I’m honored to be named alongside many of my idols like Marty Cagan and Eric Ries in PM Year in Review’s 2017 list of Product Management Influencers! Thanks to Alpha and Product Management Insider for your support this year as I’ve launched and grown my product discovery training and consulting business.
I’ve found that while people often tend to focus on solutions, when we step back to build agreement on what problem we are solving and which constraints are important, we find it much easier to agree on which solution to pick.
Check out the piece for the full story on the approach I used to help my family agree on a vacation plan:
Yesterday I had the pleasure of running a workshop at Thoughtbot‘s Summer Summit.
Thoughtbot is one of my favorite design and development shops, because they are creative, smart people who are great at applying modern best practices like design sprints, design thinking, agile, and extreme programming to build products for their clients. We used them when we were getting Shutterstock Editor going and they brought a lot of value to the team.
So I was thrilled to have the opportunity to talk with them about how to persuade key stakeholders to pivot or even kill an idea. We did exercises around about empathizing with stakeholders; quantifying the product opportunity; selecting key outcomes, core behaviors, and key metrics; and focusing research by talking about initiatives’ risks ahead of time.
I spoke with Mike Fishbein about making evidence based product decisions through high impact experimentation for episode 113 of the This is Product Management podcast. In it, I shared:
Check out the post about it to read more or find iTunes and Stitcher links for the podcast.
We don’t need to test everything. We need to test the things that are risky.
I spoke with Kaya Ismail of CMS Wire about the need for large data sets and real customer problems to drive successful machine learning (ML) products for his coverage of Hubspot’s acquisition of Kemvi. Here’s an excerpt:
Holly Hester-Reilly of H2R Product Science believes HubSpot’s acquisition of Kemvi is a, “smart move for both teams.”
Hester-Reilly continued, “[By] combining DeepGraph’s algorithm and process for processing publicly available data with HubSpot’s data on real sales looks like a great opportunity to develop real-world machine learning solutions to solve real problems for HubSpot’s sales customers.
Check out the full piece over at CMS Wire for more details on why Hubspot’s acquisition of Kemvi is exciting news for artificial intelligence, machine learning, and big data product practitioners.
I talked with Mike Fishbein about techniques to identify bad product ideas and convince stakeholders when it’s time to end an initiative. Here’s an excerpt:
When working on a product that’s already launched, Holly emphasized the importance of looking beyond “vanity metrics”, such as page views and user counts, to truly understand if the product is valuable to customers.
Read the full article on the Alpha blog for more insights, including advice from Tami Reiss and Beth Temple:
I’ve found that a key to developing continuous discovery and delivery practices—sometimes called dual-track agile—is to master the simple practice of hosting a “Built-Learned-Planning Demo” (BLP Demo).
Check out the full piece for more details and examples of how I used the technique as we built out the Shutterstock Editor team:
I talked with Moira Alexander about using long term agile planning exercises to set teams up for success and communicating candidly with stakeholders to manage expectations. Here’s an excerpt:
When it comes to addressing expectations, Hester-Reilly says H2R Product Science focuses on regular communication with stakeholders about what’s known and unknown. She utilizes visuals to show the complexities in the problem and in the technology that her team builds. In the planning stage, Hester-Reilly walks her teams through a technique similar to agile planning poker, to improve work estimates. The goal is to help her teams identify various projects they’ve done and assign a value, then they look at the work planned and do a comparison.
Check out the full article on Tech Republic to learn more tips for scheduling large initiatives:
I shared thoughts with Rachel Ferrigno for her piece about finding great female talent in tech. Here’s an excerpt:
Holly Hester-Reilly, Founder of H2R Product Science, prefers interviews that mirror the actual job functions of the position she is applying for. She says, “In terms of process and structure of interviews, I love it when employers focus more on asking for real demonstrations of my skill in the activities involved in the job, instead of focusing on the titles or roles I’ve played in the past. Since advancement within organizations is often affected by implicit biases or the impact of relationships that can be harder for women to build up in tech workplaces, de-emphasizing past roles and advancement in the interview process is a great way to identify female talent that will thrive on the job.”
Check out the full piece for more tips from women in tech on what employers can do to attract and retain a diverse workforce.