I love seeing big ideas turn into great products. In this talk, Jack Dorsey talks about the big idea that eventually led to Twitter and his new big idea behind Square. Few people have the ability to go from big idea to successful product like Jack does. Even for ideas with narrower scope, much can get lost in the implementation. But why is this?
In talking with founders, investors, product folks, designers, and engineers, here in Silicon Valley, I’m starting to realize that product management is still grossly under-developed. At many startups, the function, if it exists at all, is nothing more than translating feedback into feature lists, prioritizing that list, and calling it a product roadmap.
How many startups have defined a product strategy that clearly outlines what they might build and more importantly what they won’t build? Most of us are familiar with contextual inquiry, needs analysis, usability testing, A/B testing, among other tools, but how often are we using them? We know these tools are valuable. Why don’t we integrate them into our practice more often?
In some cases, the problem might be lack of knowledge. The 22 year-old, new college grad, who just raised a seed round, might not know the value of usability testing or contextual inquiry. Likely, he had a big idea, and sold a set of investors on that idea. That’s a great accomplishment. But it’s only the beginning.
For others, they might know about these tools, but lack the know-how to use them. I might know that I should do market-research, but if I don’t know how to construct a survey without asking leading questions, I’m probably not going to get very good data. In fact, I’m going to get data that merely confirms my assumptions.
And yet for others, they may have both the knowledge and the know-how, and yet still fall short in practice. It’s this last case that is most interesting to me. I’ve been in this situation myself many times. I’ll be the first to say I did not test every design. I have ignored valuable user feedback that turned out to be significant down the road. I have stubbornly clung to my product vision in the face of a mountain of data telling me I’m wrong.
Why does this happen? I suspect psychology can tell us a lot. I’m sure cognitive biases are at play. I know that the time pressure of most startup environments is a big factor. When there’s pressure to ship, it feels like there just isn’t time to use these tools. But I suspect by cutting them out, we are taking more iterations than we need to to get to a product that our customers want and can use.
My questions are as follows:
- How can we, as product managers, do a better job of leveraging the tools of our trade?
- How do we refine our methods so that we adopt them more often in practice?
- Can we develop new methods that help us overcome our cognitive biases so that when we do leverage these tools, we are more likely to integrate what we learn?
Through my consulting practice, drawing from both academic and business literature, and in conversation with others, I’m looking forward to exploring these questions. I plan to blog about the experience and suspect topics will include:
- Product Strategy
- linking product vision to company mission
- developing guiding principles / values
- understanding business model options
- accounting for distribution
- Product Discovery
- uncovering customer needs
- understanding context
- conducting ethnographic research
- conducting survey research
- working with sales and client services
- Idea Generation
- setting the scope
- asking the right questions
- Working with Engineers
- writing requirements
- setting project schedules
- working with engineering estimates
- Prototyping
- building prototypes
- validating prototypes
- starting with the minimum viable product
- defining iterations
- Usability Testing
- conducting studies
- communicating the results
- applying what you learn
- What Users Really Do
- learning from A/B Testing
- understanding traffic analysis
- Product Performance / Meaningful Metrics
Again, whether you lack the knowledge, the know-how, or the practice, my goal is to focus on how we can evolve the function of product management so that more big ideas turn into great products. I’m really excited. I hope you’ll join me.
Alex says
Hi Teresa,
First of all thanks for sharing your experience. I have one question and perhaps you might be able to shed some light. How do I translate data analysis into requirements? For the moment I’m talking about mobile app data and assuming I don’t have focus group/ market research data. Is there a specific methodology? Are the requirements that can come from pure data analysis more like hypos > optimisations than actual new features/products? Would you be able to share a couple of examples of how pure data analysis has/can led to defining new requirements?
Many thanks,
ttorres says
Alex, you raise a great question. It’s one I’ve been thinking a lot about, as there seems to be a lot of variance in quality in how people pull out product insights from research or traffic data. I’m hoping to tackle this very topic in a few posts with time. It’s a hard question and I’m still experimenting. But stay tuned for more.