Harder, Better, Faster, Stronger?

There is something defiant about a string quartet. (Bear with...)

Around 1787, Wolfgang Amadeus Mozart wrote a piece for four musicians that takes roughly twenty-five minutes to perform. Two violins, a viola, a cello. Twenty-five minutes then, twenty-five minutes now. No shortcuts have been discovered. No one has successfully suggested removing the viola to “streamline delivery.”

You can digitise the sheet music. You can optimise the ticketing. You can even improve the chairs. But when the music starts, time resumes its original shape.

This irritated the economist, William Baumol.

Not the music itself - he was perfectly fond of that - but the economics of it. Because while the quartet hadn’t become any faster, the cost of hiring those four musicians had steadily risen. Not because they were playing better or quicker, but because the rest of the world had moved on. Factory workers produced more. Engineers built faster. Entire industries accelerated. And if the quartet didn’t keep up, the cellist would eventually wander off to become a software developer (no offence to developers).

This is what Baumol called the cost disease: sectors where productivity stubbornly refuses to improve still become more expensive, simply because everything else does.

Once you notice it, it appears everywhere.

A teacher still teaches a class. A haircut still takes as long as it always has. The tools around them have improved enormously. The work itself resists compression.

And interestingly, the people doing these jobs haven’t become cheaper as a result of better tools. Quite the opposite. The tools have made them more valuable, not less.

Which brings us, somewhat improbably, to procurement.

Four suppliers. A contract worth north of £15 million. Twelve hundred pages of documentation scattered across Excel, PDFs, and Word files - each one structured just differently enough to resist comparison. Pricing models that don’t quite align. Assumptions tucked into footnotes like afterthoughts. One finance director, two weeks, and a board that would quite like a clear answer.

In theory, this is a three-week job.

In practice, very little of that time is spent thinking.

Most of it is spent doing something closer to archaeology. Extracting numbers. Rebuilding tables. Translating one supplier’s logic into another’s format. Creating, from fragments, something that can be compared without accidentally misleading everyone in the process.

Only once that’s done does the actual work begin.

This is where AI enters the story, usually wearing the slightly overconfident expression of someone who believes they can play the cello after watching a YouTube tutorial.

And to be fair, it can help. We processed the 1,200 pages in under 48 hours. Standardised the formats. Extracted the key data. Surfaced the obvious differences.

But raw processing is not understanding. It’s typesetting.

If you give most AI systems four proposals, they will give you back a beautifully organised comparison of those proposals. Every number in its place. Every table aligned. The analytical equivalent of a perfectly tuned instrument - waiting, rather awkwardly, for someone to actually play it.

Because something is missing.

Context.

Not the kind you can scrape from a document, but the kind that accumulates quietly over years. What “normal” looks like in stadium catering. What staffing ratios tend to hold under pressure. What growth rates are ambitious versus quietly implausible. The difference between a clever assumption and a dangerous one.

So before any documents were processed, we built that context around the problem. Benchmarks. Ratios. Ranges. The invisible scaffolding that experienced people carry in their heads without ever writing down.

In other words, we gave the AI something to disagree with.

And that’s when it became interesting.

One supplier appeared to be the most competitive on price. Clean numbers, sensible structure. But something felt off - not in the totals, but in the shape of them. The AI flagged a discrepancy: staffing levels were around 40% lower than the others.

Buried in the assumptions was the explanation. They weren’t under-staffing. They were simply expecting the client to provide a significant portion of the workforce.

Perfectly reasonable - if you happen to notice it. Less so if you don’t. The headline price remained attractively low. The hidden cost, less so.

Another proposal projected 15% annual growth in a market that tends to hover somewhere between five and seven. Not impossible. Just... optimistic in the way that tends to become expensive later.

Neither issue was concealed. But neither announced itself, either.

Without context, they pass straight through the system - immaculately processed, beautifully presented, and entirely unchallenged.

Like a recording of a concert that sounds flawless until someone asks a question the recording cannot answer.

The decision, in the end, still belonged to the finance director. That part doesn’t compress. Judgment rarely does.

But everything leading up to it had changed shape.

Instead of three weeks spent assembling something usable, the work arrived already structured, already interrogated. The anomalies surfaced. The assumptions stress-tested. The noise reduced to something closer to signal.

For the first time, the human part of the process - the part that actually matters - had room to breathe.

Baumol was right, of course. Some work resists acceleration. A quartet still takes twenty-five minutes. A conversation still takes as long as it takes. A decision, properly made, refuses to be hurried.

But what he couldn’t quite see, standing in the late twentieth century, is that you don’t have to speed up the performance to change the experience of it.

You can compress everything around it.

Preparation. Translation. Reconstruction. The noiseless, necessary friction that so often consumes the very people you rely on to think clearly.

Which leads to a different question - not which roles can be replaced, but what knowledge sits inside them, unspoken, and what happens when it leaves.

Because context is not a feature. It’s not something you install or switch on. It accumulates. Slowly, unevenly, often invisibly. Every decision adds to it. Every mistake refines it.

Strip it away, and you’re left with information that looks complete but understands nothing.

Build it deliberately, and something else happens.

Baumol showed that some work doesn’t speed up.

What’s new is our ability to stop mistaking everything surrounding it for the work itself.

Read the companion piece: The Intelligence AI Can’t Replicate

The Contour is published by Context is Everything. If you’ve got a decision buried under a thousand pages of documentation, we should probably talk.