By Hiran de Silva
If Excel is such an incredibly powerful tool—and if there’s no shortage of free tutorials, courses, and guidance on using its most advanced features—then why are Excel users typically paid so little? Why are Excel skills consistently found at the bottom of the technology pay stack, earning about a third of what other tech professionals make?
More perplexingly: why does mastering powerful Excel techniques not significantly shift how much you’re worth in the job market? Why doesn’t learning more Excel translate to higher pay?
To explore this paradox, we ran what we call the Gordon Ramsay Experiment—a way to reveal how Excel skills are perceived, misunderstood, and misapplied.
Mistaking the Tool for the Task
Let’s begin with a simple analogy: imagine you’re a carpenter faced with driving a screw into wood. You don’t have a screwdriver, but you do have a hammer. So you reach for the hammer and slam the screw into the wood. Anyone can tell you this is the wrong tool for the job. Not only does it fail to secure the screw properly, but it also damages the wood.
So why did you choose the hammer? Because you mistakenly associated nails and screws as similar enough to be treated the same, and confused the hammer’s function with that of a screwdriver. But the underlying mechanisms are completely different. One tool rotates and embeds; the other drives and impacts. A better alternative to the screwdriver might have been a table knife—not ideal, but far closer to the correct function than a hammer.
The lesson? It’s not enough to know that a tool exists. You need to understand the tool’s mechanism and purpose. The same goes for Excel. Many use it like a hammer when the job demands a screwdriver—and vice versa.
Presentation vs. Participation: A Critical Distinction
This brings us to a widespread confusion in today’s business software ecosystem: presentation tools like Power BI are often mistaken for participation tools like Excel. The result? Misleading comparisons and misguided decisions.
Let me illustrate with a common business process: month-end financial reporting.
When someone argues that Power BI is better than Excel, I ask them this: “Where does the dataset for your Power BI dashboard come from?”
The typical answer: “It’s just there.”
But it’s not just there. That dataset is the result of 7 to 10 days of coordinated effort—processes, journal entries, budget reviews, adjustments, reconciliations, and validations—performed by dozens, sometimes hundreds, of people across an organization. All this participation happens before the final dataset even becomes visible to Power BI.
And what is the tool most often used to carry out that work? Excel.
What Power BI Doesn’t Do
Power BI is a fantastic presentation tool. It takes clean, finalized data and presents it beautifully. But it does not participate in the workflows that create that data.
It doesn’t:
- Run collaborative budget review models
- Validate accounting entries against policy exceptions
- Allow budget holders to annotate draft numbers
- Execute financial modeling with custom business logic
All of that happens in Excel. When finance professionals across business units work together on schedules, adjustments, and forecasts, it is Excel doing the heavy lifting.
So when influencers say, “Power BI is better than Excel,” they’re mistaking the presentation layer for the entire process.
The Motor Car Analogy
Imagine looking at a brand-new car rolling off the production line. It’s beautiful, it drives well, and it’s ready for delivery.
Now imagine claiming that the finished car is all that matters—and dismissing the entire factory, the workers, the machinery, the design process, the parts suppliers, and the engineers who brought it into existence. That would be absurd.
But that’s exactly what happens when people praise Power BI and dismiss Excel. The “finished motor car” (i.e., the Power BI dashboard) only exists because of all the Excel-based processes that came before it.
You can’t drive a car that hasn’t been built—and you can’t publish a dashboard without a dataset that was created and refined using Excel.
So Why Are Excel Professionals Undervalued?
The problem lies in visibility and perception. Employers often don’t see the value-creating participation work that happens behind the scenes in Excel. They only see the polished final product—whether that’s a PowerPoint presentation, a PDF report, or a Power BI dashboard.
And because Excel is so ubiquitous and familiar, it’s misunderstood as a low-level, general-purpose tool rather than the participation engine it really is. This confusion fuels the perception that all Excel work is interchangeable—and commoditized.
But as we’ve shown through both illustration and real enterprise examples, Excel is essential infrastructure for organizational intelligence. It is not just a spreadsheet tool. It is the tool where collaborative, iterative, business-critical work takes place.
Conclusion: Presentation Is Not Participation
So let’s be clear:
- Power BI is a presentation tool.
- Excel is a participation tool.
Both are valuable. But they serve fundamentally different roles. The claim that Power BI is “better” than Excel collapses once you understand what happens between the raw data and the dashboard.
To mistake the Power BI dashboard for the full process is to admire a car without recognizing the factory. It’s to hammer a screw because it “looks like” the right approach.
Excel professionals deserve recognition—not just for what they build, but for the invisible work they perform to bring order, accuracy, and insight to an organization.
If you remove Excel from the picture, the process breaks down—and there’s no dashboard to show at the end.
So let’s stop making these flawed comparisons. Let’s stop mistaking presentation for participation. And let’s give Excel the strategic recognition it has long deserved.
ABSTRACT
This article explores the common undervaluation of Excel professionals despite the program’s critical role in data processes, contrasting it with the often-overstated importance of Power BI. It argues that Excel is primarily a participation tool, facilitating the collaborative creation and refinement of data, whereas Power BI serves as a presentation tool for finalized information. The author uses analogies to highlight how the visible output (like a Power BI dashboard) is often valued without recognizing the essential underlying work done in Excel. Ultimately, the piece advocates for greater recognition of Excel’s fundamental contribution to organizational intelligence.
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