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.
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.
