A new report published this week by Dresner Advisory Services sheds some light on how IT organizations want to apply advanced analytics to optimize IT operations.
The 2018 IT Analytics Market Study finds that the top four management metrics in terms of importance are software license and utilization analysis, vendor license compliance reporting, alignment of headcount, cloud license optimization, and optimizing time spent on tasks versus project tasks. Within the context of operations, however, the report finds that service experience and service level agreement (SLA) performance along with incident root cause analysis are the top two requirements for IT organizations.Today varied approaches are being used to analyze IT operations. The report finds that 38 percent of the IT leaders surveyed rely on a third-party applications versus 14 percent that have developed their own applications. Another 22 percent collect data manually using spreadsheets, while 20 percent say they don’t measure anything at all.
Implementing IT operation analytics requires significant expertise. The report notes that 93 percent of respondents viewed IT analytics as being “critical”, “very important”, or “important.” But only a little over half of the survey respondents (52 percent) are relying on a third-party applications or have built their own applications. That suggests that there’s a major gap that could be filled by managed service providers (MSPs).
Getting the most value out of your analytics investment
IT operation analytics is prerequisite for IT automation. Most MSPs to one degree or another have already implemented at least one or more analytics application to optimize their own operations. The Dresner survey shows that the next opportunity is to extend those analytics investments to optimize the IT operations for the customer’s they serve. In many cases those analytics are being sought to accelerate a transition to more modern approaches to managing IT using DevOps processes.
But the value of those analytics investments doesn’t end there. The data collected by those IT analytics applications will become a critical source for advanced machine and deep learning algorithms that will be employed to create artificial intelligence (AI) models to automate everything from cybersecurity and disaster recovery policies to how applications update. AI models won’t eliminate entirely the need for IT staff. But the role IT professionals play in managing IT operations is about to change completely. The biggest challenge most organizations will face is that those algorithms are only as good as the quality and amount of data being collected. MSPs are in a unique position to collect enough data to operationalize AI in a way that most internal IT organizations will not be able to accomplish on their own. IT operational analytics essentially provides the foundational technology that will enable MSPs to become the primary catalyst for driving a massive wave of transformation in IT operations.
MSPs are generally aware they need to invest more in automation to remain competitive. What many of them don’t appreciate as much is that as their end customers become more dependent on IT, they will soon be looking to MSPs to apply that automation expertise to almost every aspect of their IT operations.
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