Researchers - The engine of your organization’s continuous learning

Article: Researchers – the engine of your organization’s continuous learning

“Oh right! We have a research department.” 

You’d be amazed at the number of times I hear that from product development teams. Most large companies hire researchers. Those same companies then end up putting those folks in a department with an acronym no one can decipher, under a leader who doesn’t understand what these folks do. Or they do end up in a group that values their work but then hordes their skill sets only for work within their jurisdiction. Regardless of the organizational design, researchers are often underutilized and undervalued. This has to change.

Big research efforts are vital

If you’ve read my work before, you know I’m a huge advocate for lean, lightweight, cheap learning activities. That focus in no way negates the need for large, longitudinal research studies. There are behavioral patterns that only emerge over time. In more complex industries (think B2B2C or highly regulated environments) it may take months to understand the complete impact, at scale, of a proposed or existing user journey. Your research team (go find them) is uniquely equipped for this task. This is what they live for. They will help you refine and sharpen your learning goals. They will give you a sense of what they need to do to achieve those learning goals as well as how long it will take. And, at the end of the initiative, they will deliver the results you need.

Now, this doesn’t mean they disappear for nine months only to emerge triumphant with magical results. No—while the total initiative may take months, your research team is responsible for reporting back to you on a regular, shorter cycle. They should share what they’ve done, who they’ve spoken with, what they’ve learned so far and what’s coming up next. They may even have some preliminary results to share with you. Their work is designed to reveal, over time how your customers, both current and prospective, act within your domain and industry. 

What are the latest trends, and how are they being adopted and adapted? 

Who’s leading the way? 

What are they doing that’s attracting attention? 

What’s the impact of these new trends over time? 

These big questions can only be answered with large research efforts. They underpin the more tactical, shorter-term questions your teams ask in each sprint. 

When I worked at a job board company called The Ladders years ago, we interviewed executive job seekers on a weekly basis. At the time, texting was new. It was mainly done by teenagers, and it was certainly not a viable means of “real” “business” communication. Over time, though, we started seeing a shift in job seekers’ behavior. Suspecting their bosses could read their emails, they began texting headhunters and recruiters when they began their job search. They believed this was a way to circumvent any corporate spying and keep their job searches private. At first it was a trickle. Then, it became a full-on flood of text messages. The behavior was changing, slowly, over time and, had we not been running a lengthy research project to continuously monitor job seeker behavior patterns, we would have missed it until it was too late. Instead, we were ready with new features that solved for these needs.

For lighter efforts, researchers can ensure high quality

Lean experimentation also requires research. In this case the research is continuous and frequent. It happens every sprint. There are not going to be enough researchers in your company to actively support every product development team. That’s why we rely on our product managers and designers to do the majority of the tactical research through product discovery and Lean UX methods. 

Many of the teams we meet don’t know how to do this. We train them, but they often need ongoing support. This is where your research team comes in again. Given their vast expertise, your research team can level up the skills of your product managers and designers to make them good customer interviewers. They can help them learn how to synthesize qualitative data and write good surveys. In this way they democratize research across the organization and ensure it stays front and center in the work of every team across the company. Lighter research efforts aren’t going to yield huge a-ha’s every sprint, but that doesn’t mean the data they produce should be low quality. Lean on your research team to make the rest of the organization better at product discovery.

Continuous learning requires qualified skills

Your teams need to build learning into every cycle. Your research team (again, go find them) can support cycles of every length so that learning is indeed continuous within your organization. In longer cycles they can run the research themselves. This is their core expertise. For lean experimentation and product discovery, ask them to train your teams to do great interviews and surveys. This is where most teams start their product discovery journey. If they have a good experience here, they’ll continue to advocate for evidence-based decision making. Your research team can make all of this happen.

What I've been up to

I went to Dublin, Ireland, AGAIN (four times this year), though this time it was to celebrate my friend Jon’s 50th birthday. We decided to act our age and take the above photo. That’s 100 years of youth making that leap :-) 

December is always a busy month for my family with the holidays, my wife’s and my wedding anniversary and lots of family birthdays. This year we decided to spice things up a bit and also move houses. Why not, right? What this has meant is that basically everything else is taking a back seat to the move. The next time you get this newsletter we will be in our new place, hopefully settled and out of boxes. I’ll share some pics once that’s done.

On a work note, Josh Seiden and I are hip-deep in the second draft of Who Does What By How Much?, our new book on OKRs. Learn more here. And we are now booking out into Q2 and Q3 of 2024 for workshops, keynote speeches and coaching work. If you’re looking for some on-demand training in Lean UX, product management and OKRs for your teams instead, you can learn more here. 

Finally, as the year comes to a close and this is the last newsletter of 2023, I wanted to say thank you. Thank you to our clients for continually trusting us and working with us to build better products. Thank you to you for reading this newsletter, the blog posts, LinkedIn blurbs and the books. I can’t tell you how much it means to me to hear from you and know that I’m making some kind of a difference in the way you're working. If there’s anything else I can do to help you, your team or your company, don’t hesitate to reach out.

Happy holidays, and a happy new year to you and yours! See you in 2024. 

Jeff

Watch, Listen, Read

Watch: Bodies on Netflix – Time travel? Murder mystery? Post-apocalyptic new order? I mean, that’s my recipe for a show. And this series didn’t disappoint. Good fun all around.

Listen: The Whitest Boy Alive – Another weekly discovery thanks to some algorithm that caught my ear. I like the mix of groove, Rhodes piano and chill vibe. It’s good “load the dishwasher” music as well as some late afternoon chilling out.

Read: Conscious Capitalism by John Mackey and Raj Sisodia – I read (most of) this book for my book club. I won’t lie: It’s not great. But it’s worth reading or listening to the first chapter or two to hear John Mackey’s origin story and the founding of Whole Foods. He basically does an about-face on his convictions after figuring out that communism wasn’t his vibe any more. What a shock :-) All that said, this whole book boils down to: treat all humans with respect. I can get behind that message and try to live it myself, but I didn’t need 300 pages to tell me that. YMMV.  

New on the blog

Measuring What Doesn’t Matter – We build on the shoulders of giants. That doesn’t mean those giants were flawless. Grove, Doerr and others gave us OKRs. Here’s how OKRs evolve.

Use Key Result Triggers to Stay on Top of Progress – When do you act on new data? Using OKR thresholds to trigger a team response can help. Here's how to do that.

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