Product managers working with data science teams on production applications have more challenges than with more deterministic (traditional) applications. These include providing more business/user context, not assuming that data will be predictive, and discussing accuracy requirements at the very start of a project.
Career paths for product folks are murky, with most of us falling into product management accidentally. Opportunities for advancement can be just as unclear. How do we think about product leadership roles, and how might we pursue them?
Wide-ranging conversation about product leadership, how product management has evolved, validation ahead of building, teleportation, scaling up product management teams, and working with non-product executives.
I talk with lots of senior individual contributors about the risks and challenges of moving “up the ladder” into product leadership roles. Here’s a survey I fielded to capture their top questions and concerns about getting promoted. What do product leaders do? How do product managers signal their interest in becoming one?
Industrial hardware and enterprise software are both great business, but have very economics, scorekeeping, and development models. To run a strong software business, we may need to retool some operating processes as well as executive assumptions.
There are some inherent mis-alignments among internal stakeholders that can complicate enterprise product planning and roadmapping. How do we understand these systematically instead of as personal confrontations?
Software is intangible: it doesn’t have weight or size or per-unit manufacturing costs. But if we’re in the software business, we have to assign units and prices that reflect our value to customers. And we should be mapping out pricing strategy before we start development, not the day before product launch.