What it means
The technique rests on the idea that financial numbers have relationships that hold in normal conditions. Payroll should move roughly with headcount, and warranty costs should move roughly with units sold, so a number that breaks its relationship deserves an explanation.
Auditors are required to use analytical procedures when planning an audit and again when forming their overall conclusion, and often use them as substantive evidence in between. For internal finance teams the same techniques underpin the monthly review that catches a missing accrual before the accounts go to the board.
Doing them properly means setting the expectation before looking at the recorded number. You also have to set a threshold in advance, both as a dollar amount and a percentage, above which a difference will be investigated rather than explained away.
The quality of the procedure depends entirely on the quality of the expectation. Comparing this year's revenue to last year's is weak evidence; building expected revenue from square footage, occupancy and average price is far stronger, because the model would have to be wrong in several places to mask an error.
The most common weakness is confirmation. When a variance appears, the temptation is to accept the first explanation offered by management, and good practice requires corroborating that explanation against something independent before closing the point.
Scale matters too, because averages hide problems. A group-level comparison can look perfectly reasonable while one division is badly wrong and another is wrong in the opposite direction, so procedures are usually run at the lowest level of detail the data allows, month by month and site by site.
In practice
Real-world examples.
Example
A hotel group's auditor builds expected room revenue from available rooms, occupancy rates and average daily rate, and finds recorded revenue $900,000 below expectation. The gap turns out to be commission wrongly netted off rather than shown as an expense.
Example
A finance manager reviewing monthly accounts notices gross margin has jumped from 38% to 44% with no price change. Investigation reveals that a stock count adjustment was posted to the wrong period.
Example
An auditor compares the ratio of repairs expense to the carrying value of plant across three factories. One site is far out of line, and the review finds $340,000 of capital projects incorrectly expensed rather than added to fixed assets, which the client agrees to correct before the accounts are signed.
Think of it
“Analytical procedures look for things that don't make sense-unusual patterns or relationships.
Formula
Calculation
Variance = Recorded Amount - Expected Amount. Percentage Variance = Variance / Expected Amount x 100. Investigate whenever the variance exceeds the pre-set threshold.
An auditor tests the payroll expense of a call centre business. Human resources records show an average of 120 employees during the year at an average fully loaded cost of $65,000, giving an expectation of 120 x $65,000 = $7,800,000.
The recorded payroll expense is $8,450,000. The variance is $8,450,000 - $7,800,000 = $650,000, which is $650,000 / $7,800,000 x 100 = 8.3% of the expectation. The auditor set a threshold of the lower of 5% or $400,000, so the difference must be investigated.
Follow-up shows $410,000 of one-off redundancy payments and $95,000 of overtime, leaving $145,000 unexplained. That residual is 1.9% of the expectation, inside the threshold, so the auditor documents the explanations and the corroborating payroll reports and moves on.Case study
Seen in the real world.
Bramwell Coldstore is an invented, fictional food storage business used for this illustrative case. Its auditors ran a simple analytical procedure on electricity costs, expecting them to move broadly with cubic metres of refrigerated space and average outside temperature.
The expectation for the year was about $1,240,000, but the ledger showed $1,015,000, a shortfall of $225,000 that no one had questioned because costs coming in under budget rarely attract attention. The audit team pressed the point, since a cost that low was physically implausible for the space being cooled.
The explanation was an unposted accrual: three months of invoices from a new supplier had been sitting in a shared mailbox. The illustrative moral is that analytical procedures work in both directions, and a favourable variance can be just as informative as an unfavourable one.
Watch out
Common mistakes.
- Forming the expectation after seeing the recorded figure, which almost guarantees the expectation quietly bends to fit the number.
- Using only prior year comparisons, which simply carries forward last year's errors as this year's benchmark.
- Accepting management's first explanation for a variance without corroborating it against independent evidence.
Questions
People also ask.
Are analytical procedures enough on their own?
For low risk areas they can provide the main evidence, but material and high risk balances normally need detailed testing as well.
What makes an expectation reliable?
Independence from the accounting records, so operational data such as headcount, units shipped or square footage tends to be stronger than ledger-based comparisons.
Can non-auditors use these techniques?
Absolutely, and month-end review by a finance team is exactly the same discipline applied before the numbers are published.
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