When it comes to digital products, innovating with good intentions is not good enough. Most teams never intend any harm, yet the algorithms they create–based on their own background and experience–are algorithms that end up impacting a significant number of users negatively. Often teams never suspect certain contexts or edge cases exist, especially with algorithms that use data to guide interactions. To illuminate assumptions like these, surround yourself with different perspectives and broaden your awareness of diverse thinking styles. Know your problem space.
Most teams have an abundance of skills for solving problems, and only shallow experience (and time, budget, encouragement) understanding the problem space. The problem space is about understanding people and their larger purpose–and it has nothing to do with your organization, your offerings, nor users. Soak up a deep understanding of their inner reasoning and the way their reactions and guiding principles guide their decisions.The mindset of problem space research is about letting go of thinking of solutions for a time.
Organizations are starting to realize they’ve not invested enough in understanding the problem space. In addition to budgeting to study their solution’s design and use, now leading-edge organizations are also investing in problem-space research. They are gathering data for mental model diagrams and opportunity maps, cross-correlating these with thinking styles, and methodically applying this tangible knowledge to their product strategy.
Not every organization understands the risk of their own assumptions, the misleading correlations they steer by, nor how confidence in data is achieved in the social sciences. But when they do, they realize problem-space research is necessary. And they educate themselves about when it’s needed and when it’s not.
developers • product owners • user experience designers • market strategists • team leaders • entrepreneurs