A spreadsheet contains many amounts beginning with the digit one. That can be ordinary in some datasets. Benford’s law describes a leading-digit distribution in which smaller first significant digits occur more often than larger ones.
Pain and Ralchenko’s research paper on Benford’s law gives the formula and discusses applicability limits. Under that distribution, the first significant digit is one about 30.1% of the time. It is not a universal requirement for every list of numbers.
Ask how the numbers were produced
Imagine a fictional catalogue in which every product costs between 200 and 299 units. Every price begins with two because the catalogue was defined that way. A comparison with Benford frequencies would reveal the selection rule, not establish dishonesty.
Assigned identifiers are another reason to stop before testing. A sequence of membership numbers describes an administrative naming system, not necessarily a naturally varying quantity. Examine the field definition, range, filters, and repeated fixed amounts before deciding that the comparison is meaningful.
A published Kent audit report illustrates the cautious interpretation: unusual digit combinations can reflect error, potential irregularity, or normal constraints such as expense caps. The report describes follow-up testing rather than treating a digit flag as a verdict.
For your own analysis note, separate the observation from the explanation: “Digit frequency differs from the reference pattern; dataset suitability and transactions need review.” Preserve the data-selection steps so another reviewer can reproduce the result.
A statistical flag is a question generator. It cannot identify who acted improperly or why. Before making a public accusation, establish the underlying facts through appropriate investigation, not a colourful chart of first digits.