Dispatches from Day Four of the Operational Analytics Conference
Product managers have a special place in my heart – it was my first job right out of college. I was a PM building developer tools at Microsoft for seven years before starting my first company. For me at the time, it was the perfect job because it was a really interesting discipline. It's multi-faceted, and you get to touch a lot of different things while doing your job, not just pigeonholed into one thing.
That made Thursday’s Operational Analytics Conference panel was a perfect mix of nostalgia and tons of insight, as our expert panel of PMs, ex-PMs and product people shared their perspectives on building data and machine learning products, up-leveling their companies and organizations to be more data-centric, and when not to use data in making product decisions. The panel was
While we covered a ton of ground over the course of the hour, James shared a story that hit home for me. Alignment and coordination between teams is a crucial component to successful project management. While a team might be incredibly high performing and hitting or exceeding all its numbers, if those OKRs or metrics aren’t tuned in to meet the needs of that team’s constituency, that success is going to be pretty hollow.
James Mayfield: I'll share one thing that was particularly telling for me while PM-ing a team that was focused on data infrastructure, analytics tools and a mission-aligned platform. We once had an instance where our team actually hit a majority of our OKRs. We were agreeing across the board, but data science was incredibly unhappy and unproductive because the goals we had at the time were largely focused around scalability, uptime and ensuring that the platform was available and running smoothly. I thought that was incredibly telling and both from a perspective of being able to set the right goals.
The really interesting thing was that we had co-defined our specific metrics and OKRs with our most important customers, and actually identified things that make them more productive. That's when you start thinking about your data stack as a complete end-to-end product. It's not just each part – the data visualization tool, the query engine and the data platform in isolation – it’s about thinking about and defining things that go end-to-end. That's where product managers can play an especially effective role in these types of situations – really looking at, and thinking about a use case from start to finish.
Boris Jabes: That's a great insight. You could use James's approach to say, "Hey, let's instrument our outputs to find out if people are even using them," which is a good way to determine whether you're adding value in the organization.There's also something almost more simple and human. If you've accomplished your goals at the end of the year, but the team is actually not happy, you could probably find that out with a very small number of interviews. Those are all probably good signals that you need a product manager in the mix.
The whole discussion was a fantastic, in-depth dive into a profession that’s always changing and evolving. It’s a must listen for current and aspiring PMs.
Listen to the entire discussion below and be sure to check out the other sessions as well.