If mission-critical IT is moving out from the data center, and toward the edge, CIOs and other IT leaders should consider if it makes sense to decentralize IT technical support employees so that direct support can be provided at the edge.
According to Grand View Research’s “Edge Computing Market Size, Share & Trends Analysis Report, 2021 – 2028,” the edge computing market will exceed USD 61 billion by 2028. This equates to a compound annual growth rate of roughly 38.4 percent over the following six years. Unfortunately, the IT staff required to support the expansion of edge technology in businesses is not growing by 38.4%. It’s time for IT to figure out how to support all of this edge technology.
Here are seven strategies that organizations can adopt.
Adopting an Account Management Approach
Account managers are often assigned by IT vendors to major customer accounts to manage relationships. If a problem emerges, this account manager can mobilize the necessary resources and ensure that work and support are completed to a good resolution.
The account management strategy with end-users can benefit IT, especially if users have a lot of edge applications and networks. When a persistent problem emerges, an appointed business analyst who communicates with tech support and others in IT can be the point of contact for an end-user department. This account manager can also visit the user department regularly to assess IT support and technology performance.
If end-users feel they can go to someone if they need to escalate an issue, they are more likely to communicate and collaborate with IT.
IT must ensure that IT assets at the edge are secure and that only those allowed can use them from a security and governance standpoint. End-users can’t be expected to implement security and governance independently, and if they don’t, a breach can quickly escalate into a massive support issue.
Zero-trust networks automate the IT monitoring and security process to prevent incidents by monitoring every IT asset on the network. If there is a breach – or the deployment of a new edge IoT solution that IT is unaware of – the network detects it immediately and sends out an alert.
Maintenance that is done ahead of time
If network routers, industrial robots, workstations, drones, and other devices are not properly maintained, they will fail. AI analytics software for preemptive maintenance is now available, which monitors edge IT assets and sends out alerts anytime a potential problem is spotted. This allows technical help to address a problem before it becomes a significant issue.
These fixes can often be performed remotely from a central location. This cuts down on travel time and expenses for IT technical support.
Software Upgrades Should Be Automated
A key contributor to the technical support workload is the failure to upgrade firmware and software proactively for performance enhancements and security vulnerabilities. Many of these upgrade-related technical support issues can be avoided by using firmware and software automation software that automatically deploys new updates as they are released.
When it comes to network and system backups, the same rule applies.
End users can avoid downtime by automating the backup process and establishing recovery points for these assets. Simultaneously, automated backups and failovers provide more non-stressful time for technical support to examine what happened during an issue and design a solution to ensure it doesn’t happen again.
Technical Support Knowledge for Application Design Processes
Technical support is one area of IT that is well equipped to provide insight into how and where networks and systems are failing. This is because technical support is out on the field daily, hearing about issues from end-users, troubleshooting them, and figuring out what’s wrong.
Suppose technical support knowledge about where network and system issues arise on the edge is applied to initial application design processes. In that case, it is quite likely that the first application design will avoid many of the existing difficulty spots that afflict existing applications.
Because systems don’t constantly break, this increases customer satisfaction. The workload of technical support is also reduced due to fewer system failures.