Pillar 1: Reactive Support Services

Fast, Experienced Support Built on Process

We understand that, above all, our clients want their IT systems to work consistently — and to be fixed quickly and correctly the first time. Our Reactive Support Services are designed with processes we’ve spent years testing and revising based on real-world experiences and feedback from our clients.

We’re fast. When a support request comes in during regular business hours, we will triage the case within a maximum of 12 minutes (our current average is three) — quickly categorizing each type of issue so that we aren’t just making a quick fix, we’re using that data to prevent future occurrences. More than one technician may then start work depending on the impact and severity of the problem. And, of course, we offer the same level of support outside of business hours for critical issues that just can’t wait until morning.

Being “Powered by Process”, our reactive support desk utilizes a Ticket Dispatch Workflow System to streamline the triage process and achieve greater efficiencies when our clients need support. Doing so ensures that each issue is handled in a consistent manner, delivering the best possible outcome for our clients, no matter which team member addresses the issue.

When clients implement our comprehensive process, their reactive issues drop significantly over time. We call these issues that need reactive support “noise,” as they greatly impact productivity and detract from the bottom line. Noise is any technology issue that slows down employee performance and impacts their ability to be productive. Much like an onion with many layers, our clients’ systems are complex with layers of technical inefficiencies and problem areas. As we continue to use data and best practices to streamline systems, the onion gets smaller and smaller over time, resulting in a less reactive environment with fewer support calls and revenue losses due to downtime.

We Track Everything — And Use it to Serve You Better

After a problem is resolved, we don’t just close the support ticket and move on. We take note of (and report on) the average:

  • Tickets per endpoint per month
  • Time per ticket to resolution

Analyzing that data reveals patterns regarding:

  • Response times
  • Systems that are failing most often
  • Kinds of requests received
  • How long downtime lasted
  • Where the “noise” and risk are greatest

More importantly, these metrics inform other components of our methodology, allowing us to provide valuable counsel to company stakeholders about improvements to IT systems that will make a measurable difference in operations. Using this data, we actively work to drive down the number of support calls over time, positively impacting employee productivity.