IT orgs feel less locked into their network management tools, particularly as they look to apply AI/ML to tasks such as intelligent alerting, change management, and capacity management.
Nearly 74% of IT organizations are at least somewhat likely to replace a network management tool over the next two years, according to new research from Enterprise Management Associates (EMA).
“I don’t think anyone is tied to their existing tools,” an IT operations manager at a very large government agency recently told an EMA analyst. “If a new tool comes along that is better or cheaper, we’ll consider it.”
Tools aren’t as “sticky“ as they once were
For a variety of reasons, network management tools have historically been sticky in IT organizations. First, tool vendors sold them with perpetual licenses, which meant a long-term investment. Second, tools could take time to implement, especially for larger companies that invest months of time customizing data collection mechanisms, dashboards, alerts, and more. Also, many tools were difficult to use, so they came with a learning curve.
But things have changed. Most network management tools are now available as SaaS solutions with a subscription license. Many vendors have developed new automation features and AI-driven features that reduce the amount of customization that some IT organizations will need to do. Tool vendors have also focused on improving ease of use, through modernized GUIs and AI features that provide natural language insights.
For all these reasons, many IT organizations feel less locked into their network management tools today. Still, it’s important to note that replacing tools remains challenging. In fact, network teams that struggle to hire and retain skilled personnel are less likely to replace a tool. They don’t have the capacity to tackle such a project because they’re barely keeping up with day-to-day operations. Larger enterprises, which have larger and more complex networks, were also less open to new tools.
“In general, my organization is pretty open to changing tools,” an IT tools architect at a Fortune 500 media recently said. “But the more complex your organization is, the more complex it is to replace a tool. But we are open to trying something new to try to solve problems better.”
New tools to solve old (and new) problems
EMA believes that this readiness to replace network management tools is driven by longtime inefficiencies in network operations groups along with emerging challenges presented by new technologies. Regarding longtime inefficiencies, EMA’s new Network Management Megatrends 2024 report, based on a survey of 406 IT professionals, revealed that network teams are more likely to replace an incumbent tool with a new one if they are:
- Experiencing a high volume of network outages and degradations caused by manual errors
- Spending a large percentage of their work days on network troubleshooting
- Lacking defined network operations processes
EMA’s new research also found that network teams were more likely to replace a tool if they were dealing with multi-cloud networks or secure access service edge (SASE), two newer technology architectures that are highly disruptive to network operations. In particular, a network team was more likely to swap tool vendors if it was struggling to monitor the health and performance of the cloud points of presence where SASE vendors host their security functionality.
What to look for in new tools
A network engineer at a Fortune 500 aerospace and defense company told EMA that his company was open to new tools. A switch would be driven by “depth of functionality, the network [equipment] that it supports, and cost.”
EMA’s Megatrends report confirmed that depth of functionality is as major consideration when network teams look at a new tools. Research participants who were open to new tools were more likely to seek the following tool capabilities:
- Aggregated network health score reporting
- Auto-discovery of services and dependencies
- Automated topology mapping
- Support of streaming telemetry
- Support of synthetic network traffic monitoring, particularly for monitoring of hybrid WAN performance and end-user experience
Finally, EMA research revealed that interest in applying artificial intelligence and machine learning (AI/ML) to network management correlated strongly with openness to new tools. They were especially interested in new tools if they wanted to apply AI/ML to intelligent alerting, change management, capacity management, and conversational tool queries via chatbots/virtual assistants.
