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Case Study: Large Financial Co. Selects CA over BMC and Improves Productivity over 80%

Introduction

This case study of a large enterprise financial services company is based on a January 2013 survey of CA Workload Automation customers by TechValidate, a 3rd-party research service. The profiled company asked to have their name blinded to protect their confidentiality.

“CA Workload Automation has improved our control over jobs entering our environments. It has also made it easier for us to do audits, monitor jobs and make changes to existing jobs.”

“I am crazy about the new web interface with r11.3.5. That was one of the best improvements in years.”

Challenges

  • Purchased and implemented CA Workload Automation to address the following:
    • Reduce number of job failures
    • Reduce the time required to process workloads
    • Satisfy Compliance and Audit Requirements
    • Improve application development cycles
    • Manage the growing volume of workloads

Use Case

  • Runs 50,000 to 100,000 jobs per day with CA Workload Automation.
  • Supports the following applications with CA Workload Automation:
    • IT Operations (system backups, etc.)
    • Mostly Command jobs
  • Uses the following CA Workload Automation Products:
    • CA Workload Automation AE (AutoSys)

Results

  • Replaced or selected CA Workload Automation over the following vendors:
    • BMC
  • Rated CA Workload Automation’s capabilities:
    • Ease of use and management: highly differentiated
    • Scalability & performance: extremely differentiated
    • Depth of functionality: extremely differentiated
    • Platform & application support: extremely differentiated
    • Return on investment: extremely differentiated
  • Achieved the following after implementing CA Workload Automation:
    • Reduced job failures: 80%-100%
    • Improved staff productivity: 80%-100%




About This Data

This data was sourced directly from verified users of CA Workload Automation by TechValidate.

TechValidate verifies the identity and organizational affiliation of all participants that contribute to published research data. When research participants so desire, we also guarantee their anonymity so that they may share information honestly and freely.


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