Lab managers are a pivotal and essential part of any research organization and should, by rights, have an unparalleled level of strategic influence. They know their labs and the people in them, they know how they operate, and they know what activity is taking place on any given day, week, month, or year.
But when it comes to discussions about equipment investment, divestment, or reallocation, lab managers are not always afforded the level of influence they deserve. This happens because they often lack the hard, structured data needed for these discussions.
Why does this happen? From my conversations with lab managers and lab operations professionals around the world, it’s typically a combination of intense, multidisciplinary workloads, combined with difficulty in gathering this data in the first place.
The invisible pressures driving equipment decisions
From the outside, equipment decisions can seem straightforward, though they rarely are. Certain instruments might appear oversubscribed because a particular team has a major deadline, others might seem underused because one group relies on them and protects them from use by others, and others still might seem redundant when, in fact, they’re simply broken down because of untrained usage. Based on what I often hear, equipment purchasing decisions are regularly made without much data at all. Lab managers will often find themselves piecing together anecdata, incomplete shared calendars or spreadsheets, and whatever information happens to be volunteered by the most assertive teams or individuals, which is to say: arguments are often won by those who shout the loudest.
Against this backdrop, lab managers are left to navigate a complex environment where the tools for capturing usage are often inconsistent or inaccurate. When scientists are under pressure, collecting or maintaining detailed logs understandably drops down the priority list.
But lab managers are the ones asked to explain usage, justify purchases, and decide when repairs are needed. They become the point of escalation when budgets tighten or when instruments fail and are expected to provide clarity in situations where the available information is anything but clear.
So, how should any lab manager attempt to divine the truth in these situations? It all boils down to the accuracy, depth, and ease of access to their usage data.
Organizational hierarchy versus operational influence
The absence of structured usage data affects more than the decisions about certain assets. It has a significant impact on the influence lab managers have within their organizations.
It’s important to mention that influence is not always about hierarchy. Rather, it comes from people trusting that you have visibility into how the lab actually works, with the data to support you. When lab managers can make the case for or against an investment using clear usage patterns, they speak from a position of authority, and their recommendations carry weight because they are based on evidence that others can also see and understand.
But when the data is incomplete or inconsistent, the conversation shifts from evidence to argument, and decisions begin to reflect who feels strongly about a particular instrument, who has a persuasive story, or who has seniority. Lab managers may implicitly know that an asset is underused or that a requested purchase isn’t justified, but without trustworthy data, it’s harder to push back than it needs to be.
What structured usage data changes
When labs begin to capture usage data more accurately and consistently, the tone of these discussions shifts, and patterns that once seemed anecdotal are held to a higher standard: high-demand instruments can be distinguished from those that only feel busy because bookings are inconsistent, while underused assets that, for example, regularly require maintenance and calibration become easier to identify. In short, the assumptions that drive investment conversations can be tested against real data and challenged where needed.
The lab managers I speak to often describe this kind of change as a key turning point. They no longer have to rely on persuasion alone and can show how often an instrument was used, who was using it, who wasn’t, when demand spikes or troughs occurred, and whether redistribution would relieve pressure without new purchases. It’s this kind of clarity that greatly helps to increase the confidence that others have in their recommendations.
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Increasing influence through data clarity and granularity
Perhaps the most important shift is the one in perception. When structured, accurate usage data is introduced into discussions about equipment decisions, this creates a more strategic posture by default. Leadership begins to see recommendations as evaluations grounded in reality rather than simply preferences. Likewise, lab users quickly come to understand that decisions about equipment are based on real-world requirements rather than persuasion.
The influence that comes from this clarity is therefore earned, not granted. It grows because the quality of decision-making improves, because the rationale behind those decisions is visible to others, and because the data reflects the way the lab actually operates. It becomes far easier for lab managers to advocate for what their labs need as a result.
Turning lab equipment usage data into organizational confidence
No one working in a lab expects completely perfect operational information. The problem is that lab managers are often asked to make high-stakes decisions without enough visibility to properly defend them. This is an unreasonable position to be placed in, and it limits the ability of any lab manager to shape the decisions that define how their labs operate.
Structured usage data begins to level that playing field and helps increase the strategic influence that a lab manager can have. It doesn’t necessarily simplify the job, but it does reduce guesswork and gives lab managers the ability to speak with clarity, removing the pressure to rely on negotiation when evidence is missing. When the data reflects the real conditions of the lab, their voice becomes harder to overlook—and that is where influence truly starts to grow.
