Data-Driven IT Automation and the “More Syndrome”
by Dennis Drogseth, VP of Research, IT Megatrends, Analytics, and CMDB Systems
The results are in from “Data-Driven IT Automation: A Vision for the Modern CIO.” We had 405 respondents, with 200 from North America, 107 from EMEA, and 98 from Asia Pacific when we wrapped up data collection in March. Since then, I’ve spent more than two weeks analyzing it and I thought I’d share answers to some of the questions I posed in my prior blog.
The use cases for strategic automation initiatives were:
- Problem, incident, and availability management
- Configuration, change, and capacity management
- Application performance and workload optimization
We were overall very pleased with the data, which was consistent and sometimes even revelatory. For instance, we had assumed that most respondents would be locked primarily in one use case but this turned out not to be the case, with more than 50% seriously involved in two, and the majority engaged at some level in three and sometimes four. This, among quite a few other data points, spoke to both the growing need and the emerging readiness for IT organizations to think about bringing their automation technologies together more strategically and efficiently across use cases.
The questions list
In a prior blog for APM Digest, I posed a list of questions. With this blog, I’d like to provide a data point or two to address five of the original ten.
- How far along are IT organizations in automation adoption?
When we surveyed respondents, we found that (on average) about 40% of IT processes had been automated. This included a population of 495 respondents, since we terminated those with fewer than 21% of their processes automated, given our goal to seek more in-depth insights into strategic automation initiatives. Among the population finally surveyed, the average was 50% of IT processes automated.
- What IT automation technologies are most prevalently in deployment?
Perhaps not surprisingly, the most pervasive technology was workflow within and across IT. This was true for three of the four use cases; however, workload automation (WLA) led for automation supporting DevOps initiatives, reflecting WLA’s growing relevance for coordinating automation capabilities far beyond job scheduling. On the other hand, when asked about the preferred investment for unifying automation across multiple use cases, IT process automation was the clear winner with its long and proven history in bringing different automation technologies together.
- What is the impact of AIOps and other analytics on automation, as in the titled theme of the research “data-driven IT automation?”
Contrary to many industry assumptions about AIOps penetration, 75% of our respondents had AIOps or related IT analytics either already established as a major initiative or actively in some form of deployment. Moreover, 90% of respondents viewed coupling AI/analytics with automation as a high priority or an extremely high priority. Across the board, when we looked for factors leading to IT automation effectiveness, AI/analytic integration was among those most consistently in the forefront.
- How are trends such as digital transformation impacting IT analytics adoptions?
The short answer is “positively.” When EMA looked at best practices overall (and digital transformation specifically), more best practices and a stronger commitment to tie digital transformation to automation initiatives were both key catalysts in enabling more effective automation outcomes. These results underscored the importance of process, in the human as well as technology sense, for bringing IT organizations together and aligning them with the business.
IT automation and the “More Syndrome”
Perhaps the most critical question in all our research was: What separates IT organizations that are more forward-looking in terms of automation adoption from others? The answer to this correlated strongly to what EMA has already established as the “More Syndrome.” The More Syndrome’s impact in this research was, in fact, especially telling.
So…what leads to IT automation effectiveness?
- More automation technologies in play
- More stakeholders engaged
- More metrics in play
- More best practices supported
- More analytic deployments and integrations
- More processes automated per use case
- More integrated automation across use cases
However, as I reviewed the data in context with our consulting experience, it struck me that it’s always important to remember the “more” so often ignored—more communication and planning. It is just as important to understand your stakeholders, your overall environment and needs, and your IT and business requirements as it is to be diligent in evaluating and adopting technologies stage by stage to address your evolving priorities.
For the “more” on what this research has to offer, I’ll once again recommend our April 30 research webinar, which will offer 45 minutes of context, surprises, and guidance.