Ask a room of CFOs, data analysts and admin assistants the same question — what’s the one app you can’t live without? A large share will point to the same green grid: Excel. Forty years after its debut, it’s still the lingua franca of business data: quick lists, ad-hoc charts, million‑row models and the occasional piece of fragile infrastructure that keeps payroll, budgets or recruitment running.
We shouldn’t be surprised. Excel is fast where it counts. Its recalculation engine and desktop performance let complex sheets feel responsive in ways many web apps don’t. People also learn it early — it’s taught in schools and expected on résumés — so a spreadsheet becomes a shared language across generations and job grades. That cultural network effect is huge: hand someone an .xlsx and they speak the same shorthand, even if they mean something entirely different by a column label.
Why businesses can’t quit the grid
There are three practical reasons Excel persists.
- Flexibility: The grid is a blank canvas. Need to prototype a pricing model, flag exceptions on an invoice run, or build a one-off reconciliation? Excel is immediate and forgiving. You don’t need a ticket to IT or a new app to test an idea.
- Backward compatibility: Companies still open spreadsheets created decades ago. That continuity matters more than novelty when long-lived financial logic or audit trails are at stake.
- Shadow IT and low‑code power: Because Excel is effectively Turing‑complete for many use cases, legions of “accidental programmers” build processes on top of it — macros, pivot tables, Power Query flows and bespoke formulas that replace whole department tools.
That power, however, carries risk. Poorly documented macros, spreadsheets living on individual laptops, and half-baked copy‑and‑paste workflows create fragile single points of failure. Public embarrassments — from recruitment mishaps to government finance problems that boiled down to spreadsheet chaos — are reminders that the convenience of the grid sometimes hides structural fragility.
The human trade-offs: control versus scale
Moving off Excel is as much a social problem as a technical one. When a company rolls out a centralized planning system, teams often try to keep their beloved sheets as a comfort blanket. It’s not just nostalgia: people feel they understand their numbers because they built the model. But that illusion of ownership can sabotage efforts to create cleaner, centralized data streams that feed analytics and AI.
Wider adoption of better tooling can save money and speed decision-making — but it requires enforcing new habits. Some leaders take the blunt route: don’t let spreadsheets coexist with the new platform. Others gradually migrate processes, re‑teaching teams to think in standardized data rather than bespoke workbooks.
Lessons from the champions and the engineers
If you want to get better at Excel, the advice from top practitioners is blunt and useful: believe there’s a better way. Repetitive manual work usually has a formulaic fix — SUMIFS, Power Query, or a macro can turn a 30‑minute slog into a repeatable two‑minute task. That initial time investment rewards you exponentially over months and years.
At the same time, engineers point out why Excel endures: it adapts. Over the last decade Microsoft has layered heavier data‑handling capabilities into the product — things like Power Query for ETL, Python integration for data science, and AI features to help automate routine tasks. The company’s broader push into AI — visible in its own model work and image/model initiatives — signals that Excel will keep morphing as the wider productivity stack embraces machine learning. See how Microsoft is investing in in‑house AI development with Microsoft’s MAI‑Image‑1, and how search and document grounding are shifting into deeper AI workflows via Gemini Deep Research.
The Excel World Champion’s simple counsel fits here: learn the right tools and step back. Fast execution matters, but the step back — asking whether an outcome makes sense and communicating the insight — is what separates a good spreadsheet user from a trusted analyst.
A pragmatic path forward
Treat Excel as both tool and symptom. For quick analysis, prototyping and one‑offs, it’s unrivaled. For mission‑critical systems, centralize the data, enforce versioning, and move complex logic into managed apps or scripts where possible. Where spreadsheets remain, apply software engineering practices: documentation, testing, access control and periodic reviews.
For individuals, invest in learning a few high‑leverage skills — advanced formulas, Power Query, and basic automation — and pair that with an insistence on sanity checks. For organizations, accept that excising Excel entirely is unrealistic; instead, design systems so the spreadsheet becomes the last resort, not the primary data store.
If you work with heavy models, consider the hardware and environment that make analysis less painful — a powerful laptop can change the experience. (A reliable MacBook is one practical option for power users who prefer macOS.)
Excel’s longevity is a little ugly and a lot impressive. It survived because it was useful, because it didn’t break people’s work, and because communities formed around it. The better future isn’t an Excel zero‑sum: it’s one where robust platforms and smart spreadsheets coexist, with AI and central data plumbing doing the heavy lifting while humans keep asking the awkward, essential question — does this number actually make sense?