Insights Operations, Enablement, and Harmonization

GRIT’s ruminations over the 2026 Insights Practice Report and its predecessors led us to think about how musical ensembles compare to insights teams and how they are coordinated, especially as the somewhat malaproptical term “insight orchestration” crept into the conversation.

“Orchestration” means the adaptation of music composed for one medium so it can be performed by an orchestra, presumably under the command of a conductor. Somehow, copying ideas so that they can be precisely recreated in another form with a repeatable process and a predictable outcome doesn’t seem to capture what most insights stakeholders want to reap from their investments. An “insight” represents a new-to-the-world (or at least “new-to-you”) understanding, and it has nothing in common with well-rehearsed ways of reproducing pleasingly familiar outcomes. 

Perhaps some insights organizations resemble symphonies: highly structured, with formal sections, clear roles, shared standards, and strong central direction. Others may be closer to jazz combos, where skilled players work from common themes but have considerable freedom to improvise. Still others may resemble music festivals, with different stages, genres, performers, and audiences operating autonomously yet within a curated program. As GRIT makes us increasingly aware, insights teams differ as much as musical ensembles, from orchestras to string quartets to garage bands to DJs, and coordination within and across them can be just as idiosyncratic.

Insights Ecosystems and Ensembles

When GRIT explores insights roles and configurations of roles on the brand side, we are exploring what each participant tells us about their insights ecosystem, which includes anyone they consider to be an “insights professional.” “Ecosystem” describes the complete current environment, regardless of whether it was intentionally designed, evolved over time, or both. 

Recent GRIT data suggests that insights work is becoming more centralized at the same time as it becomes more decentralized. Among brand-side research professionals, the percentage working within an insights or research group increased from 53% in 2022 to 67% in 2026. Among analytics professionals, the percentage working in analytics or Data Science increased from 27% in 2023 to 52%. This suggests increased centralization.

At the same time, the percentage of research professionals saying all insights professionals work in a formal group declined from 65% to 52% in the latest wave, while the percentage saying only some do increased from 30% to 39%. Among analytics professionals, “all” fell from 27% to 14%, while “some” increased from 64% to 80%. This suggests more insights work is being done by specialists outside of a central group even while the sizes of the central groups seem to be growing.

Because these questions focus on “all insights professionals,” we can assume that those operating outside a formal group are embedded insights specialists. About one-third of research professionals work outside an insights or research group, while nearly half of analytics professionals work outside an analytics or Data Science department. They can be found embedded in marketing, product and innovation, executive functions, CX, and other areas. 

Although GRIT mainly focuses on insights professionals, we have reason to believe significant insights work is performed by non-specialists distributed throughout the organization. Several signals suggest they matter. Insights professionals contribute across a broad range of business disciplines even where their leadership of those disciplines has declined. Technology and self-service capabilities are widespread. Earlier GRIT research has also documented concern about the rigor of work performed by non-experts. None of this tells us how many non-specialists perform insights work, but it does suggest that formal insights specialists do not represent the entire ecosystem.

Perhaps, then, we can think of an insights ecosystem as a large music festival with a variety of prog rock, soul and R&B, hip-hop, chamber pop, and other styles performing on different stages, some at the same time and some at different times. Some stream over Hulu to a wider audience, some play only to their in-person audience. We can think of centralized groups, embedded experts, and distributed non-specialists as ensembles representing different genres and audiences, and each type may be represented multiple times at the same “festival.”

The comparison to a music festival breaks down on an essential point, however. Although a festival promoter curates the entire festival to appeal to different segments across a broad audience, they do not have to harmonize each ensemble into a single coherent piece. An insights manager has to do exactly this or risk stakeholder exposure to a cacophony that could bring the whole practice of insights into question, if not undermine the realization of business objectives. Somehow, the rule-based “insights orchestration” approach seems to fall well short of this challenge.

Enter “Insights Operations”

GRIT continuously tracks the evolution of brand-side roles, but has paid less attention to how these various ensembles might (or might not) be enabled and harmonized by some deliberate, coordinating force. This year, the Insights Practice survey introduced “insights, analytics, or research operations” as a role that might be significant for insights professionals, alongside others we perennially track, such as in-house research, strategic insights consulting, and data and analytics. 

Its debut was striking. More than 80% of brand-side participants identified operations as a significant role for insights professionals, and 28% selected it as the most important role—more than any other role tested. 

Because this was our first measurement, we cannot say whether operations is increasing, declining, or holding steady. Nor did GRIT define the term tightly enough to assume that everyone means the same thing by it. It could refer to workflow management, technology administration, governance, supplier management, enablement, knowledge management, standards, quality, or some combination of these.

To better understand what GRIT participants visualize when they see “insights operations,” we asked the data: What tends to be different across participants who say insights operations is the most important role for insights professionals and those who name another role as most important?

A More Scalable, Integrated Insights Environment?

Participants who name insights operations as most important are more likely to work in organizations with large insights staffs and budget. Twenty-five percent report 100 or more insights professionals where they work compared with 14% of everyone else, while only 12% report four or fewer compared with 23%. They are also more likely to report research budgets above $15 million, even though company size and number of research projects do not meaningfully distinguish the two groups.

The importance of insights operations seems to depend more on the complexity of the insights ecosystem, not simply the size of the enterprise. The correlation with complexity is reinforced by their methodology priorities. 

When choosing research methods, participants who name operations most important place much less emphasis on total cost, with an importance score of just 28.0 versus 47.3. They place much more emphasis on scalability, 14.9 versus 5.5; innovative approaches, 16.2 versus 6.1; and ease of synthesis with other sources, 12.7 versus 5.3.

Their regular methodology use also skews toward capabilities involving integration, infrastructure, automation, or flexible access. Software and tools marketplaces are used regularly by 61% versus 33% of others; data integration by 53% versus 37%; and talent marketplaces by 30% versus 16%.

Rather than selecting isolated project solutions, those who say insights operations is the most important role seem to be focusing more on how capabilities fit into a broader system.

Technology and Outsourcing Can Grow Together

Supplier priorities support the theme of scaling to manage complexity over optimizing individual projects.

Among those who name operations most important, 55% consider suppliers' use of technology in research and analysis a key selection criterion, compared with 28% of others. They place less weight on general pricing, 53% versus 70%, and existing relationships, 24% versus 40%. Whereas they place less emphasis on relationships, they place more emphasis on reputation (49% to 38%).

At the same time, they are not turning away from outside suppliers. They are more likely to say they rely too little on external suppliers for research and analytics design, more likely to expect supplier use to increase, and less likely to expect it to decrease. 

Those who say insights operations is the most important role also appear further along in institutionalizing technology. Formal AI guidelines are more common, expectations for AI use are clearer, and agentic AI use and expectations are somewhat higher.

Consequently, technology maturity and external supplier use may be complements rather than substitutes.

The broader business picture suggests they may have more resources to invest and more initiative to make these investments. Participants who name operations most important more often report increases in research spending, technology spending, insights staffing, and externally performed work. They are also more optimistic about their department or functional area. From this perspective, it is not clear whether complexity creates the need for an operations role or if the operations role creates the opportunity for a more sophisticated ecosystem.

None of this establishes what insights operations means, but it does suggest one possible manifestation.

Enablement and Harmonization, Not Necessarily Control

Insights operations may be less about administering research and more about creating an environment in which many different kinds of insights work can succeed. That could mean shared infrastructure, standards, governance, technology, workflows, access to external capabilities, enablement for non-specialists, or mechanisms that help otherwise independent groups work together.

This looks more like an “operating system” than “orchestration.”

An operating system does not decide what every application should do (or even what they are). It provides common infrastructure, protocols, resources, and rules that allow many independent applications to operate within the same environment.

Similarly, insights operations might enable and harmonize an ecosystem without controlling every participant in it.

That is only a hypothesis; “insights operations” may actually describe several substantially different roles or management approaches, and the differences we see could reflect multiple subgroups rather than one coherent model.

The next GRIT Business & Innovation research will explore these issues more directly. In particular, how centralized specialists, embedded experts, distributed non-specialists, and external resources coexist; how much autonomy and coordination exist among them; and what organizations actually mean when they talk about “insights operations.” Given that investigation, we might see “insights operations” more clearly as one implementation of system for enabling and harmonizing insights ensembles.

For now, GRIT sees enough evidence to suggest that there is no single way insights work is organized—and probably no single optimal way, either. The question is not whether everyone follows the same sheet music and executes exactly what the conductor dictates: it is whether the ecosystem enables them to optimize and harmonizes them to produce more than the sum of their parts.