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Variance Monitor ensures accurate data. NRG and GenOn discover real power.
Merger with Fortune
500
energy provider
Efficient variance
testing process
100% accuracy with
payroll simulation run
Time and effort
saved
About NRG Energy
Headquartered in Houston, Texas, NRG Energy is an energy generation and retail energy provider with a diverse portfolio. The company’s retail electricity providers, which include NRG, Reliant, Green Mountain Energy, Cirro and Direct Energy, together serve about 7.3 million residential, business, commercial and industrial customers. As a Fortune 500 company with about 15,000 employees, NRG is committed to managing their business in environmentally responsible ways while offering products and services to help their customers do the same. Newsweek recently listed NRG as one of America’s most responsible companies.
GenOn Energy, Inc., was one of the largest independent power producers in the US with the capacity to generate more than 14,000 megawatts of power. The company was acquired by NRG Energy in December 2012.
The EPI-USE Labs support staff said I would be able to use Variance Monitor to run a simulation and compare results against the original without ever creating a new payroll. I thought,‘Wow! I didn’t know that...let’s try it.’ It was great... and it allows you to process large volumes.
About the project
Mergers are inevitably a source of trepidation for data and system managers. Vast amounts of information from different systems must be relocated quickly and accurately; error is always a risk; and time, cost and expertise are invariably in short supply. The union of NRG Energy and GenOn Energy showed that the negative effects associated with mergers can be mitigated. This successful integration can be attributed in part to the use of Data Sync Manager™(DSM) and Variance Monitor™, both EPI-USE Labs’ solutions.
We absolutely counted on those reports to help us identify the variances, help the testing teams focus, and also show the management that we were working through the problems.
Merger of NRG and GenOn
When NRG acquired GenOn in 2012, the two companies were faced with the integration of two very different systems and processes. GenOn, the smaller company with about 3,000 people, was on a full SAP® platform using CATS; while NRG’s 6,000 employees were using ADP for payroll and a system called eTime for time entry. An interface to load eTime data to Infotype 2010 (which is the additional payment information) had already been built, and the plan was to convert the NRG population to CATS in three rollouts.
The payroll challenge
The first complication in the move to CATS was that time processing was determined by personnel area, and required extensive payroll schema modifications. Both the time processing and the schema changes would need to be tested, which would involve a huge effort as well as the analysis of thousands of payroll results to be sure that the changes had no negative effects.
DSM was used to copy the employee population on Production to the test system; then the old eTime data was deleted and the corresponding CATS data added back. Once this was complete, Variance Monitor was used for the payroll comparisons. At this point it became apparent that testing could be done based on a simulation run, which would speed up the testing phase significantly and, crucially, deliver 100% accuracy.
It was necessary to change the configuration of the savings plan for one of the union groups. I was able to make the appropriate change and run the Variance Monitor whileI went to lunch. When I returned, I had a detailed report of exactly which employees had changed and in what way but, more importantly, I had a regression test assuring me that the8,000 employees who weren’t supposed to be impacted, remained unchanged.
Variance Monitor plots the way forward
Variance Monitor incorporates Statistical Analysis reports. These were integral to managing the variation testing process because they create a graphic interface that is ideal for showing the total population of the employees under scrutiny, as well as the testing status, and how it was progressing. The reports helped track progress, and management could instantly see that the data was, for example, 80% correct, with a 20% variance that would need analysis. Variance Monitor made it easy to verify potentially hazardous changes to rules, schemas and configuration.
The project took three months and was delivered on time, thanks to Variance Monitor. Initially three parallel tests were planned, but because of Variance Monitor’s ability to show the completeness and testing through the reports, only two parallel runs were needed.
I use it all the time now as a regular testing method for Production support. It’s easy. After we had used it for the time project, we saw other things that it could do. It could compare an external file to internal SAP wage types, so it could do all the data loads and confirm that all the data actually got loaded into the SAP system. There’s probably much more that I don’t know it can do, but I’m learning.
The benefits of Variance Monitor
Variance Monitor enables users to:
- see fluctuations and discrepancies in detail, which means that problems can be resolved before they happen
- create multiple rules to easily determine the course of problems on a large scale, rather than person-by-person
- easily repeat period-to-period runs; no need to reinvent the wheel each payroll
- run in a simulation mode for config changes; issues are identified and corrected before payroll is opened
- save time and effort.
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