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Why Product Managers Should Operate at the Intersection of Product, Design, and Data

Published Jan 12, 2021

Product managers are great generalists, and their talents can be applied in many places across an organization. Unfortunately, this means whenever there is a gap elsewhere in the business—often a knowledge gap due to a lack of continuous exposure to the market—bringing in the product manager is a natural way to fill it. As a Pragmatic Institute instructor, I’ve taught product managers who regularly act as de facto designers, user experience experts, architects, sales operations specialists, and project managers if their business is under-resourced in those areas. This turns the product management role from one that is highly strategic into “Chief Firefighter.”

A fellow Pragmatic instructor, Cindy Cruzado, points out another phenomenon: “When teams expand with design and data science roles, this adds additional pressure for product managers to provide details to these resources, making it even harder for them to become market experts.” We’ve heard firsthand the challenges and goals of product managers collaborating with data and design functions:

  • “Our organization is on a mission to digitally transform our products. I really want to learn more about data science so I can be a better product partner in that process.”
  • “I’ve started working with products that heavily draw on the quantitative data provided by our data science team. I need to understand some basics so I know how to get insights from all these numbers.”
  • “Designers I work with keep saying they don’t know enough to move forward, but I don’t know how much information or what kind of context to provide.”
  • “If I’m going to collaborate effectively with our design team on new products, I need to have a little more insight into their processes and capabilities, which are a bit of a mystery to me.”

Product management must understand that its function isn’t to fill gaps in the business but to enable its product team and business for success. That starts with working more effectively with data scientists and designers by knowing the right questions to ask and where their role stops and their peers’ roles begin. By transforming from Chief Firefighter into Chief Enabler, product managers can get the essential work done without juggling everything themselves.

Product teams and the product managers within them should create a culture of “outside-in” decision-making that leverages market data. This means performing primary research on their market — both qualitative and quantitative — to accurately represent what the market wants and needs. 

They can pull data from a variety of sources:

  • Win/Loss interviews
  • Competitive landscape insights
  • Their own product usage and adoption data
  • Social media sentiment analysis
  • Customer loyalty and satisfaction data

Fortunately, the product manager doesn’t have to do all of this themselves. There are many intersections with design and data science on this research, and those functions often have complementary goals. To start, working with those teams can help product managers form hypotheses to test and questions to answer.

“There’s value in involving designers and design researchers in the discovery process, when you’re first uncovering market problems,” says Jim Dibble, Co-Director of Design Practice at Pragmatic Institute. UX design research and synthesis are often untapped or under-utilized capabilities. Designers have rigorous practices around exploratory research with target users—from surveys to interviewing, quantitative to qualitative data. The patterns and insights that emerge from that research will help build user personas and deepen understanding of user behaviors, needs, and attitudes. So, on market visits, it’s valuable to partner with designers trained in ethnographic research, which focuses on developing that understanding of user behavior in context by observing people in their homes or offices and asking open-ended questions. 

Designers are also excellent at a process called problem framing (and reframing), which builds a deeper understanding of the market problems and how to potentially solve them. “If you give designers the opportunity to help frame the problem in a solution-agnostic way, you’re going to get richer results,” Co-Director of Design Practice Shannon McGarity says. Exploring multiple solutions for problems helps product managers refine a large quantity of ideas down to the highest-quality solution.

When it comes to quantitative research and analysis, data scientists are key. Whether they’re designing valid surveys, looking at product analytics and telemetry, or pulling a data set from an industry data source, product teams should work with their colleagues in data science to find trends and patterns in the data that they might not have found otherwise. 

A close partnership with the data team helps product managers avoid a common problem: access to huge data sets without the right analysis to provide actionable insights. Partnership has the added benefit of building alignment across teams, highlighting new metrics to track, and ensuring the data collected answers larger questions and serves product goals.

Often, product managers have to harness research and quantitative data to gain support and buy-in from executives on a product direction. They shouldn’t craft that story in isolation. As Cindy explains, “Leveraging design and data science will help product managers understand why problems are important to the market, craft positioning statements sharing impact on target personas, and articulate the whole story to stakeholders in a more succinct and concise way, so they can get others on board.”

Shannon adds that partnering with designers can help in synthesizing data, visualizing it, and creating narratives. In this way, “Product managers can be more persuasive and better detail the impact of what they’ve learned in market research, communicating that in a way that compels corporate action and conveys impact.” 

Amid increasing expectations and competitive markets, finding the role’s intersection points with data science and design and fulfilling the potential of cross-functional collaboration will empower product managers to work more strategically and effectively toward product success.

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