The cursor is a rhythmic hammer, beating against the white void of Cell AR107. It is 11:07 PM. The office air conditioning has shifted into its ghostly night-mode, a low-frequency hum that makes the teeth ache. I am not currently calculating the future; I am performing an exorcism on the present. My boss, a man who views spreadsheets as choose-your-own-adventure novels, has been very clear: the project needs to show a seventeen percent return on investment by Monday morning. If it does not, the ‘strategic initiative’-which he has already bragged about to the board-will look like a 377-million-dollar mistake. My current model, grounded in the stubborn soil of actual market data, is gasping at a miserable four percent.

I reach for the levers of the fictional world. I adjust the ‘customer acquisition cost’ down by a mere seven cents. I nudge the ‘upsell probability’ from zero-point-two to zero-point-seven. The numbers dance. The ROI climbs. This is the ROI Theater, a silent play where the script is written in formulas and the ending is decided before the curtain ever rises. We are not using data to make decisions. We are using data to perform a ritual of validation for decisions that were made in a steakhouse three weeks ago.

The Unyielding Reality of Structural Integrity

Consider Natasha J.-C., a woman I met once at a transit conference. She is a bridge inspector. Her world is made of rivets, tension, and the cold, unyielding reality of structural fatigue. When Natasha J.-C. crawls into the hollow of a steel box girder, she is not looking for a way to justify the bridge’s existence. She is looking for the 27-millimeter crack that might send ten thousand commuters into the river. She counts the 47 corroded bolts. She measures the salt ingress. If she were to ‘tweak’ her data to please the mayor, people would die. In her world, the numbers have weight. In mine, they are as light as the air in a marketing pitch.

We have entered an era where data has been weaponized against the truth. It sounds like a contradiction, but it is the daily bread of the corporate analyst. We collect petabytes of information, not to explore the landscape, but to find the specific pebbles we can use to build a wall against criticism. We call it ‘data-driven,’ but it is actually ‘conclusion-led.’ We start with the answer-‘This project is a success’-and work backward until we find the variables that allow that sentence to exist without the spreadsheet turning red.

This practice is corrosive. It doesn’t just produce bad projects; it destroys the internal compass of the organization. When everyone knows the ROI is a fiction, the numbers lose their ability to signal danger. We ignore the 137 red flags because we’ve been trained to paint them green for the quarterly review. We become an organization of bridge inspectors who have been told that rust is just a ‘vintage aesthetic’ that helps the bridge blend into the sunset.

The Forger’s Shame

I felt the same shame I imagine a forger feels when they add a fake signature to a masterpiece. This is why I find myself increasingly drawn to the philosophy of systems that don’t allow for this kind of creative editing. There is a desperate need for architectural integrity in our digital lives. We need a way to look at the world that doesn’t involve a filter designed to make us look more profitable than we are. When I think about the work of Datamam, I perceive a different path. It is the path of building systems that reveal the objective truth, even when that truth is inconvenient, ugly, or points toward a ‘no’ when everyone is shouting ‘yes.’

True data science should be more like Natasha J.-C.’s bridge inspection and less like a Broadway production. It should be about finding the 67 points of failure before the structure collapses. If we continue to treat data as a tool for political air cover, we will eventually lose the ability to distinguish between a thriving business and a 237-story house of cards. The cost of ‘finding the data’ to support a bad decision is much higher than the project itself; it is the cost of our collective sanity and the eventual erosion of trust.

The Honesty of the Spice Rack

I look at the spice rack again when I get home at 1:07 AM. It is the only thing in my life that makes sense. The Paprika is exactly where it should be. It doesn’t try to pretend it’s Saffron just because I’m making a paella and don’t want to go to the store. It is honest. It is what it is. I wish I could say the same for the projections I just uploaded to the shared drive.

We are currently trapped in a cycle where the person who brings the most ‘positive’ data wins the promotion, while the person who brings the most ‘accurate’ data is labeled a cynic or ‘not a team player.’ We’ve created an ecosystem that rewards the 87 percent of analysts who are willing to massage the numbers until they scream ‘success.’ We need to start rewarding the people who have the courage to say, ‘The bridge is failing, and no amount of spreadsheet manipulation will make it stand.’

I think back to my last project before this one. We spent 57 days arguing over a single metric. Not because the metric was hard to calculate, but because it didn’t tell the story the board wanted to hear. We spent more time debating the definition of ‘active user’ than we did actually building the product for the users. By the time we finished the ‘ROI Theater,’ the market had already moved on. We had a perfectly justified, data-supported, board-approved failure.

The Desire for Unbreakable Models

What would happen if we stopped? What if we walked into the boardroom and said, ‘The ROI is unknown, but the structural necessity is 100 percent?’ What if we admitted that we are making a gut-feeling bet and we are using the data to track our progress rather than to justify our start? It would be terrifying. It would require a level of vulnerability that most corporate cultures find allergic. But it would also be honest.

Natasha J.-C. told me once that she loves the cold wind on the high spans of the bridge. It reminds her that she is part of the world, not just an observer of it. The wind doesn’t care about her report. The steel doesn’t care about the budget. There is a liberation in the unyielding. I want to find that liberation in my spreadsheets. I want to build a model that I can’t break with a nudge of a variable. I want to reach a point where I don’t need to alphabetize my spices to feel like something in this world is true.

The Final Cost

But as I walk to my car, I can’t help but look at the overpass above me and hope, with a sudden and sharp intensity, that Natasha J.-C. was the one who inspected the rivets. I hope she didn’t feel the need to tweak the data. I hope she didn’t have a boss who needed the rust to disappear to save his reputation. In a world of fiction, we are all eventually at the mercy of the facts we chose to ignore.

We’ve created an ecosystem that rewards the 87 percent of analysts who are willing to massage the numbers until they scream ‘success.’ We need to start rewarding the people who have the courage to say, ‘The bridge is failing, and no amount of spreadsheet manipulation will make it stand.’ It’s not just about the money. It’s about the soul of the work. When we lie to ourselves with numbers, we lose the capacity for genuine surprise. We close our eyes to the unexpected opportunity because it doesn’t fit the pre-approved ROI model. We miss the 7-percent outlier that could have been the next billion-dollar idea because we were too busy forcing the existing idea to look like a safe bet.

I think back to my last project before this one. We spent 57 days arguing over a single metric. Not because the metric was hard to calculate, but because it didn’t tell the story the board wanted to hear. We spent more time debating the definition of ‘active user’ than we did actually building the product for the users. By the time we finished the ‘ROI Theater,’ the market had already moved on. We had a perfectly justified, data-supported, board-approved failure.

What would happen if we stopped? What if we walked into the boardroom and said, ‘The ROI is unknown, but the structural necessity is 100 percent?’ What if we admitted that we are making a gut-feeling bet and we are using the data to track our progress rather than to justify our start? It would be terrifying. It would require a level of vulnerability that most corporate cultures find allergic. But it would also be honest.

Finding Liberation in the Unyielding

Natasha J.-C. told me once that she loves the cold wind on the high spans of the bridge. It reminds her that she is part of the world, not just an observer of it. The wind doesn’t care about her report. The steel doesn’t care about the budget. There is a liberation in the unyielding. I want to find that liberation in my spreadsheets. I want to build a model that I can’t break with a nudge of a variable. I want to reach a point where I don’t need to alphabetize my spices to feel like something in this world is true.

As the sun begins to hint at the horizon at 5:07 AM, I finally close the laptop. The ROI is 17.7%. The boss will be happy. The project will be green-lit. The theater will continue for another season. But as I walk to my car, I can’t help but look at the overpass above me and hope, with a sudden and sharp intensity, that Natasha J.-C. was the one who inspected the rivets. I hope she didn’t feel the need to tweak the data. I hope she didn’t have a boss who needed the rust to disappear to save his reputation. In a world of fiction, we are all eventually at the mercy of the facts we chose to ignore.

We are currently trapped in a cycle where the person who brings the most ‘positive’ data wins the promotion, while the person who brings the most ‘accurate’ data is labeled a cynic or ‘not a team player.’ We’ve created an ecosystem that rewards the 87 percent of analysts who are willing to massage the numbers until they scream ‘success.’ We need to start rewarding the people who have the courage to say, ‘The bridge is failing, and no amount of spreadsheet manipulation will make it stand.’ It’s not just about the money. It’s about the soul of the work. When we lie to ourselves with numbers, we lose the capacity for genuine surprise. We close our eyes to the unexpected opportunity because it doesn’t fit the pre-approved ROI model. We miss the 7-percent outlier that could have been the next billion-dollar idea because we were too busy forcing the existing idea to look like a safe bet.