Introduction of LSMW scripting methodology in
Our project to minimise time&effort utilization
for batch scheduling.
Manual scheduling and its challenges:
Manual creation of jobs always is time consuming and more prone to errors. Still manual creation is preferred and feasible if we want to create few jobs like 10-20. But in cases where there is a need to create mass jobs [approx 3000+ jobs] especially prior to cutover rehearsals or go-lives, where time and efficiency are major factors, manual job creation is not at all recommended or preferable.
So in such cases we can make use of LSMW scripting methodology [ Using recording technique of LSMW]
LSMW scripts may focus on the following points:
- Mass job scheduling for setting up Daily jobs.
- Mass job scheduling for setting up Weekly jobs.
- Mass job adding multiple steps to existing jobs.
I can give example of my project where, we had a similar situation where we had to create around 2000+ jobs in a very less time but the manual scheduking of jobs was not at all acceptable due to time factor.
SO here, this LSMW scripting technology worked wonders . The above three scripts worked as a relief for the hectic overhead we used to have during job scheduling. The total time required came down to 2 days at max with one resource working full time where it used to take 10 days with 4 resources.
Later on based on different types of requirement, I prepared some other scripts for:–
- Mass release of jobs [ which earlier took large amount of time, as doing manually we can only release one job at a time],
- Changing the release time of mass jobs at one shot. [Which manually we used to do taking one job at a time]
- An absolute relief from the hectic procedure of manual scheduling of jobs.
- Now a resource can run the script in background and work on some other stuff, hence resource multiplexing can be achieved.
- We now can schedule more than 5000+ jobs within 1 day at min and 2 days max with only one to two resource full time. Hence time& effort is saved resulting into proper resource optimization.