The Jittery Red Dot and the Liturgy of Spreadsheets

The laser pointer is a jittery red dot dancing across the 25th slide of the morning, and the dust motes in the projector’s beam are the only things in this room moving with any real honesty. I am sitting in the third row, leaning back just far enough to avoid eye contact with the executive vice president, while my thumb scrolls through a thread of old text messages from 2015. It is a dangerous way to spend a Tuesday at 10:05, but the contrast is too sharp to ignore. On the screen, a series of bar charts in varying shades of corporate teal are supposedly ‘proving’ why we need to pivot our logistics strategy to a centralized hub. The presenter-a mid-level analyst who looks like he hasn’t slept more than 5 hours a night for a month-is explaining the standard deviation of our shipping times with the solemnity of a priest reading liturgy.

We spent 35 days on this. We pulled 105 separate datasets from five different legacy systems, scrubbed them, normalized them, and ran them through models that cost the company $5,555 in cloud computing credits alone. And yet, as I look at the back of my boss’s head, I know exactly what is happening. He had this idea during a scotch-heavy dinner in June. He didn’t need the 45-page report to decide; he needed the report to make the decision look like it wasn’t his fault if it failed. It is data-driven storytelling in its most expensive form, a meticulously crafted narrative designed to retroactively justify a gut instinct that was formed in about 15 seconds.

I’m Parker B., and as a disaster recovery coordinator, my job is usually to clean up the mess when the ‘data-driven’ projections hit the brick wall of reality. I deal in the aftermath of the spreadsheets. When a server room floods or a supply chain collapses because a model didn’t account for the 5% chance of a localized freak weather event, I’m the one on the phone at 3:15 in the morning. Reading these old texts from the 2015 server migration failure reminds me that the most important information never actually makes it into the slide deck. The texts are full of human panic, the smell of burnt plastic, and the frantic realization that the ‘optimized’ backup schedule we’d spent weeks calculating was useless because the physical keys to the backup vault were in a desk drawer 25 kilometers away in a locked building.

The Fetish for the Countable

We have developed a collective fetish for the quantitative. If it can be counted, it is considered true. If it can be visualized in a scatter plot, it is considered actionable. This creates a fascinating kind of corporate theater where we all pretend that the numbers are the primary actors, while the old power structures and emotional biases are merely the stagehands. In reality, it’s the other way around. The biases are the lead actors, and the data is just the costume department. We dress our fears and our ambitions in the garb of ‘objective analysis’ because, in the modern office, saying ‘I just have a feeling’ is seen as a professional weakness, whereas saying ‘The regression analysis suggests’ is seen as a sign of intellectual rigour.

I remember a specific instance where we were tasked with evaluating the efficiency of our remote response teams. We gathered 65 different metrics, from response latency to ticket resolution speed. The data was clear: Team B was 25% faster than Team A. On paper, the decision was obvious. We should move more resources to Team B and perhaps phase out the leadership of Team A. But when you actually went into the field-when you actually stood in the mud and watched these people work-you realized that Team A was slower because they were the ones who actually fixed the underlying problems. Team B was just ‘closing tickets’ by applying temporary patches that would break again in 15 days. The data was recording the speed of the band-aid, not the healing of the wound.

This is the danger of the abstraction. When we move further away from the physical reality of the work, we become more susceptible to the illusions that numbers provide. It is a comfortable lie. It allows us to make hard decisions-like layoffs or budget cuts-without having to look at the human cost, because the numbers told us to do it. We outsource our morality to the algorithm. I’ve seen managers who couldn’t tell you the names of 5 people on their team, but they could tell you the exact ‘utilization rate’ of their department down to the decimal point.

Beyond the CSV: The Honesty of Experience

It’s a strange contradiction to live in. I rely on data to monitor system health, yet I distrust it as a tool for visionary decision-making. There is a specific kind of arrogance in thinking that a complex human system can be fully captured in a CSV file. We ignore the ‘dark data’-the hallway conversations, the subtle shifts in morale, the intuitive sense that a project is doomed despite what the green status lights on the dashboard say. I find myself increasingly drawn to things that can’t be faked by a pivot table. There is a profound honesty in physical exertion and firsthand experience that the corporate world has largely forgotten.

You see this clearly when you step away from the glowing screens and the climate-controlled boardrooms. If you are planning a journey, you can look at topographical maps and weather charts for 35 hours, but that won’t tell you how your knees will feel on the third day of a steep ascent. There is a massive difference between the data of a trail and the experience of walking it. This is why I appreciate the approach of organizations like Hiking Trails Pty Ltd, where the emphasis remains on the lived experience and the tangible reality of the path under your boots. You don’t need a chart to know you’ve covered the distance; the ache in your calves and the clarity in your head are the only metrics that actually matter.

The Ultimate Insurance Policy: Accountability Nullified

Back in the meeting, the analyst has moved on to Slide 35. He’s showing a ‘heat map’ of potential risks. It’s a vibrant patchwork of reds and yellows. My boss nods sagely, as if he’s absorbing profound insights, but I can see him checking his watch. He’s already thinking about his 12:45 lunch. The data hasn’t changed his mind about anything; it has merely provided him with a shield. If the centralized hub fails, he can point to this presentation and say, ‘The data supported the move.’ It is the ultimate insurance policy against accountability.

I think about the texts from 2015 again. One of them, from a guy named Dave who left the company 5 years ago, just says: ‘The numbers don’t matter if the room is on fire.’ It’s the most honest thing I’ve read all week. In disaster recovery, we talk a lot about ‘Resilience,’ but resilience isn’t found in a database. It’s found in the ability of people to ignore the plan when the plan no longer fits the reality. It’s the capacity to trust your eyes over the dashboard.

Information vs. Wisdom

We are currently living through a period where we are drowning in information but starving for wisdom. We have more ‘insights’ than ever before, yet we seem to make the same 5 or 15 fundamental mistakes over and over again. We prioritize the measurable over the meaningful because the measurable is easier to defend in a performance review. But the meaningful is where the actual value lives. It’s in the relationships that don’t show up on an org chart and the expertise that can’t be captured in a training manual.

As the presentation finally winds down, there is a polite smattering of applause. The lights come up, and the spell is broken. The blue glow of the projector fades, and we are just people in a room again, squinting against the sudden brightness. My boss stands up, claps the analyst on the shoulder, and says, ‘Great work. This confirms exactly what I was thinking.’

He says it without a hint of irony. He truly believes that he has been led by the data, rather than the data being led by him. I gather my things, feeling that familiar weight of cynical exhaustion. I have 55 unread emails waiting for me, most of them containing attachments full of more charts, more graphs, more ‘proof’ of things we already know or things that aren’t true.

The Month Without Charts

I wonder what would happen if we just stopped. If for one month, we weren’t allowed to use any charts. If we had to make decisions based on what we saw with our own eyes and what we heard from the people actually doing the work. The ‘theater’ would collapse, of course. We might find ourselves feeling exposed, standing there without our spreadsheet shields. But we might also find ourselves making decisions that actually work, rather than decisions that just look good on a slide.

I walk out of the room, past the 5 empty coffee cups left on the side table, and head toward the stairwell. I need to feel the floor beneath my feet and the air in my lungs. I need something that isn’t a projection. I think I might take a long walk this weekend, far away from any cell service or ‘data-driven’ insights. Just 25 kilometers of dirt and rock. No slides, no dashboards, just the truth of the trail and the reality of the distance. Does the data say that’s a good use of my time? I don’t know, and for the first time in 35 days, I really don’t care.