IT operations (IT Ops) is one of the most underappreciated jobs in any organization. In addition to trying to implement application changes lobbed over by App Teams, they’re also responsible for managing a technological Rubik’s Cube, where innovation and evolution is happening so frequently they can barely keep up. Couple those stressors with CIO demands for an enterprise-wide digital transformation, and the job can seem impossible.
Rather than proactively plan for digital transformation, IT Ops is dealing with daily and hourly nuisances in the network environment that often consists of siloed tools, legacy systems, and inconsistent data models. In fact, according to Enterprise Management Associates (EMA), more than 70 percent of their time is spent working to simply keep the lights on; and that’s why making the digital transformation is so critical.
In their recent white paper, “How to Enable IT to be a Change Agent; Adopt an Automated, Service-Centric Approach,” EMA explores the relationship between the quest for digitalization and its effect on IT Ops. Notably, EMA suggests that IT Ops is not focusing enough on enabling the enterprise to make the digital transformation, “They [IT Ops] spend a tremendous amount of time putting out fires, rather than proactively preventing trouble.”
EMA then details that only 40 percent of service issues or outages are detected before end users recognize and report them. With the remaining 60 percent of end users already seeing or feeling the devastating effect of a service outage, it’s no wonder that IT Ops is ill-equipped to make the leap.
When asked why IT Ops is struggling to support their service objectives, EMA points to three roadblocks:
1. Mired in Legacy investments
The substantial investment in legacy tools and legacy processes means changing course could be a tedious and time-intensive process.
2. Silo tools, data and processes
The aforementioned legacy investments lead to the production of silos. And since every group uses their own tool, it’s difficult to produce a common data model and processes across their technology domains.
3. Lack of context Context is a major issue in the face of complexity. Specifically, EMA notes that 37 percent of enterprises lack a single pane of glass view into their DevOps and services pipeline.
Although EMA points to three roadblocks, there’s also a critical fourth one at play: the human element.
It’s really the people and who can make or break the road to digital transformation. When moving from traditional ITOps to AIOps, recognizing and planning for challenges is critical. That change isn’t incremental, but it is radical. A memo and some training won’t get the job done.
My colleague Brian Amaro explored this idea in a recent blog, Are You Seriously Ready for AI and ML in Incident Automation (Part 2). In his post, Brian addresses the need to build trust to overcome organizational inertia.
In a recent video blog, Thoughts on the State of IT Operations in 2018, EMA research director Shamus McGillicuddy goes into more detail on the practical issues facing CIOs if complexity, tooling, and human resource issues are not addressed. He also offers some fundamental steps to flip the script and ensure digital transformation makes that improved experience possible.
Those steps include:
• Enable comprehensive, intelligent data collection. Today’s enterprise depends on a complex mix of components, including public and private cloud infrastructure, legacy systems, applications, and more. Identifying and accounting for all sources and types of data and IT resources being used is critical to managing the digital enterprise Simply put, you need a single data model that stores all of the information.
• Establish a contextualized understanding of infrastructure and operations. Context matters in a complex, dynamic environment. A three-dimensional view of configuration item interrelationships and dependencies (infrastructure to infrastructure, infrastructure to app, app to app, and infrastructure to service) is essential to maintaining and managing a service-centric posture. Without context, you just have a bunch of data. Automation is key… relationships are fluid today — humans can’t manually track and map relationships.
• Automate manual processes using contextualized data. Lack of trust in data is a significant barrier to automation. Establishing a common data model and context for that data is crucial to establishing trust, automating processes today–and to provide a platform for future automation.
• Support analytics to better understand operations. A data-driven enterprise thrives on turning data into actionable insights that further support initiatives like process automation and the creation of new products and services based on evolving best practices.
• Demonstrate a capability to support future digital initiatives. Adequate support for new tech can give impetus to adopt tools like public cloud, containers, IoT, serverless infrastructure, software-defined data centers and other tech driving change in the enterprise.
For many, the road to a successful digital transformation is beset with headaches, foul starts and an omnipresent fear of the unknown. And although no journey is ever easy, it’s important for IT Ops to do more than just fight fires as they happen, they need to be empowered to strategically plan for what’s coming. To ensure that your organization is adequately prepared to arrive at the destination with minimal difficulty, download the EMA white paper.