If It Skips Excel, Think Twice

A Provocative but Useful Test

A slightly provocative test for whether an engagement counts as genuine analytical consulting is simple: does it require meaningful spreadsheet work to categorize, count, calculate or correlate real data?1 Work that skips this entirely tends to resemble coaching, staffing support or project management more than data-driven consulting, valuable disciplines in their own right, but a genuinely different kind of work.

Without Data, Conclusions Become Impressions

Without structured quantitative analysis, conclusions end up resting more on interviews, observations and general impressions than on verifiable data. That kind of qualitative input has real value, but it is a fundamentally different foundation for a recommendation than one built on actual numbers, patterns and statistically meaningful sample sizes.

Small Sample Sizes Hide in Plain Sight

Skipping spreadsheet analysis often signals, whether consciously or not, that the underlying sample size is genuinely small. Real analytical engagements frequently involve tens of thousands of records: a robust logistics spend analysis might cover a hundred thousand individual deliveries, a hospital bed utilization study might draw on tens of thousands of patient records, and a promotional analysis might span thousands of distinct product types. Managing that volume of information reliably in one's head, or on paper, simply is not realistic.

Spreadsheets Are Where Consulting Skill Actually Builds

Spreadsheet proficiency functions as a foundational skill most consulting analysts build early and continue refining throughout an entire career, requiring the kind of extended, deliberate practice that any genuine expertise demands.2 Becoming genuinely fast at grouping, organizing and slicing large datasets is less about any single clever technique and more about accumulated repetition over hundreds of real engagements.

The Hidden Ratio Behind Every Slide

Behind nearly every polished, well-worded presentation sits several messy, complicated spreadsheet files where the real underlying analysis actually happened. A rough but genuinely useful rule of thumb holds that roughly ten hours of spreadsheet work supports every single hour spent building the corresponding presentation, a ratio that surprises people outside the field who assume the visible slide deck represents most of the actual effort involved.

A Trait Common Among Strong Analysts

Consultants with strong quantitative training, often from engineering or similarly rigorous backgrounds, tend to grasp spreadsheet discipline naturally, organizing information methodically and appreciating its importance instinctively. That trait, sometimes paired with a genuinely detail-oriented personality, correlates strongly with strong analytical output across a consulting career.

Manufacturing Data Where None Exists

Even on an engagement that initially seems to lack obvious quantitative data, it is usually worth pushing to find or create genuinely measurable inputs, structured survey responses, coded interview themes, or formal evaluation scores that can be organized into rows and columns. Doing so surfaces trends and patterns invisible to purely narrative analysis and builds considerably more credibility with a client than impressions alone ever could.

Where Real Insight Actually Happens

Presentation software excels at communicating a conclusion clearly and persuasively once it exists, but the genuine analytical breakthroughs, the moments where an underlying pattern in the data suddenly becomes visible, tend to happen while directly manipulating raw numbers rather than while designing slides. Presentation software tells the story; spreadsheet analysis is where the real story gets discovered in the first place.

Building the Habit Early Pays Off for Years

Junior analysts who invest real effort mastering spreadsheet fundamentals early in their careers, pivot tables, lookup functions, conditional formatting, formula auditing, tend to move noticeably faster than peers relying only on basic formulas years into their careers. That early investment compounds steadily, since the analytical speed it produces frees up more time for the genuinely valuable work of interpreting results and building a persuasive narrative around them.3

Modern Visualization Tools Extend the Same Discipline

More recent data visualization platforms have made discovering patterns considerably less laborious than traditional spreadsheet work alone, and plenty of experienced analysts today strongly prefer these newer tools for genuine data discovery. The underlying discipline remains essentially identical regardless of which specific tool actually gets used: find or create real quantitative data, then let disciplined, patient analysis reveal what a conclusion should actually be.

• 1Microsoft Excel
• 2Deliberate practice
• 3Spreadsheet