Your Work Is Being Measured in the Shadows

Simon Carver

[warmly] Welcome to the show. This one is called How Big Brother Is Watching—and You May Not Even Know It. If this kind of conversation helps you make sense of modern work, like, share, and subscribe, and as always I’m here with Lachlan Reed. Lachlan, I keep coming back to this image: every email, every Teams reply, every meeting you accept or decline, every document you touch—or don’t touch—throws off a kind of behavioral dust. And that dust doesn’t just settle. It gets collected.

Lachlan Reed

[skeptical] Yeah, “behavioral dust” is a beauty of a phrase, mate, because it sounds harmless till you realize it’s more like footprints in wet cement. Once it’s there, it sticks. In tools like Microsoft 365, all that everyday admin of work—calendar, chat, docs, email—can become a data shadow of how you behave, not just what you deliver.

Simon Carver

And that’s the twist, right? These platforms started life as hammers and screwdrivers. Useful tools. But in practice they can also become telemetry systems. Not just “did the work get done?” but “how often did you respond,” “how many people did you interact with,” “how visible were you while doing it?” It’s like your office badge suddenly also became a fitness tracker for your professional life.

Lachlan Reed

[responds quickly] “Responsiveness” is the one that gets me. That word sounds tidy, almost noble. But if I’m doing deep work—say I’m buried in a gnarly piece of analysis for three hours, no chats, no meetings, no little thumbs-up in Teams—some systems can read that as low engagement. That’s like judging a mechanic by how often he waves from under the bonnet instead of whether the engine starts.

Simon Carver

[questioning tone] Wait—“three hours, no chats” is exactly the example that lands for me. Because to a human manager, three focused hours on something complex might be the MOST valuable part of your week. To an activity dashboard, it can look like silence. And silence, in a lot of systems, gets interpreted as absence.

Lachlan Reed

Too right. And the problem is these metrics often aren’t context-aware. They don’t understand strategic thinking. They don’t understand role differences. They don’t understand that one job needs constant chatter and another needs long stretches of proper concentration. They see patterns, then they score the patterns. Even a kangaroo could trip over that logic.

Simon Carver

[reflective] Let me try to say it back. If I’m the person constantly firing off messages, joining every meeting, commenting in every shared doc, I might look “collaborative.” But if you’re the person solving the difficult problem that makes all those meetings unnecessary next month, you might look... quiet. So the visible worker can outscore the valuable worker.

Lachlan Reed

[short pause] Almost. Not always—but enough that it should make people sit up. Because the system isn’t asking, “Was this excellent?” It’s asking, “Was this detectable?” And detectable is not the same thing as useful. That’s the bit that gives it teeth.

Simon Carver

[calm] Once you start scoring detectability, it gets slippery fast. Collaboration scores. Responsiveness indicators. Focus-time versus meeting-time ratios. After-hours activity patterns. Cross-functional engagement levels. On paper, those sound like neutral management tools. In real life, they can start feeding reviews, promotions, and—when times get ugly—workforce reductions.

Lachlan Reed

[matter-of-fact] Yeah. Once you’re scored, you can be ranked. Once you’re ranked, you can be compared. And once you’re compared, you’re part of a decision model. Maybe nobody in a room ever says, “Lachlan’s not valuable.” Instead they say, “The data suggests lower engagement.” Same punch in the teeth, just with a spreadsheet doing the swinging.

Simon Carver

“The data suggests”—that phrase is so slippery. It sounds objective, almost innocent. But it can hide a chain of assumptions. Maybe your role is supposed to be heads-down. Maybe the project was complex. Maybe the best work happened in thinking, not typing. An algorithm can count signals. It cannot, by itself, understand meaning.

Lachlan Reed

And it definitely can’t feel context. If someone’s after-hours activity is high, what does that mean? Are they committed? Overloaded? In a different time zone? Bad at setting boundaries? Looking after kids all day and working late? The raw signal is the same. The story behind it is wildly different.

Simon Carver

[curious] The after-hours one really sticks with me. Because “8:47 p.m.” can mean diligence to one manager and dysfunction to another. Same timestamp, completely different verdict. That’s where human judgment still matters.

Lachlan Reed

Exactly. Human judgment can ask, “What’s their role? What were they trying to do? What outcome did they create?” A context-blind score just says, “Here’s the pattern.” And leaders under pressure—cost pressure, efficiency pressure, justify-yourself-with-data pressure—can lean on that because it’s convenient. Fast, neat, scalable. Bit like using a shifter as a hammer. Wrong tool, still swings.

Simon Carver

[softly] Here’s the awkward truth I don’t think enough people say out loud: most workers have no idea what’s being measured behind the scenes. Not specifically. They know, vaguely, that systems collect data. But they don’t know which patterns matter, how those patterns are interpreted, or whether context ever gets added back in. That uncertainty changes how a workplace feels.

Lachlan Reed

[reflective] Yeah... and I reckon that’s the creepy bit without needing any tinfoil hat stuff. It’s not a conspiracy. It’s convenience at scale. Companies want cleaner dashboards and faster decisions. Fair enough. But if you’re being translated into metrics you can’t see, or can’t challenge, you’re basically being reviewed through frosted glass. Someone can make out your shape, but not your actual work.

Simon Carver

And when the glass is frosted, false narratives grow easily. “Not collaborative enough.” “Slow to respond.” “Low visibility.” Those labels can harden before anyone asks whether they’re true.

Lachlan Reed

[energized] So let’s get practical, because listeners can’t exactly wander into the server room and unplug the thing. First: understand your digital footprint. Email activity, calendar usage, Teams engagement, document collaboration—those are the bread crumbs. Don’t fake busyness, but do be strategic about being visible where your work already lives.

Simon Carver

“Strategic, not artificial” is the key phrase there. Because the answer is not to become one of those people who sends five pointless updates a day just to create movement. That’s like revving a parked car so the neighbors think you went somewhere. What you want is a clear trail that connects effort to contribution.

Lachlan Reed

Spot on. If you spend long stretches in deep work, balance that with visible check-ins. Share progress in a Teams channel. Drop a short update in the shared tool. Note a milestone in the document itself. You’re not gaming the system—you’re giving your work a bit of signage so nobody drives past it.

Simon Carver

And use the tools yourself. Viva Insights, MyAnalytics—those kinds of dashboards aren’t only for employers. Look at your own patterns. Are you appearing disengaged unintentionally? Are meetings swallowing your week? Is your collaboration pattern skewed so far inward that nobody outside your immediate team can see your impact?

Lachlan Reed

[chuckles] Yeah, have a squiz before someone else does. And then document outcomes, not just activity. Keep a clean record of what changed because of your work. What problem got solved? What decision got improved? What business goal did your output support? Data without context is dangerous, so hand over the context.

Simon Carver

I’d add one more layer: build HUMAN visibility, not just digital presence. Algorithms do not promote people. People promote people. People advocate. People remember who made a hard project easier, who clarified a messy issue, who delivered something solid when it mattered. So yes, be legible to systems—but make sure real humans can tell the story of your value too.

Lachlan Reed

And if something feels off, ask professional questions. Simple ones. “What metrics are being used to evaluate performance?” “How is collaboration being measured?” “How is context incorporated?” That’s not being difficult. That’s basic self-protection. If they’re gonna weigh the bike, you’re allowed to ask what scale they’re using.

Simon Carver

[warmly] That may be the whole heart of it. You do not need to game the system. But you do need to understand the system well enough to stay understandable inside it. Because the future of work is going to involve more analytics, more automation, more behavioral insight. That part is not going away.

Lachlan Reed

[softly] The real question is whether workers learn how they’re being measured before the system measures them incorrectly. That’s the race, hey.

Simon Carver

If this resonated, share it with someone who works inside one of these platforms every day, and subscribe so you don’t miss the next one.

Lachlan Reed

[warmly] Good on you for listening. Stay sharp, stay human, and we’ll catch you next time.