You do not need to be an Excel expert on day one of an MBA. But the first term moves quickly, and students who are already comfortable with a spreadsheet spend their time on the business problem rather than on the tool. Here is what is worth practising, in roughly the order it pays off.

1. Move around without the mouse

A handful of shortcuts saves hours over a term:

  • Ctrl + arrow keys jump to the edge of a block of data; add Shift to select it.
  • F2 edits the active cell; F4 toggles between relative and absolute references while editing a formula.
  • Alt + = inserts a SUM for the cells above or to the left.
  • Ctrl + T turns a range into a table, which keeps formulas and formatting consistent as data grows.

On a Mac, Ctrl is usually Cmd, and some function-key shortcuts need the Fn key.

2. Understand references properly

Most broken spreadsheets come from references that move when they should not. Practise until these are automatic:

  • A1 — relative: changes as you copy the formula.
  • $A$1 — absolute: always points to the same cell (use it for assumptions such as a tax rate).
  • $A1 / A$1 — mixed: one part fixed, one part moves. Useful for tables that combine a row input and a column input.

3. Look things up

XLOOKUP finds a value in one column and returns the matching value from another. It is available in Microsoft 365, Excel 2021 and later, and Excel for the web. If you are on an older version, learn INDEX with MATCH, which does the same job and works everywhere.

=XLOOKUP(G2, Products[SKU], Products[Price], "Not found")
=INDEX(Products[Price], MATCH(G2, Products[SKU], 0))

4. Summarise with conditions

SUMIFS, COUNTIFS and AVERAGEIFS answer most "how much, by what" questions without a pivot table:

=SUMIFS(Sales[Revenue], Sales[City], "Pune", Sales[Channel], "Online")

Learn the argument order — the range you are adding up always comes first in SUMIFS.

5. Use logic carefully

IF and IFS handle decisions; IFERROR hides errors. Use IFERROR sparingly: an error is often telling you something real, and hiding it can make a broken model look fine.

6. Clean text and dates

Real data is messy. TRIM removes stray spaces, TEXT controls how numbers and dates display, and EOMONTH and EDATE handle month-end and month-shift logic that comes up constantly in finance.

7. Pivot tables and charts

Pivot tables are the fastest way to explore a dataset: drag a field to rows, a measure to values, and you have a summary in seconds. Pair them with simple charts — a bar chart for comparing categories, a line chart for change over time. Avoid 3D effects and pie charts with many slices.

8. Model like someone else will read it

The habits that make a model trustworthy matter as much as the formulas:

  • Keep inputs, calculations and outputs in separate, clearly labelled areas.
  • Colour inputs in blue and formulas in black — a widely used convention that tells readers what they can change.
  • Never type a number inside a formula. =B5*1.18 hides an assumption; put 18% in its own labelled cell and reference it.
  • Keep one consistent formula across a row, so the model can be checked by looking at the first cell.

Open our projection starter model to see these conventions in a small, working example.

A two-week practice plan

Download the free practice sales dataset — a synthetic year of orders for a fictional brand — and work through it:

  1. Days 1–2: Format it as a table. Add a Month column from the order date.
  2. Days 3–4: Use SUMIFS to build revenue by city and by channel.
  3. Days 5–6: Build the same summaries with a pivot table and compare.
  4. Days 7–8: Add a gross margin column and find the least profitable category.
  5. Days 9–10: Chart monthly revenue and describe the trend in two sentences.
  6. Days 11–14: Build a one-page summary a manager could read in a minute.

When you need to express growth between two numbers, the CAGR calculator shows the formula and the year-by-year path.

Written by Akash Gautam (LinkedIn profile, opens in a new tab). Spotted an error? Tell us.