Killing Sacred Cows, Part 4: The Research Enterprise Is Powered by Invisible Labor

Killing Sacred Cows — Part 4 of a series examining the unspoken norms, taboos, and protected assumptions in academic research that are rarely questioned, even when they undermine effectiveness and resilience. This series names those assumptions, puts them up for debate, and asks whether they still deserve protection. Parts 1: Staff Should Not Report to Faculty  Part 2: We Can't Train What We Can't Define Part 3: Research Matters and We Could be Doing it Better

Perhaps the closest popular culture has come to illustrating the invisible work that sustains complex research systems is the 2016 film Hidden Figures. Based on a true story, it brings to life three African American women who worked as mathematical “computers” at NASA, performing calculations so foundational to the space program that failure was not an option, yet whose labor remained largely unseen. It is a useful analogy for understanding how modern research enterprises actually function.

Invisible Work Is Not Accidental

There is little public understanding of how research happens inside universities, and even less appreciation for the volume of invisible labor required to make it possible. More surprisingly, many faculty investigators - despite their deep expertise and responsibility - are only partially exposed to this reality. Not because they are uninterested, but because the system is structured to shield them from it.

Faculty are rarely encouraged to understand the full context in which they operate: a densely regulated environment governed by federal statutes, agency-specific policies, institutional risk frameworks, and compliance regimes whose consequences often surface long after decisions are made. In practice, this complexity is not eliminated or brought into the light of day; it is absorbed. Research administrators and staff function as the human integration layer, continuously reconciling rules that were never designed to coexist so that research can proceed without interruption.

From Rules to Judgment

This distinction matters: the research enterprise does not run on compliance with rules. It runs on judgment; on people who translate abstract, conflicting, and shifting requirements into workable decisions in real time. When that labor is treated as infinite or interchangeable, the system becomes breakable. Work does not disappear; it concentrates. Risk does not vanish; it migrates.

Over time, this manifests as burnout, turnover, and loss of institutional memory - outcomes that are often misdiagnosed as individual performance issues rather than structural design failures. When experienced staff leave, they take with them not just knowledge of policies, but the unwritten understanding of how those policies interact, where flexibility exists, and where it does not. The cost is not merely operational inefficiency; it is increased institutional exposure and reduced resilience.

Why Workload Visibility Matters

If more faculty understood the environment in which research administration operates, as in what is constrained by regulation, what is shaped by institutional risk tolerance, and where discretionary judgment carries downstream consequences, I believe we could move beyond the implicit and crude expectation that staff will simply “handle it.” That understanding creates space for better questions: What is actually feasible? Where are trade-offs being made? And what work is being hidden to preserve the appearance of smooth operations?

This is why workload management in research administration is not a secondary or technical concern; it is a strategic one. As my colleague Lacey Rhea has articulated, accurate workload assessments are essential for understanding capacity, prioritization, and sustainability within research organizations. Without them, invisible labor remains…invisible, and institutions continue to make decisions based on incomplete information.

Without a clear view of the work being done, institutions cannot meaningfully assess workload, risk, or sustainability, which means they can’t respond to change and opportunities.

If we're challenging assumptions let's ruminate on some final questions.

• What is the institutional cost of relying on people to absorb complexity instead of fixing the systems that create it?

• What does “efficiency” mean when it is achieved by transferring cognitive load to individuals rather than improving systems?

• At what point does invisible labor become institutional fragility?

• Who benefits when complexity remains hidden and who pays the price?

The system map that follows makes this reality explicit. It shows the layered rule environment surrounding a single research award and the central role played by the people who hold those layers together. Its purpose is to clarify constraints, surface hidden work, and create a shared understanding of what the system actually requires to function.