I’m sure you are well aware how important and useful information technology, or IT for short, departments are. Starting a new job and need the computer system up and running? Not a problem. Working through an important financial document when the next ice age blows through, leaving you frustrated over an immovable screen that mocks your every futile move? Not a problem. Is your security system ignoring you while cyber space shattering viruses are invading your computer? Not a problem.
So how can IT companies or departments keep up with the demand for expert level service, especially when most of the people asking for help are two steps away from using a mallet on their computers? Well, the first step is simple. Dissuade customers from using mallets, but I digress. What should be looked at are key performance indicators, metrics and benchmarks. Tracking the data associated with metrics in your IT balanced scorecard or dashboard will not only show the company or department what is actually happening, but it will also show what can be improved. Let’s take a look at a few.
1. Cycle Time: Customer Support Ticket Resolution
This productivity metric measures the number of hours required to close, or resolve, a customer support ticket (also known as a help ticket), from the time the ticket is opened until the issue is resolved. What’s a customer support ticket, you ask? Simply put, a customer support ticket is a mechanism used to track the detection, reporting and resolution of an IT problem. This is a simple metric to understand, right? If not, imagine that your phone system has 5 customers on hold and there’s only one of you. Each customer is paying for service so logic dictates that you should attend to all 5 customers to obtain the most amount of money, right? The best way to do that is to aim at spending only the necessary time required to help the customer. That way, you can get to the other customers before they decide to hang up. Be sure to consider the customer’s satisfaction when you attend them. The Cycle Time: Customer Support Ticket Resolution metric will help you strike the right balance between quick cycle time and customer satisfaction.
The Mean Time to Repair (MTTR) measures the average amount of time (measured in hours) required to repair the system, application or network to full functionality following a failure (i.e., a service interruption), measured from the time that the failure occurs until when the repair is completed and rolled out to all required locations (servers, devices, workstations, etc.). So what’s the optimum value for such a metric as this? Well, imagine the network went down in financial company during the work day due to a security incident. Computers are the company’s lifeblood. So what’s going to happen? You guessed it, the company’s employees will be hovering around you as you fiddle with the system, and their bosses will ask you hundreds of questions, not so subtly urging you to quickly fix the issue. Oh and your boss will be breathing down your neck because you have other customers to attend to. No pressure.
3. Mean Time Between Failures (MTBF)
This metric measures the average amount of time (in days) elapsed between network (or system, application) failures or outages, measured from the moment the network (or system, application) initially fails, until the time that the next failure occurs (includes the time required to perform any repairs after the initial failure). Again, a simple metric to understand, the longer the time period between failures, the better. Be aware that the value for Mean Time Between Failures (MTBF) includes only operational time, not the repair or outage time. Don’t worry though, those are separate metrics. To reduce the Mean Time Between Failures (MTBF) value, attempt to segment the time between failures with the usage of different systems and software packages.
Support Tickets Closed per Employee measures the number of customer support tickets resolved and closed by the customer support team divided by the total number of support tickets opened over the same period of time, as a percentage. Yes, it’s not a good thing to acquire lots of calls since that means there are a lot of issues that need to be resolved, but when it comes to productivity, the higher the number, the better. This value can be used to both indicate which employees need to improve, but it may also help in illustrating the parts of the service that need to be improved. Be sure to keep the customer in mind, however. A satisfied customer is just as important as the closing of a ticket.
5. Unit Cost: Customer Support Ticket
The Unit Cost: Customer Support Ticket metric measures the total expense incurred by the customer support function divided by the total number of customer support tickets opened over the same period of time. Though a bit different than the previous metrics, defining the cost of operations is a must. How else are you to track money, and thus the life blood of any company or department? In either case, this metric keeps track of just how much is being spent to bring computer support to each employee experiencing issues.
Are you looking for a full list of IT KPIs? Download our IT Key Performance Indicator Catalog here.
Thanks for sticking with me thus far. Tracking KPIs, metrics and benchmarks should be on the top of everyone’s to do list. For those within the information technology businesses, doing so will not only bring a higher quality service to their customers, but will also make sure they can stay in the business of providing technological services. Heck, using KPIs, metrics and benchmarks to improve will even help in outperforming competitors and save cost on the bottom line. Now, who wouldn’t like that? Should you need help in interpreting just how to use metric data to improve, reach out to the OpsDog team here for some nifty consulting services and data analysis. Stay tuned for Part 2 where I will discuss the 5 IT Project Implementation KPIs that should be tracked!