Finance track

Finance · Phase 33

Excel for Consultants

Keyboard-first modelling, lookups, sensitivity tables and audit-proof formatting.

In plain English

Excel is still where consulting work is delivered. Speed comes from never touching the mouse, and credibility comes from a model someone else can follow without asking you what a cell means.

The advanced view

Treat a workbook as software: separate inputs, calculations and outputs; keep one formula per row consistent across all columns; avoid hard-coded constants inside formulas; and make every assumption traceable to a single cell. A model that cannot be audited will not be trusted, however correct it is.

Layout first. Three zones: inputs (blue font, one cell per assumption, units labelled), calculations (black, left to right in time), outputs (the two or three numbers the client actually reads). Never repeat an input in two places. Never mix a constant into a formula — 'Revenue × 1.03' hides a growth assumption nobody can find. One formula, copied cleanly across the row, is both faster to build and far easier to check.

Keyboard navigation that saves hours

Ctrl + arrows / Ctrl+Shift+arrows

Jump to the edge of a data block, or select to it. The core movement of fast modelling.

F2, F4, F9

Edit in place; cycle absolute/relative references; evaluate the selected part of a formula.

Ctrl + [ and Ctrl + ]

Trace precedents and dependents to find where a number comes from.

Alt + = , Alt + ;

AutoSum, and select visible cells only when rows are filtered or grouped.

Ctrl+Shift+{ and F5 → Special

Select all precedents, or jump to constants, formulas and blanks to audit a sheet.

Alt + N + V / Alt + H + 0

Ribbon key sequences: build a pivot, insert a row. Learn the four you use daily.

The functions that matter

INDEX(range, MATCH(key, keys, 0))            — robust two-way lookup
XLOOKUP(key, keys, values, "n/a")            — modern replacement, exact-match by default
VLOOKUP breaks when columns move; INDEX/MATCH and XLOOKUP do not
SUMIFS / COUNTIFS / AVERAGEIFS               — aggregate by criteria instead of nested IFs
IFERROR(value, "check")                      — trap errors without hiding them
OFFSET / INDIRECT                            — powerful, volatile, and unauditable: avoid
Data → What-If → Data Table                  — one- and two-way sensitivity on any output
Named ranges: WACC, TaxRate, ExitMultiple     — formulas read like the model, not like coordinates

Worked example: a two-way sensitivity table

Step 1 of 10

  1. 1Model output: equity value per share in cell B40 =

Circular references are the classic modelling trap: interest depends on average debt, debt depends on cash flow, cash flow depends on interest. Three ways out. Use opening-balance interest, which is simple, defensible and almost always accurate enough. Or enable iterative calculation, which resolves it but makes the model fragile and hard to audit. Or break the loop with a small manual convergence — a copy-paste of the interest figure. Say which one you chose and why; interviewers ask.

Must know cold

  • Inputs blue, formulas black, links to other sheets green — the standard colour convention.
  • One formula per row, consistent across every column. Inconsistency is the top source of model error.
  • No hard-coded numbers inside formulas; every assumption is its own labelled cell.
  • F9 on a selected fragment evaluates just that fragment — the fastest debugging tool in Excel.
  • Label units everywhere: SEKm, %, x, days. Unit confusion causes more errors than bad maths.
  • Build a check row: assets − liabilities − equity = 0, and cash flow ties to the balance-sheet cash movement.

Common pitfalls

  • ×VLOOKUP with an approximate match left on by default, returning silently wrong values.
  • ×Wrapping everything in IFERROR so genuine broken links look fine.
  • ×Merged cells, which break sorting, selection and every keyboard shortcut.
  • ×Hard-coding a plug to make the balance sheet balance instead of finding the error.
  • ×Sending a workbook with iterative calculation on and no note explaining the circularity.

Essential vocabulary

Named range
A label assigned to a cell or range so formulas read =EBITDA*ExitMultiple.
Data table
Built-in one- or two-way sensitivity analysis that re-runs the model per cell.
Volatile function
A function like OFFSET or INDIRECT that recalculates constantly and defeats dependency tracing.
Check row
A formula that must equal zero; the model's own unit test.
Plug
A hard-coded number inserted to force a balance. Always a bug, never a solution.

Strategy connection

The model is the argument. A clean workbook with named assumptions lets a client challenge one number and see the consequence immediately, which turns a debate about your conclusion into a debate about their assumptions — the position you want to be in.

Exercises

Try each one on paper before revealing the worked solution.

Exercise 1

You inherit a workbook where the balance sheet is out by 14 in year 3 only. Give the diagnostic sequence.

Exercise 2

Rewrite VLOOKUP(A2, Data!A:F, 5, TRUE) safely, and say what it was doing wrong.

Exercise 3

Structuring exercise: you have four hours to build a model that answers whether a client should close one of three plants. What do you build?

References

  • Rosenbaum, J. and Pearl, J. (2020). Investment Banking: Valuation, LBOs, M&A, and IPOs. 3rd Edition, Wiley, Hoboken.
  • Handley, B. (2003). Speed Mathematics: Secret Skills for Quick Calculation. Wiley, Hoboken.

Statistics glossary for this phase

The terms an interviewer expects you to use precisely — with the pitfall attached to each.

Mean (average)

Sum of the values divided by how many there are.

In finance

The base case in any sizing or margin estimate: revenue per customer, ticket size, cost per unit.

Pitfall

×Averaging averages. Average margin across segments is only valid when weighted by revenue.

Median

The middle value once the data is sorted.

In finance

Use it for skewed data such as deal sizes, household income or customer spend.

Pitfall

×Quoting a mean where a few whales dominate makes the typical customer look far richer than they are.

Order of magnitude

The nearest power of ten of a quantity.

In finance

In market sizing, being right to a factor of two beats being precise and wrong.

Pitfall

×Losing a factor of 1,000 between thousands, millions and billions late in the arithmetic.

Weighted average

Average where each value counts in proportion to its size.

In finance

Blended margin, blended price, WACC — all weighted averages.

Pitfall

×Using unweighted averages across segments of very different size.

Practise this

The drills and cases where this phase turns into arithmetic you do out loud.