What it means
The Gini Index comes from the Lorenz curve, a graph that plots the cumulative share of a population against the cumulative share of whatever is being measured. If income were spread perfectly evenly, that curve would be a straight diagonal line, and the Gini Index measures how far the real curve sags below the diagonal.
The bigger the sag, the higher the score. For a business, the appeal is that it compresses an entire distribution into one comparable figure.
You can track it month by month, compare it across regions, or set it as a target without staring at a full table of deciles every time someone asks whether things are getting more lopsided. Outside economics, the most common commercial use is revenue concentration.
A software company that earns most of its revenue from three accounts has a high Gini Index on its customer base, which is a plain warning about how fragile next year's numbers are. Lenders use the same statistic to judge how well a credit scorecard separates borrowers who repay from those who default.
The main nuance is that the index describes the shape of a distribution, not its size. Two markets can share an identical score while one is uniformly wealthy and the other is uniformly poor, so it should always be read alongside an absolute figure such as median income or average revenue per account.
It is also fairly insensitive to what happens right at the top and bottom tails. If a handful of extreme values genuinely drives your decision, pair the index with a simpler measure such as the share of revenue held by your largest 10% of customers.
In practice
Real-world examples.
Example
A regional bank calculates a Gini Index of 0.31 on household income across its lending footprint and 0.47 across a neighbouring state. It uses the gap to justify a different product mix in each area, pushing entry-level accounts where the distribution is wider.
Example
A logistics firm ranks its 900 shipper accounts by freight spend and computes a Gini Index of 0.72. The finance director flags this to the board as the reason a single contract loss could wipe out a quarter of gross profit, and the sales team is set a target of pulling the score below 0.60 within two years.
Example
A consumer lender tests a new credit scorecard and finds its Gini Index for separating defaulters from non-defaulters has risen from 0.42 to 0.51. The risk committee approves the new model because a higher score here means sharper discrimination between good and bad applicants.
Formula
Calculation
Gini Index = 1 - sum across every population slice of (width of the slice x sum of the cumulative shares at its two ends).
Take a subscription business that ranks its customers by annual spend and splits them into five equal groups of 20% each. Those groups contribute 5%, 10%, 15%, 25% and 45% of revenue.
Cumulative revenue share at the end of each group: 0.05, 0.15, 0.30, 0.55, 1.00. Each slice is 0.20 of the customer base wide.
Sum of the paired cumulative shares: (0.00 + 0.05) + (0.05 + 0.15) + (0.15 + 0.30) + (0.30 + 0.55) + (0.55 + 1.00) = 0.05 + 0.20 + 0.45 + 0.85 + 1.55 = 3.10.
Gini Index = 1 - (0.20 x 3.10) = 1 - 0.62 = 0.38.
A score of 0.38 says revenue is meaningfully skewed towards the top group but is not dangerously concentrated in a single account.Case study
Seen in the real world.
Northvale Instruments is an illustrative, entirely fictional maker of laboratory equipment with $62 million of annual revenue. For years its leadership described the customer base as healthy simply because the total kept rising, and nobody looked at how that total was distributed.
A new commercial director ran the numbers and found a Gini Index of 0.68 across roughly 400 accounts, with the top fifth of customers producing well over half of all sales. That single figure changed the conversation in the boardroom faster than any spreadsheet had: it turned a vague sense of dependence into something that could be tracked and targeted.
Over the following eighteen months the fictional company deliberately grew its mid-sized accounts, added a lower-priced instrument aimed at smaller labs, and declined one large tender that would have made the skew worse. Revenue rose only modestly, but the Gini Index fell to 0.57, and the illustrative business found it noticeably easier to negotiate with its biggest customers once none of them could threaten the whole year.
Watch out
Common mistakes.
- Treating a higher Gini Index as automatically bad. In credit scoring a higher score means the model separates good and bad borrowers more sharply, which is exactly what you want.
- Comparing scores calculated on different numbers of groups. A Gini Index built from five quintiles is not directly comparable to one built from a hundred percentiles, so keep the method consistent before drawing conclusions.
- Reading the index as a measure of wealth or size. It describes only the shape of a distribution, so a poor region and a rich region can produce the same number.
Questions
People also ask.
What is a normal Gini Index for income?
National income inequality scores commonly sit somewhere between roughly 0.25 and 0.60, with lower figures in countries that redistribute heavily through tax and benefits.
Can I calculate it in a spreadsheet?
Yes, sort your accounts from smallest to largest, build cumulative population and value shares, then apply the slice formula in a single column of arithmetic.
Is the Gini Index the same as the Gini coefficient?
They are the same statistic, and the only difference is presentation, since the coefficient is usually quoted as a decimal such as 0.38 while the index is sometimes shown as 38.
From the founder's library
Take it further with the book.
Build your financial confidence beyond this definition. Shihan's full-length guide, Accounting Fundamentals, takes the same plain-English approach and turns it into a complete, practical playbook for non-finance managers, business owners and students - with chapter-end quiz answers and presentation slides included.
25% off with code MMHQ25, applied at checkout. Priced in USD - checkout may show the equivalent in your local currency.
View the book and save 25%