Is Product Management More Art Than Science?

Michael Riemer Michael Riemer
July 2, 2018 ConsumerTech

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Does being customer-focused mean that product usage information is the most critical factor in driving feature/enhancement prioritization. A recent LinkedIn post by Gibson Biddle reconfirmed my long-held belief that good product management is as much art as science.

From a quantitative perspective, it is really exciting to see some great new products (such as Pendo.io, Mixpanel just to name a few) that enable a better understanding of user behavior (customer experience) within applications.

But does product usage information give you the insight you need to make all your critical decisions?

Anyone who has worked with me over the last 30 years has heard me say that poorly designed features that don't get used are not (necessarily) good indicators of customer need or value.  

On the qualitative side, I have also been known to say that "customers are never right" when they ask for feature changes. This means that customers only know what they know, but not what is possible. One (of the many) job of a good product management is to work with the customer to uncover new ways to solve their problems. Start by asking "why" – why is it important; why does it impact their business or process; why will it change their behavior; why will it increase user engagement; why it will it impact their metrics for success, etc. –

Recently, Roger Attick shared a great article from The Atlantic by Derek Thompson about Google-X. The following passage, based on the author's idea for creating floating houses on oceans, sums up the critical importance of asking why.

"I’d expected the team at X to sketch some floating houses on a whiteboard, or discuss ways to connect an ocean suburb to a city center, or just inform me that the idea was terrible. I was wrong. The table never once mentioned the words  floating or  ocean. My pitch merely inspired an inquiry into the purpose of housing and the shortfalls of U.S. infrastructure…They start with the hard work of finding the right questions.

At least in the B2B software world, I also don't agree with the infamous quote attributed to Steve Jobs — "Customers don’t know what they want".  Customers understand their businesses better than any software provider. However, it is impossible, IMHO, to create great products and services that delight and engage users, and deliver valuable customer outcomes in a vacuum.

So what does this mean? 

It means that as a product manager, you need to capture, understand, interpret and analyze a range of qualitative and quantitative inputs to arrive at the ideal product decisions including:

  1. The competitive landscape (and substitutes if you think you don't have competitors and most importantly how does this impact future sales opportunities)
  2. Direct Customer feedback (including in application messages, support calls, feedback from sales, customer meetings, etc.)
  3. Indirect Customer Feedback (what they say about you on social channels)
  4. Product and service usage and analytics (as mentioned above)
  5. Qualitative market research (one-on-one interviews, focus groups, etc.)
  6. Quantitative market research (including stated and derived importance/value of features versus delivered satisfaction of such features)
  7. Customer Value (how much does the customer value the feature, will it make them a customer for life – Bob London's favorite question, and the rest of the why questions from above)
  8. Company Value (what value does it bring to your company and how does this align with the broader company goals – new revenue, incremental revenue, user engagement, user retention, etc.)
  9. Risk and Scale (how risky is the development effort and how much resource will it require)
  10. Vision, Intuition, and Experience (enough said)

While this is likely not an exhaustive list, it's clear there is no one single source of "truth" exists when making product decisions. Some inputs are definitely more quantitative than others, but many also need a dialogue with customers as well as judgment calls, best guesses, and interpretations.

Putting all these inputs into a single, uniform funnel or process is one of the hardest and often the most controversial activities inside a software company. I have personally not used all the techniques that Daniel Zacarias outlines in his recent post in Folding Burritos. It is also clear from the recent survey results in Mind The Product by Kate Bennet that there is no standard approach or single tool that meets everyone's needs.

So what's the answer? Is product management more art than science? I guess the debate continues. What do you think?

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