Skip to main content

ATO benchmark comparison

+----------------------------------------------------------------------+
|                       ATO benchmark comparison                       |
+----------------------------------------------------------------------+
|           Offline variance analysis against ATO benchmarks           |
+----------------------------------+-----------------------------------+
| DR  what it gives you            | CR  what it needs                 |
+----------------------------------+-----------------------------------+
| ATO benchmark ratio compare      | P and L figures per account       |
| accurate turnover definition     | account to label mapping          |
| shows the working per account    | -                                 |
+----------------------------------+-----------------------------------+

ato-benchmark-compare

tests PyPI License: MIT python

Distribution ato-benchmark-compare, import package atobenchmark, command ato-benchmark-compare.

Compare a set of profit and loss figures against the ATO small business benchmarks, on your own machine, with the working shown.

The ATO publishes benchmark ranges for 100 industries and uses them to pick which small businesses to look at more closely. Checking a client against them is a sensible thing to do before lodgment, and it is usually done by hand: find the industry page, work out which turnover range applies, add up the right accounts, and divide. This does that, and it records which accounts went into which figure so the answer can be checked by someone else later.

Australian tax rules only. Every figure comes from the ATO's own published dataset, and the comparison is a comparison, not advice.

The published Python distribution and command remain ato-benchmark-compare, and the import package remains atobenchmark.

What it gets right

The arithmetic is not "expenses over income". The ATO defines these ratios narrowly, and the differences change the answer:

  • Turnover is the sales of goods and services label, not total income. It falls back to total business income only when sales are blank, zero, or less than 50% of total business income.
  • Total expenses for the ratio is total expenses less payments to associated persons. Wages to a spouse or an associated entity come out before the division.
  • Cost of sales for the ratio excludes salary and wages, so the wages sitting in a bakery's cost of sales are moved out of the numerator and stay in total expenses.
  • The key range is cost of sales to turnover where the ATO publishes one for that industry, otherwise total expenses to turnover.
  • Turnover bands are treated as adjoining. The ATO prints $65,000 - $400,000 then $400,001 - $750,000, which read literally leaves $400,000.50 in no band at all.

Source: Australian Taxation Office, How we calculate benchmark ratios (QC 37143).

Excel workbook

No Python? workbooks/ato-benchmark-compare.xlsx is the same comparison in ordinary worksheet formulas: paste the profit and loss, review the mapping, pick the industry and read the result. It is macro-free, needs desktop Excel for Microsoft 365 or Excel 2024, and is held to this engine's answer by tests/test_workbook.py. See workbooks/README.md.

Install

git clone https://github.com/ryanduguid/australian-accounting.git
cd australian-accounting/packages/ato-benchmark-compare
pip install .

Python 3.10 or later. The runtime has no dependencies at all: the benchmark data ships inside the package and nothing is fetched at run time.

pip install ato-benchmark-compare installs the same package from PyPI; clone the repository when you want the example files used below.

Use it

The flow is two commands, because the middle step is a person reading the ledger.

1. Draft a mapping from the profit and loss.

ato-benchmark-compare map --profit-and-loss examples/bakery-pnl.csv --out mapping.csv

That writes one row per account with a suggested bucket, the reason it was suggested, and the amount it read. Suggestions come from account names alone.

2. Review it. Open mapping.csv, fix the buckets, and change the source column to reviewed. ato-benchmark-compare buckets explains each bucket. This is the step that decides whether the answer is worth anything: no account name tells you whether wages went to an associate.

The generated mapping includes an account_key immediately after account. It is a SHA-256 digest of the tool's existing case-and-whitespace-insensitive account identity. Leave both columns unchanged while reviewing bucket, source and note; amount is shown for context and is not bound by the key. On the next run, the key lets the tool recover a formula-guarded logical account without confusing =cmd|calc with the genuine account '=cmd|calc when both look the same in a spreadsheet.

account_key is an identity integrity check, not authentication or tamper resistance. Anyone who can edit the file can recompute it, and case- or whitespace-only account edits remain valid by design. Older mappings without the column remain readable for ordinary, unambiguous account names. A legacy formula-like name or one that could already contain a spreadsheet guard must be regenerated; reapply the reviewed bucket, source and note values to the new mapping. Profit and loss input parsing strips and normalises leading whitespace, so leading tab, carriage-return and newline prefixes are not distinct raw-ledger identities.

3. Compare.

ato-benchmark-compare compare \
  --profit-and-loss examples/bakery-pnl.csv \
  --mapping examples/bakery-mapping.csv \
  --industry "Bakeries and hot bread shops"
ATO small business benchmark comparison
=======================================
Business type:  Bakeries and hot bread shops
Benchmark year: 2023-24
Turnover:       $850,000.00 (sales of goods and services)
Turnover band:  More than $750,000

Ratio                                   This business  ATO range         Result
---------------------------------------------------------------------------------
Cost of sales to turnover (key)         31.76%         29% to 36%        within
Total expenses to turnover              83.17%         82% to 90%        within
Labour to turnover                      32.68%         -                 no benchmark in this dataset
Rent to turnover                        7.29%          -                 no benchmark in this dataset
Motor vehicle expenses to turnover      1.12%          -                 no benchmark in this dataset

Figures used
  Sales of goods and services   $850,000.00
  Other business income         $1,200.00
  Total business income         $851,200.00
  Total expenses                $751,950.00
  Less payments to associates   $45,000.00
  Total expenses for the ratio  $706,950.00
  Cost of sales excluding wages $270,000.00
  Labour                        $277,800.00

Add --json result.json for the same result as structured data, including every bucket total and the source metadata.

Library callers that distinguish an omitted figure from an evidenced zero can use atobenchmark.to_evidenced_dict(comparison, supplied_fields); include w1 in that collection when it was supplied. The serializer masks ratios and prose whose required inputs were not supplied and returns supplied_buckets, omitted_buckets, and complete_buckets alongside the ordinary comparison payload.

Other commands:

ato-benchmark-compare industries --search cleaning   # find the ATO business type
ato-benchmark-compare show "Bakeries and hot bread shops"
ato-benchmark-compare buckets

Input formats

The format this tool guarantees is two columns, with an optional section column of income, cost_of_sales or expense:

account,amount
Sales,850000
Purchases,290000

A report style export, with a title block, section headings and subtotal rows, is also read. Subtotal rows are detected and written into the mapping marked excluded rather than dropped, so a total can never be quietly added to the figures it totals, and nothing vanishes without appearing in a file you can read. Amounts are taken from the first column that parses as amounts; --amount-column takes a column number or a column heading when a comparative export has more than one.

The report style layout is inferred. It was written against the shape these exports normally take, not verified against a real export from any particular accounting package. Check the mapping file against your own export the first time, and use --amount-column if it picked the wrong period.

Buckets

Bucket What the ATO does with it
turnover Sales of goods and services. The turnover denominator.
other_income Business income that is not sales. Only reaches turnover through the fallback rule.
cost_of_sales Cost of sales, excluding wages inside it.
cost_of_sales_labour Wages inside cost of sales. Kept out of the cost of sales ratio, kept in total expenses and labour.
salary_wages Salary and wages outside cost of sales.
contractor_commission Contractor, subcontractor and commission expenses.
associated_persons Payments to associated persons. Deducted from total expenses. The wage buckets already exclude these, so labour deducts nothing further.
rent Rent expenses.
motor_vehicle Motor vehicle expenses.
other_expense Every other expense, including superannuation and depreciation.
excluded Outside the ATO calculation: income tax expense, subtotal rows.

Exit codes

Code Meaning
0 Comparison produced, nothing to flag: key ratio inside the ATO range, or no published range applies to this turnover
1 Could not produce a comparison, for example an account with no mapping entry
2 Comparison produced, key ratio outside the ATO range
3 Comparison produced, but accounts still carry suggested buckets

What it does not do

  • It is not tax advice, and sitting outside a range is not a finding that anything is wrong. The ATO publishes ranges precisely because businesses differ.
  • The bulk dataset the ATO publishes carries the two key ratios only. Labour, rent and motor vehicle ratios are calculated and shown, but the ranges for them are on the ATO's individual industry pages and are not in this dataset yet.
  • Activity statement benchmarks are not covered. The ATO has not produced them since 1 July 2017.
  • It reads a profit and loss. It does not read a tax return, so it cannot see the W1 label, the salary and wages code, or anything else that only exists at lodgment. Pass --w1 if you want the ATO's W1 rule applied to the labour ratio.

Client data

Nothing leaves the machine. There is no network call anywhere in the runtime.

The .gitignore blocks the file names a real ledger arrives under, including pnl*.csv, mapping*.csv, spreadsheets, and client-data/. The example files are invented. Do not commit a real one.

Benchmark data

Year Business types Source
2023-24 100 ATO Small Business Benchmarks, data.gov.au
2022-23 100 same dataset

Each shipped file records the resource URL, the date it was retrieved, and the SHA-256 of the ATO workbook it was built from. The comparison prints all of that, so a report can be traced back to a specific published file.

To add a year when the ATO publishes one:

uv run --with openpyxl python tools/build_dataset.py \
  --xlsx small-business-benchmarks-2024-25-data.xlsx \
  --year 2024-25 \
  --resource-name "2024-25 Benchmarks" \
  --resource-url https://data.gov.au/... \
  --resource-last-modified "<observed resource modification timestamp>" \
  --retrieved "<actual retrieval date YYYY-MM-DD>" \
  --out atobenchmark/data/benchmarks-2024-25.json

Replace the placeholders with the actual observed resource metadata for the build.

The builder refuses a workbook whose columns are not where it expects them, rather than quietly producing a dataset with the ratios in the wrong places.

Attribution

The benchmark figures are derived from Australian Taxation Office data, Small Business Benchmarks, used under CC BY 2.5 AU. The data has been converted from the ATO's spreadsheet into JSON, and turnover band bounds have been made adjoining as described above. No published ratio has been altered. The ATO has not endorsed this tool and has nothing to do with it.

The code in this repository is MIT licensed. The data attribution is also recorded in NOTICE, which ships inside the wheel and the sdist.

Author

Written by Ryan Duguid, a provisional member of Chartered Accountants ANZ, independently, in his own time and on his own equipment. Nothing here is the work of any employer, and no client data was used to build or test it.

Every ATO rule it implements was checked against the ATO's own published pages, and the shipped benchmark figures were cross checked against the ATO's industry page for the same industry.

Metadata

Release files for ato-benchmark-compare 0.1.7

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for ato-benchmark-compare 0.1.7
File Size Uploaded
ato_benchmark_compare-0.1.7.tar.gz 84.7 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for ato-benchmark-compare 0.1.7
File Interpreter ABI Platform
ato_benchmark_compare-0.1.7-py3-none-any.whl Python 3 none any Details

Total release size: 135.8 kB

Release files / ato_benchmark_compare-0.1.7.tar.gz

Download URL ato_benchmark_compare-0.1.7.tar.gz
Size 84.7 kB
Tags Source
SHA-256 checksum
How to use checksums
189adcb0bce73e7ee9cd4a9db5b0007b5aff5dbfefb09dfa0fae1fe7350cd72e
BLAKE2b-256 checksum
How to use checksums
41fe50d244c007d5e375989a3c2a7b475e46ccfb5dbd24694c20c5b5d7a4c773
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 12, 2026.

Transparency log

Release files / ato_benchmark_compare-0.1.7-py3-none-any.whl

Download URL ato_benchmark_compare-0.1.7-py3-none-any.whl
Size 51.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
bc84b724ed9fdf832d48b725b6ca8b3dccf8f153d284c5a909e4b1c95df78e13
BLAKE2b-256 checksum
How to use checksums
9050065409746c995fa4c07521408cbda74497ab6e568f7075efdc5cc33c0943
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 12, 2026.

Transparency log

Release history Release notifications | RSS feed

0.1.11

2 release files

0.1.10

2 release files

0.1.9

2 release files

0.1.8

2 release files

This release

0.1.7 This release

2 release files

0.1.6

2 release files

0.1.5

2 release files

0.1.4

2 release files

0.1.3

2 release files

0.1.1

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page