Welcome to the third post in our series about best practices to create a healthy relationship between product owners (POs) and product managers (PMs) that drives product success. You can check out the previous post here.
In this post, we’ll dive into examples of how you might find yourself in the feature factory described in our first post. Plus, we’ll offer some thoughts about how to get back to strong PO/PM relationships, and focusing on delivering value.
Scenario One: Who are you talking to?
Picture this: You’re a PM at a company that’s designing a new app. In the spirit of customer centricity, you’re actively getting feedback. You’re regularly talking to a couple of hyper-engaged customers from Company X. It’s a large company and you’ve got a strong relationship with one of their internal champions who’s easy to get in touch with. During one of these customer feedback sessions, a developer on your team joins the call, too. Afterward, while you’re confident things are headed in the right direction, your developer wonders out loud why the customer thinks feature A is great if she really hasn’t used it yet.
Contacting the same customer for feedback on every new thing your company is working on isn’t the best approach. Why? If you’re not careful, you might end up thinking about her as representative of all the rest of your customers with the same job title. That’s likely not the case, so you should also be talking to customers at different companies with different needs for whatever it is you’re building. Another thing to think about: if it’s just you talking to the same customer all the time, you’ll often believe that your organization is always building the right thing. Inviting other people in your organization to collaborate with you on those customer calls might uncover a different perspective, as your developer did in the previous scenario. Having those two or three perspectives in the room is greater as a whole than as individual viewpoints.
Scenario Two: What are you measuring?
Picture this: Your organization developed a page on a website and is seeing 20 percent user adoption on that page. As the PM, you think that’s successful because you’re hitting a key performance indicator (KPI) revealing that 20 percent of people logging in are using the page. But your PO feels that’s not necessarily true because the metric represents the same handful of people logging in, not 20 percent of overall users, which is how they interpreted the KPI of “20-percent adoption.” To address the data conflict, you and the PO look at the feature to see what the details of the KPI were. Turns out there aren’t any details, nor is there any mention of baseline metrics. So, neither of you know if the page was successful or not, or if you should pivot or persevere, or what to compare the data to. And the team’s efforts turned into a feature factory because the goals were really about getting the features out the door instead of the goals themselves.
It seems really apparent that PMs and POs need to agree on what measurements translate to a successful outcome, and how they’ll be tracked and interpreted. But we often skip over that part, just assuming all that will be obvious when the time comes. But actually, that assumption often leads to data conflicts. Aligning on metrics is hard work. You may not even know exactly how to measure success yet and you might have to slow down before you speed up, but agreement is critical to avoid future data conflicts.
The same applies to determining the goal of the work and the value to the customer using SMART objectives. Many of us are familiar with these. But really, how often do you and the team take the time to get alignment and a clear, shared understanding of all the details of your objective? Is it specific, measurable, achievable, realistic, and time-bound (SMART)? Or is it just specific but not measurable?
And remember, it’s ok to fail, as long as you’re learning and applying what you learn to improve. The learn part is only possible in a culture that allows for failure, for example, where you’re not hitting the metrics. It’s a culture where people don’t feel the need to mess with the data or avoid committing to a measure from the beginning. It’s part of the innovation process to fail. If the culture doesn’t allow for that, then you’ll get a culture of people that skip that step on purpose to make it look like they’re successful.
The trap of the feature factory is easy to fall into. I hope now that you have a clear path to:
- Improve how you collect and perceive customer feedback
- Write clearer KPIs with baseline metrics
- Clearly define and align on SMART goals across teams
Armed with this information, you can better recognize the trap, and use your PO/PM relationship to stay out of it.
Check back soon for another post in our PO/PM success series.