Are you designing for yourself or for your users?

Introduction

Back in the 90s and early 2000s, Alan Cooper coined the term "self-referential design". He was referring to the risk of designers designing for themselves rather than for their audience. If there is no external frame of reference, designers will simply design the solution the way they like it or are familiar with. While Alan Cooper was referring to the individual designer, this phenomenon of self-referential design also exists at the organizational level.

Insight-out thinking in product management

Domain experts in organizations slowly become disconnected from the actual work practice, product owners see their existing product as the solution to every problem, and existing products are incrementally improved within the existing solution space instead of studying the actual user need. This is also part of the innovator's dilemma because successful product organizations become immune to discovering new solutions, we at ProContext call this the innovation “immunization trap”.

Design Thinking helps - but can turn into inside-in thinking

One way to avoid this trap is to get closer to the end users and start observing the actual users without imposing a solution on them. The Gemba Walk or Contextual Design are two famous methods of this kind of ethnographic field research. However, because such field research is expensive, time-consuming, and requires skilled user researchers, it is often replaced by internal workshops that use design thinking exercises to immerse themselves in the user’s point of view and generate new ideas by leveraging the existing knowledge of internal stakeholders and invited customer representatives who act as proxy users. The inherent risk is that these participants may also be immunized based on their affiliation with the product organization that invites them to the design thinking workshop.

Can a handful of stakeholders provide representative input?

One of the main goals of these workshops is to break away from the day-to-day business and rethink the solution in a fresh and unbiased way. While these workshops seed innovative ideas, they are statistically dependent on a small set of stakeholders who are often subject to the collective immunization trap of innovation described above. Therefore, workshops need to be grounded in real customer/user data, which is often done by having domain experts share their knowledge about a particular work practice as input to the workshop.

The quality of the input depends on how representative this input is and how much these “proxy users” are biased by their own organization and experience. Replacing the designer's tendency to self-referentially design with the proxy user's tendency to self-referentially remember is still a high risk. This is why design thinking introduces a lot of forced voting and shortlisting, so that at least all workshop participants have the same decision-making power.

This dependency on participants is an inherent risk of design thinking workshops. While 3-5 field interviews result in a solid, unbiased picture of the user's reality, 3-5 workshop participants do not guarantee an unbiased view of the world. At the same time, locking these participants in a room for 2-4 days is also quite expensive in terms of man-hours from an organizational perspective.

Utilizing available “world knowledge” rather than relying on a few stakeholders

With the Product Context Analyzer, we introduce a low-budget tool for conducting secondary research in the world knowledge stored in LLM systems. Running an analysis with the Product Context Analyzer gives you a detailed description of the common work practices for a specific use case, leveraging LLM's ability to synthesize millions of content sources. This output from the Product Context Analyzer serves as an unbiased description of a product's usage context. The structured context information provided by the Product Context Analyzer is shielded from any self-referential point of view or organizational immunization trap. Utilizing this unbiased input is an effective way to level-set user research activities and counteract biased viewpoints. At the same time, the cost of using this tool is at a fraction of the cost of conducting field research or spending valuable workshop time to find out who the users are and what they do.