a blog written by my former Purdue graduate school classmate and CTO of Juniper Networks Raj Yavatkar. In his post, Raj offers great insights about being an effective CTO.

Recently, I have been spending time with product teams whose “products” are internal systems. I define an internal system to be software that supports some internal business, administrative, or other process (e.g., internal communications, manufacturing, finance, etc.)

In previous posts, I have discussed the Five Product Movements Models (5PMM), a SaaS product management life cycle model. It consists of an organic, iterative, and mutually informing series of five Movements (Strategy, Planning, Development, Marketing, and Operations).

The board of directors of a company should be focused on the strategy of the company, including value creation and value capture against desired company outcomes. 

These days, product teams are obsessed with customer-centric outcomes and outcome-driven product roadmaps. I align with that perspective. I have been spending a great deal of time working with B2B SaaS companies on customer discovery.