Measuring ROI of mainframe batch optimization
In our introductory blog on this topic, we discussed the primary business impacts of failing to perform mainframe batch optimization. In this blog, we will touch upon the importance of planning for, and measuring the ROI of the mainframe batch optimization methodology.
Step three of the methodology considers defining the success criteria. As with any initiative, the most important part of measurement is to plan what will be measured. For mainframe batch optimization, it is clear that an assessment of the overall ecosystem will yield several dependencies, business process duplication as well as data inconsistency and duplication. As we build out short-term initiatives as well as a long-term roadmap to resolve these gaps, the benefits case can be built out.
It is useful to segregate the benefits case into various categories to avoid capturing only the most obvious:
- Cost of execution: Can we minimize CPU cycles? This is the most common low hanging fruit that most initiatives go after, by either improving performance or consolidating multiple processes.
- Business opportunity lost: Several cross sell or upsell programs may depend on how well and how quickly the programs run.
- Time to market and cost of new business opportunities: Mainframe batch optimization is an important contributor to launch new initiatives quickly and effectively.
Download the white paper “Business Agility through Mainframe Batch Optimization” to learn more. However, it is important to execute activities at each step of the methodology to meet business objectives in a comprehensive fashion.
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