Excel mistakes cost millions of dollars
- Some people fix them as a job
- Bespoke software simply isn't an option for some of the African clients.
"As a result spreadsheets almost become the default – especially within governments."
"In the end, the problem isn't spreadsheets, but people."
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Excel is a disconnected sandbox and that works
My best guess is Excel’s biggest weakness—that it’s disconnected from live data, and that every file is named
monthly_results_final_v2_FINAL.xlsx—is actually its moat. What makes Excel (and Google Sheets) unique from BI is that it’s not just a tool for working with data; it is the data. You can create in it; you can update it without being afraid that you might break something else; you can share it, all in a single file. You can save it, and know, with total confidence, that when you open it tomorrow, next week, or next year, it’ll be the same as it was when you last left it. It’s not a tool for exploring and presenting data—which is what BI is for—but a sharable, self-contained sandbox for writing down numbers and adding them up. That makes replacing Excel a catch-22: If you build a tool that solves its biggest problems—being disconnected and static—you’re suddenly building a BI tool and not Excel.
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Is Excel immortal?
Especially driven by Sales & Finance because of sales forecasts for Wall Street:
Live, mysteriously-changing data is bad. Collaboration is bad. Restrictions on how to manipulate data are bad. Any sort of abstraction that forces sales leaders to work through some drag-and-drop visualization builder that muddies how, exactly, the fields for “deal amount,” “opportunity ARR,” and “win-probability-adjusted revenue forecast” are summed up is bad. Excel—orphaned from all other realities, saved to desktop, and barbarically updated via emails and saved as…—is good.
Excel 2027:
All together, none of this would feel that different than Excel does today. You download an application. Double click on a CSV, and Excel 2075 opens it up. You can manipulate everything directly in a spreadsheet. You can add more CSVs, by typing them in, or by dropping them in your workspace. Join them together; play with them with R; make some charts. Save the whole thing, and email it, as one file. If the data gets too big, or the computation gets too complex, push the file to the cloud, and use the desktop app to do your work on some giant computer in AWS. Let the app be smart about what to run locally, and what to run remotely.
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