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.
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.
It’s easy for CEOs to think that they personally are the best-informed people within their companies about what customers need and what markets want. In reality, product and design teams have the time, focus, expertise, and large numbers of non-selling interviews to do more objective validation of product ideas.
Occasionally building something unique and small for a single customer makes sense. But enterprise software companies can easily fall into the habit of including custom work in too many of their major deals… with disastrous results. This (long) post lays out root issues and possible solutions.