Modern IT means multiple cloud environments, big data, advanced analytics, and an increased rate of change to existing and new applications. More workloads are focused on collecting a variety of data types. All that data must be moved, stored in big data environments, and processed through analytics tools. The digital transformation that is overtaking enterprises in all industries is further complicating the task of managing the changing workload landscape. While workload automation is a mature space, it underwent significant enhancements since this study was done in 2013. WLA vendors and users had to address all of the changes imposed on IT operations. Workload automation may not have the cache of virtualization, software-defined networking, or containers, but it remains a foundational element to well-controlled IT operations. 

This research updates many of the data points collected in the 2013 "Workload Automation in an Era of Cloud, Analytics, Enterprise Mobility, DevOps, and Big Data" research, and adds new measures for recent innovations. The 2013 study was conducted with 176 workload professionals and IT leaders in North America. This year's study was expanded to 228 respondents, including 132 North American and 96 European workload professionals, IT leaders, and some business users involved in using dashboards to monitor their workloads. With a substantial number of questions asked in both studies, trends are examined from 2013 to 2016.