Intent vs. Practicality: On the desire to develop Research Insights Databases

Numerous times, my colleagues and I have worked with clients who, with varying levels of commitment, express a desire to capture insights generated from qualitative research in some sort of searchable, widely accessible mega-database. Their intent is good: to create a means of knowledge-sharing that isn't reliant on a small handful of research leads with a bookshelf full of reports knowing what might be appropriate to whom and when. And in organizations with thousands of people, the possibility (for example) of someone starting a project on marketing in Ghana to, without engaging an expert or scouring a server folder, see if their company has ever done research in the space and what was learned is pretty powerful. 

So, what could possibly be an argument against investing in the development of this sort of knowledge-management tool? When its development is considered supplementary for doing primary research work entirely. Especially when conducting generative research (defined in more detail here), there are three important considerations that affect the outcome (and usefulness) of the research output - which would be lost should qualitative research findings attempt to be handled in format much more conducive to quantitative data. 



With technology and associated behaviors changing  and evolving at an unprecedented rate, qualitative research studies now have a relatively short shelf life. This alone supports a need to do research of a similar shape and size "again," for the purpose of recency. It's ok to do the same research more than once, if it's being done for different reasons by a different team - as long as there's an awareness of it being done before and of what was learned. Which leads to the second consideration...



A tremendous benefit of doing qualitative research is having the team experience the research first-hand, in order to gain empathy with the participants, and then to be able to make more informed and effective decisions. Generative or exploratory research, by its nature, is meant to provide the team with an understanding of more than just words. Ethereal concepts such as a user's mental model of a subject are captured and understood through well-conducted research, and are not easily translated into a particular format. Good researchers understand the importance of context and design research plans to utilize it, and that context is at least half of any useful piece of data. A skilled storyteller will be able to communicate research findings in a manner that resonates with those outside of the research team, however the nuances of the project, the customer and the contexts gained are what drive the magic that is good experience design. Someone sitting behind a computer screen and "experiencing" research is the polar opposite of what good research ought to be - and anybody who's done it will tell you that the quality and texture gained from real-life engagement is unparalleled. But, isn't any research better than no research? Yes, yes it is. However, if you and your company are allocating time and resources, it ought to be considered an investment with specific goals, rather than an activity to be completed.

Assuming a team is capable of producing the richest and most effective storytelling in the world - capable of providing an emotional, virtual-reality-like experience with how they communicate the research outcome - a third consideration is...



A good research deliverable takes the form of its content - using the deck, or video, quotes and photos as part of the storytelling. The format dictates ingestion of the information in a considered manner. When data is gathered in-field, it is generally done so in the form of narrative, through a participant telling stories, making verbal and gestural connections between the seemingly unrelated data points of their life. Databases are, well, databases - and it's difficult to describe, in a field, the narrative undertone of a presentation or anecdote. Arguably, there is no explicit relationship between the data points - as they are organized by a technical means - rather than a narrative in context. Unless the type of data (method, topic) is relatively similar across studies, it will require an immense amount of customization and curation by the project team (or a separately-tasked librarian) to effectively communicate the learnings and resonant bits of a particular project.  


All of this said, these research repositories can be useful as secondary research or foundational information to inform, validate or direct new research efforts - rather than as a supplement to it. It's not uncommon at the start of a project to have an inbox full of background material and previous studies, which the research team ingests and considers as they develop hypotheses for their work. To be able to go through this at a high level and get the findings is useful.

So no - I do not believe that an organization can create efficiencies through this type of platform that rationalize a reduction or elimination of new research efforts. Frankly, it may be better to instead think of more nimble and interesting ways to get teams in contact with customers or contexts of interest. Especially when considering the costs of the development and maintenance of this type of tool, it's worth revisiting what your research is actually doing (or meant to do) within your organization, and where you want your money to go.


Shout out to Matt Franks - thanks for your eyeballs.