Infor LN Batch Job Window Calculator
Nightly jobs in Infor LN, from planning runs to costing and bulk loads, have to finish before users arrive. This calculator estimates run time and the number of parallel processes needed. Export the result to PDF or Excel for change requests.
Your numbers
Measure it on a representative sample run.
Locking, shared tables and I/O reduce scaling. 60 to 90 percent is common.
Your results
Efficiency usually falls as you add processes. Validate with a test run before changing production job settings.
Duration vs parallel processes
Sweeps Parallel processes from 1 to 32, holding your other inputs fixed.
Batch performance review
An optional expert look at long running LN jobs and their data access.
Optional. The tool and every export work without this. No spam.
How to use it
Time a sample run on a known number of records to get throughput per process, then enter the full volume. Set parallel efficiency honestly: adding processes rarely scales linearly because of table locks, shared index pages and disk contention. The result gives estimated duration, headroom against your window and the processes required to fit.
The model
Effective throughput is per process rate times the number of processes times efficiency. Duration is records divided by that throughput, converted to hours, plus fixed overhead for startup and finalization. The sweep chart shows diminishing returns: the first processes cut time dramatically, later ones barely help because overhead dominates.
Common mistakes
Taking throughput from an empty test database and applying it to production, where data volume changes performance. Forgetting that other jobs share the same database and CPU during the window. And treating the result as exact: give yourself at least 20 to 30 percent headroom for growth and bad nights.
Frequently Asked Questions
How do I measure throughput?
Run the job on a representative slice, note records and elapsed time excluding startup, and divide. Repeat at two different times of day to see variation from other system load.
Why does efficiency drop with more processes?
Processes compete for the same locks, tables, indexes, disk and CPU. Beyond a point, extra processes mostly wait on each other, so measured gains shrink.
How much headroom is safe?
Plan for at least 20 to 30 percent spare window, more for jobs whose volume is seasonal. Volume growth of even 10 percent per year erodes a tight window within a couple of years.
Does this apply to non LN jobs?
Yes. The arithmetic works for any batch with a record based workload, such as integrations, data migrations or report generation.
If batch overruns are hurting your business, we can review job design and data access patterns with your administrators.
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