For years, HDI and many others have been touting the benefits of the shift-left approach, meaning to move repetitive, simple answers and tasks into self-help or Level 0, and move some incidents from Level 2 to Level 1 for resolution. In other words, it reduces escalations and moves resolution closer to the end user, but how does automation come into play?
Even though this strategy has often been described as a cost-reduction strategy, it can more accurately be viewed as a service improvement strategy with resulting cost reduction as a benefit. This is why automation plays an important role in the shift-left mix, along with other emerging technologies.
What is Service Desk Automation?
In simple terms, automation is establishing a set of repeatable steps which can then be done without further human intervention. So, the first things you should think about automating when it comes to the service desk are the simplest and most repeatable, and those where the most value can be generated with the lowest effort.
Most organizations already have some form of automated password reset, removing most of what used to be, on average, about 30% of a service desk’s call volume. Other automated service request tasks may include:
- Computer replacement
- Software licensing, upgrade, and installation
- Access to shared resources
- Ordering consumables such as printer toner cartridges
Read more: Service Desk Automation – 10 Innovative Ideas to Boost Efficiencies
Usually, any one of these automated processes kicks off notification and/or approval processes, checks inventory, and assigns work to the appropriate team. The end user clicks on an item or service, provides basic information, and the service or item is delivered. Unless there are questions about the request or it falls outside standards, there are few manual processes involved, and no involvement directly by people at the service desk.
This strategy does have side-effects, however, and we should be aware of them before they take us by surprise.
Understanding the Influence of Automation on Standard Service Desk Metrics
Let’s look at some of the most common service desk metrics and at what happens when automation is doing its job:
If you are a senior manager, is this the kind of change you want to see? Does it make sense for there to be fewer tickets resolved during first contact? Probably not, unless you understand that these are exactly the kinds of results you should be expecting, and that they are positive signs that automation is doing its job.
Let’s take a closer look at these results.
If we remove most of the simple, repetitious work going to the service desk, what’s left is the more difficult work that requires the most effort. The consequences for standard metrics then can be massive:
- First Contact Resolution Rate (FCRR) drops dramatically when simple issues are automated
- Average Handle Time (AHT) skyrockets as brief contacts are eliminated and longer conversations are required for nearly every contact
This shows how two of the metrics that have for years established the efficiency and effectiveness of the service desk are radically changed, and in directions that have always been considered unfavorable. Say, for example, that AHT increases from 8 minutes to 16 minutes, and FCRR drops from 71% to 19%.
From the standpoint of traditional metrics, that looks just awful. But, from the standpoint of a modern service desk, it really looks good. The smart people you pay to figure things out are, in fact, figuring things out and not just providing the same resolution they did ten times yesterday.
But there’s even more…
One of the ways in which new technologies can play a role in shift-left is by assisting users, including employees and customers, in finding relevant knowledge and answers to their questions. This can be achieved by using self-help technologies and intelligent knowledge management tools that provide valuable information in the user’s context.
Instead of giving users a single destination to go to, these technologies bring relevant solutions right to where the user is working—in the form email, in a database, creating a presentation, etc. Increasing the use of self-help will drive another round of changes in the metrics you have been tracking for years.
What Should You Be Measuring?
It’s important to measure the results of our efforts, just as it always has been. You want to make sure that your automation efforts are succeeding. We’re used to measuring at the service desk, but—since we’re going to be removing some traffic—we need to measure elsewhere as well.
- Number of interruptions of service seen in monitoring and reporting (tickets created by autologging) versus the number of incidents reported to the service desk by end users
- Number of end users visiting self-help who do not contact the service desk afterward (self-resolved)
- Number of end users visiting self-help who do contact the service desk, indicating they were unable to find a resolution (items for improvement)
- Difference in contact volume after automation versus a like period (January/January, for example) before automation.
Of course, you will also want to track the effectiveness of your self-help by utilizing some knowledge management metrics such as:
- Time to Publish – average time from knowledge article creation to when it becomes available in self-help
- Percent Published – the percent of knowledge articles available kin self-help
- Known Ratio – the percent of tickets resolved using existing knowledge
- Level Zero Solvable - the percent of ticket volume that could be moved to self-service if customer adoption is increased
Over the years, it has become common for service desks to gather “feathers in their cap” for First Contact Resolution, shorter call times and wait times, number of tickets resolved, and so on. Intelligent self-help can reduce contact volume by 30% or more.
Now it is imperative to realize that the service desk is a component of a larger effort to provide excellent information technology and other services to end users and customers. In today’s highly competitive business environment, users cannot afford to wait.
In the era of increasing demand for technology support—68% of organizations reported an increase in ticket volume in 20191 according to HDI research—coupled with flat support budgets, organizations can’t afford not to automate where possible.
The tried-and-true operational metrics we’ve relied on for years will no longer be adequate for measuring the new state of service and support. This does not mean metrics go away, but they do require a new vision.
