The Limina Podcast - Episode 3

Research and Insight Operations

Guest: Jake Burghardt

An organization’s responsiveness to various market dynamics, ranging from consumer and user behavior research to competitive/comparative or any other form of generative analysis, relies heavily on its research and insight maturity.  Our guest on this episode of The Limina Podcast, Jake Burghardt, is no stranger to maturing research and insight operations having product-managed Insight Hubs at Amazon Alexa, now writing research operations thought leadership at and serving on the Cheese Board at

Managing Insight Waste

While some organizations still struggle with making a case for meaningful user research and insight management, in many places where there is relative research maturity, they struggle with the opposite problem:  an over-abundance of research. In these places, when you look across all the types of insights we generated and trace back to the studies that generated those findings, there can be a tremendous amount of data and information that didn’t make the cut. When Jake says “Insight Waste,” he’s talking about huge piles of underutilized research.

Wrong Time, Wrong Place

There is research that didn’t come to light at the right time or was revealed in another part of the organization where those findings weren’t relevant but might have made all the difference in another product initiative.

The cost of this insight waste is   In a product-led growth mindset, if you’re striving to serve people through your products and refine them and open up new avenues, you can sit at a whiteboard and generate ideas or look at one piece of user feedback and get inspired – but often there’s great research that didn’t land at the right time or was revealed in places where the findings weren’t relevant it’s considered waste. The problem is that we’re not organizing research insights for the long haul.

Who asked for this?

There isn’t enough ownership over research. It’s treated as an optional input.  In today’s tech-driven culture, we’re generally documentation averse. Still, we always document what we think is important, and in every plan, there should be a “why” – and that why is what research provides. And all of that waste is just filled with all sorts of why.  No one should ever sit at a blank whiteboard in a mature organization with a good research community – anyone who generates insights about customers and how products can be better.

Right time, Right place?

What are the right touchpoints for insights?  How are you connecting them at the times and places decisions are being made?  This isn’t research work; it’s about building the right communication plan, tooling, infrastructure, and culture for insight consumption for maximum impact. How do you ritualize and provide the right tooling and communication environment for insight management to deliver that value at the right time and place?

“In every plan there should be a “why”. And that “why” is what research provides. And all of that [research/insight] waste is just filled with all sorts of “why” that people can be planning about.

-Jake Burghardt

“Making the case for research in an organization has always been the challenge. It’s still a challenge in a lot of contexts. During the recent cuts, we could see how the tech industry values research, you know, disproportionate cuts in that space.”

-Jake Burghardt

Insight Repositories – the Good, the Bad, and the Ugly

There are very successful insight repositories with a level of impact and traceability etc.; that is all you’d want an insight repository to be.  But folks are still struggling to maximize its value because managing the repository is likely a full-time job without an owner, so researchers and research managers are taking up repository management as a side gig. 

It’s more about starting by discovering and mapping the right types of impact we want to make and where and when we want to make it.  Be clear about outcomes, and realize that insight management is not monolithic. Various solutions fall into a system, knowledge, and culture management problem.  So regardless of the power that comes with some out-of-the-box solutions, if you don’t take the human-centered approach to align the implementation with the organization’s needs, you’ll see frustration and disappointment.

When is it time to invest in an insight repository?

It is time. If you’re doing research of any kind, where are those things living? What are the standards for how it’s done?  At a baseline, your research documents and practice knowledge should live somewhere that is an anytime proposition. It’s highly likely that by design or by organic construction, your research outputs live somewhere, and it’s time to start mapping them out and learning about how effective those locations are in maximizing impact.

The formal interpretation of “investing in insight repositories is atomizing research and promoting a subset of research and investing in tooling around that.” Still, there are a lot of interim steps between where most teams are and the ideal state of a single source of truth. And that’s probably an idea that’s not useful.  But it is important to know what you want to elevate from all the research and push to certain outcomes – asking who do we want these insights to influence and when? Starting with those questions, let that drive the tooling.

Push Model for Insight Operations

When dealing with repositories, cultural and ritualistic changes need to be implemented for the optimal utilization and consumption of repository content to maximize its value. Still, there is also an opportunity for communication strategy, planning, and potential implementation of push notification frameworks. This is particularly relevant for insight management work when you’re interpreting research now for later use.

Part of the model requires curation, taxonomy, and metadata management to organize the information, either by descriptive metadata meaningfully or highly contextual metadata, to make the information relevant to specific teams (workflows, screens, components, use cases, user segments, job to be done, etc.) But ultimately, to make sure your insights are impacting teams at the right level to make informed design and engineering decisions takes an integrated push model that can be automated and consumed within the tooling of agile planning and execution, whether that’s at the documentation, meeting, tickets or review cycles of a given product or service initiative.

The Culture of Insight Value Management

There are various centralized, embedded, or hybrid models, with researchers supporting the entire organization and as dedicated contributors to product or service teams.  There are benefits and drawbacks in every instance. Still, there’s a cautionary tale of the heavily siloed research contributor who may be overworked or feeling disintegrated from participating in more meta or ecosystem-wide research initiatives. It’s important to ensure that all contributors to research at the organization can be tied into and have visibility of research initiatives and outputs at all altitudes, from long-range strategic studies to highly tactical research initiatives at various parts of the org. You never know where discoveries are being made that can impact the ecosystem.

In addition, partner with your

Partnering with AI for Insight Management

The truth about human-centered design research is that a high degree of contextual nuance and awareness that knows the history of all of the product(s)’ history, the users, customers, subject matter experts, and organizational behavior to support those products and services to build the level of context that AI may not be ready to support in a valuable and automated way. You may be able to use AI to query data, use a large language model, and use natural language and transformative computing, ala Chat GPT. The more important mindset concerning AI is to discover how best to partner with AI’s power and capability at meaningful points in the research and insight management workflow rather than try to engineer a wholesale automated takeover of research operations.

“Any place where research is stored, in my view as a repository, even a Slack channel. If that’s the place that people are going back and looking for, we need to map out those locations and understand them”

-Jake Burghardt

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