The 7 Deadly Sins of Excel

I've been in finance for over 20 years. I spent over half of that time in leadership and executive positions, building comp systems, forecasting models, and board-level reports.

I've also inherited broken spreadsheets from analysts who thought they were advanced. And I've watched models collapse under their own complexity — some of them even my own.

Here's what I've learned: The difference between a spreadsheet that gets you promoted and one that gets you fired isn't how fancy your formulas are. It's whether someone else can trust it when you're not in the room.

These are the seven deadly sins of Excel. Mistakes that have cost companies billions and analysts their jobs. I've committed most of them myself. You probably have too.

Sin #1: Hard-Coding

The Disaster

Fannie Mae, 2003. An accountant typed a single number directly into a formula. Just one number.

Result: $1.1 billion accounting error. The CEO resigned. Massive restatement.

The Sin

Hard-coding is when you type a constant directly into a formula instead of referencing a cell.

For example:

• ❌ =A1 * 1.2
• ✅ =A1 * VAT_Rate

The first formula works fine — until the VAT rate changes from 20% to 22%. Now you need to find every instance of 1.2 in your workbook. If you use Find & Replace, you'll accidentally change your currency conversion rate or miss a formula buried in a hidden sheet.

Someone will notice. Usually in a board meeting.

The Fix

Every constant needs to live on an Assumptions tab. If a number changes in the real world, it should have one home in your model where it can be easily referenced and updated.

Sin #2: Lazy or Sloppy Formula Application

The Disaster

JP Morgan, 2012. The "London Whale" trade.

A Value-at-Risk model had copy-paste errors. Some cells were divided by SUM instead of AVERAGE. The risk was grossly understated.

Result: $6 billion loss.

The Sin

Legacy Excel trained us to write a formula once and drag it down. Here's what actually happens:

1. You drag the formula down 1,000 rows
2. Excel copies it 1,000 times
3. Each cell has its own independent formula
4. Somewhere around row 347, you accidentally click and overwrite one
5. Your model is now broken, and you'll never find it

The Fix

Build your models so these mistakes aren't possible.

Dynamic arrays are one option: Write the formula once, let it spill. One formula, impossible to overwrite. You'll know immediately if something breaks because it will error.

Data tables are another option: They're structured and break visibly when something's wrong (though not always as visibly as you'd like).

The point isn't which tool you use. The point is: if your model depends on thousands of identical formulas staying identical, you've already lost.

This is about file hygiene. File cleanliness. Organization. In my Excel 4 Academy, I teach a structured approach to building tabs and files. It's all about setting up your work so common, dangerous mistakes get mitigated before they can happen.

Structure your work so a single mistake can't silently corrupt everything.

Sin #3: Mixing Inputs and Calculations

The Disaster

This one happens every day in corporate America.

I once inherited a revenue model with assumptions scattered across six tabs. Calculations were mixed with inputs. No clear flow.

I asked the analyst: "What's the annual growth rate we're assuming?"

The response: "Hold on, let me find that."

Red flag. If you can't answer that question in three seconds, your model is not trustworthy.

The Sin

Blue cells, black cells, formulas, and hard-coded numbers all on the same sheet. This isn't a model. This is a puzzle.

The Fix

Here's the thing: every company I've worked at did this differently. Some used color coding. Some used separate tabs. Some used named ranges.

It doesn't matter which system you use. What matters is that you have a system.

Assumptions need a home. Inputs need a home. Your calculation engine needs to be separate from your presentation layer.

When I open your model, I should be able to:

1. Start at the output
2. See what it's telling me
3. Trace back through the assumptions without getting lost in the machinery

Consistency is more important than the specific method. Pick a structure. Stick to it. Make sure anyone who inherits your work can figure it out in five minutes.

Sin #4: Hiding Instead of Deleting

The Disaster

Westpac, 2005. They sent a spreadsheet to analysts and "hid" sensitive profit data by making the font white.

White text on a white background. Invisible, right?

Wrong.

An analyst hit Ctrl+A. The white text turned blue. The sensitive data was exposed.

Result: Trading halt. Share price drop. Regulatory investigation.

More Disasters

Everybody's got a story like this:

• I once received an RFP package from a late bidder with hidden columns containing full competitive bid details from other vendors. They had no idea it was in there.
• I received an Excel test from a candidate with hidden tabs of real company financial information they'd copied and forgotten to delete.

People reuse files. They think they've cleaned them. They haven't.

The Sin

Hiding is not the same as deleting. White font, hidden rows, hidden columns — the data is still there. Anyone with basic Excel knowledge can find it.

The Fix

If the audience shouldn't see it, delete it before you send the file.

Before sending anything externally:

1. Review → Inspect Document
2. Unhide everything yourself
3. Delete what doesn't belong
4. Don't assume you got it all — go back and check again

Sin #5: The Dunning-Kruger Tax

The Sin

This one's about overestimating your own competence.

When I say Dunning-Kruger, most people think I'm just talking about Excel skills. But it's not just about Excel. It's about misunderstanding your role in the organization. You think you're doing a good thing when you're really creating a bad situation.

The Research

• 90% of Excel users rate themselves as "advanced"
• 90% of spreadsheets contain material errors

Funny how that works.

Knowing how to nest 10 IF statements doesn't make you advanced. It makes you dangerous.

Here's what I learned the hard way: I once created a sophisticated model using the latest functions (LET, LAMBDA, etc.) that nobody else knew how to use. It had to be fully rebuilt for the end users to sustain it.

I caused more harm than good.

Being advanced isn't about knowing the newest functions. It's about building something your team can actually use.

The Organizational Behavior Angle

I love LET and LAMBDA. They're powerful. But if nobody else on your team knows them, you're creating technical debt and becoming a bottleneck.

You have to meet people where they are. If you want to enact change, do it tactfully. Train the team first. Don't just run away with the ball.

That's the punchline: It's either you think you know more than you do about Excel, or you think you know more than you do about organizational behavior. You're overestimating your competence in one of those two areas.

And both are dangerous.

The Fix

• Build models your successor can understand
• Use the simplest tool that solves the problem
• If you want to level up the team on modern Excel, do it as a deliberate upskilling effort — not a surprise buried in production code

Sin #6: Manual Data Cleaning

The Sin

This one's slow. It's the 2 hours every month you spend copying, pasting, trimming, and deduping data manually.

Here's the thing: Every single time you do this manually, you introduce errors.

• Trailing spaces
• Missed duplicates
• Wrong date formats

Every manual step opens up more opportunity for mistakes. You're amplifying the potential for error with every single repetition.

Your CFO asks: "Can we automate this?"

You say: "Not really, it's complicated."

You just lost credibility. Because you answered too quickly. Because you made assumptions.

The Fix

Manual data cleaning in 2026 is inexcusable. Power Query exists. It's built into Excel. It's free.

Learn Power Query. Learn to use tools that minimize or fully mitigate manual data cleaning.

The workflow:

1. Connect to your data source once
2. Build your transformation steps once
3. Click refresh forever

The analyst who manually cleans data every month? That's the analyst who doesn't get promoted.

Sin #7: Using Excel for Everything (Or Not Enough)

The Disaster

UK Public Health England, 2020.

They used Excel to aggregate COVID test results. The file hit the Excel row limit. The data silently truncated.

Result: 16,000+ test records dropped. Contact tracing failed.

The Sin

When you have a hammer, everything looks like a nail. And if you're good at wielding that hammer, you see nails everywhere — even places they shouldn't be.

I've seen:

• Commission tracking in Excel for 200-person sales teams
• Inventory management for 50,000 SKUs
• Project timelines with manual Gantt chart updates

I built some of these things. I should have known better. I learned better over time.

Every one of those should have been in a database or purpose-built software.

But here's the flip side: There's another group of people who underestimate how powerful Excel actually is. They dismiss it entirely. And that's just as dangerous.

You've got these two sides of the coin. Everybody's operating somewhere in between. And knowing when and where to draw the line? It's never a hard-and-fast rule. It depends on each and every situation.

The Fix

Before building in Excel, ask three questions:

1. Volume: Am I dealing with more than 100,000 rows or complex formulas? (Power Query can process it, but that doesn't mean it should land in a spreadsheet)
2. Concurrency: Do multiple people need to edit simultaneously?
3. Audit trail: Do you need to track who changed what, when, where, and how? (Critical for commissions, payroll, or anything compliance-related)

If yes to any of those: Excel is probably the wrong tool.

Part of mastery is knowing when to say when.

The Bottom Line

These are the seven deadly sins of Excel:

1. Hard-coding — constants buried in formulas
2. Lazy or sloppy formula application — not taking advantage of ways to mitigate common mistakes
3. Mixing inputs and calculations — models that are puzzles instead of tools
4. Hiding instead of deleting — sensitive data still in the file
5. Overestimating your competence — in Excel or organizational behavior
6. Manual data cleaning — amplifying errors with every repetition
7. Using Excel for everything (or not enough) — not knowing where to draw the line

Each one has cost real companies real money. Each one has cost real analysts their credibility.

The good news: every single one is fixable.

I violated every one of these at some point in my career. Part of mastery is admitting to your past sins — that's the only way you'll ever be free of them.

Want to learn modern Excel skills that actually matter to your career? Check out Excel 4 Academy.