SAP User License Optimization Calculator
License cost is often the most visible number a Basis team can move. This calculator separates the two main levers, removing inactive users and moving over-licensed users to a lower type, so you can size the prize before starting the clean-up.
Your numbers
Use your contract price or support-inclusive cost. The default is a placeholder.
From last logon date (USR02 TRDAT) and usage statistics.
Your results
Model only. Real SAP license metrics depend on your contract, user type definitions and measurement results from USMM and LAW. Cost reductions may not be realised until the next contract true-down or renewal.
Total annual savings vs downgrade share
Sweeps Remaining Professional users who only need Limited from 0 to 60, holding your other inputs fixed.
Get a license clean-up plan reviewed
Share your figures and get a short written review of the assumptions. Optional.
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How to use it
Enter your counts and unit costs from the contract. Estimate the inactive share from last logon dates and the share of remaining Professional users whose roles only need Limited Professional activities. The calculator applies inactive removal first, then downgrade to the remaining population, so the two levers do not double count. Use the slider chart to see what each additional percentage of downgrades is worth.
- Pull last logon from the user master and check for service users
- Exclude technical, system and communication users
- Review authorizations, not job titles, to decide who needs Professional
- Agree the reclassification with the business owner and procurement
The formulas
Inactive savings equal inactive users times the Professional price. Downgrade users equal the active Professional population times the downgrade share, and savings equal that count times the price difference between Professional and Limited. Total savings is the sum, and the percentage divides it by current annual cost. Because the downgrade applies after removal, the model reflects the real order in which a clean-up is done.
Worked example
800 Professional users at 3,000 and 600 Limited users at 1,200 cost 3.12 million per year. Eight percent inactive is 64 users, saving 192,000. The remaining 736 users with 20 percent downgraded is about 147 users saving 1,800 each, roughly 265,000. Total is about 457,000, or nearly 15 percent. The result is sensitive to the downgrade share, which is why the authorization analysis behind it matters more than the arithmetic.
Common mistakes
Counting dormant users as savings when the contract is based on a fixed purchased quantity means no cash is returned until renewal. Downgrading users whose roles still contain Professional-only activities creates audit exposure. Forgetting indirect access, where third party systems read or write SAP data, can erase the saving in a licence audit. Treat the output as a prioritisation aid and confirm every user type change with measurement data.
Frequently Asked Questions
Does removing a user save money immediately?
Not always. Many SAP contracts are based on purchased quantities, so reductions only matter at renewal, at a true-down clause, or when you avoid buying more. Read the contract before promising savings to finance.
How do I find inactive users?
Check last logon dates in the user master, usage statistics and any usage tracking you run. Exclude technical, service and communication users, and watch for users who log on only at quarter or year end.
Can I downgrade based on roles alone?
Roles are the starting point, but the license depends on the activities the user can actually perform and on contract definitions. Compare against SAP's measurement results and keep documentation for any later audit.
What is not included here?
Indirect or digital access, engine licences, package licences and cloud subscriptions are not modelled. Those can dominate the cost in some landscapes and need their own analysis with your SAP account contacts.
Netray can help build a read-only, on-prem view of last logon, role usage and user type across your SAP systems so reclassification decisions rest on current data.
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