8 metrics to help you assess your IT Self Service success

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For both your organisation, and hard pressed IT and service management leaders, trying to deliver better End User support under ever tighter budgetary constraints, self-service promises high valuable wins.

To begin with, there’s the promise that Service Desk overheads might be lowered. Then there’s the possibility that demand on overstretched Service Desk resources might be eased. There’s also the promise of improvements in end-user satisfaction, with staff empowered to find the resolution to issues, or requisition routine service catalogue items, quickly and easily for themselves.

The danger of judging Self Service performance using 1st line KPIs

Quantifying the success of self service support portals, knowledge bases and other tools cannot be done using traditional Service Desk assessment measures.

Call volume and effort, traditional measures of Service Desk reporting, shed little light on the usage and efficacy of self-service resources, or on areas in which Self Service might merit further investment.

Furthermore, where budgets are based on support agent staffing, metrics that show only reduced IT Service Desk transactions, without reporting an increase in Self Service requests and resolutions, could actually endanger an organisation’s entire Support provision.

Plan-Net’s thinking on tracking Self Service Support

As an expert provider of End User Support services, Plan-Net puts great value on self-service support components. However, we believe that the key to gaining the user benefits and cost savings offered by Self Service depends on obtaining data and reporting appropriate to the consumption and resolution rate of the service, as well as its impact on usage of the Service Desk.

Here are 8 up-to-date KPIs (six relating to measuring Self Service support itself, plus two modifications to existing 1st line support KPIs) for understanding how your self-service is performing. (These draw on an excellent paper, ‘8 KPIs That Demonstrate How Self-Service Initiatives Advance Your IT Service Desk’, published in March 2019 by Gartner.)

6 KPIs for measuring your Self-Service Support

So let’s begin by looking at 6 KPIs which look directly at Level 0 metrics:

KP1 1 - Measure your Total Cost per Contact

If you’re tracking only the cost of calls to your Service Desk, you’re not working with complete data. An omni-channel service desk should track the total cost of Support staff, the IT Service Management tool and all self-service tools, so you can consider these alongside the volume of calls, emails and other support tickets.

As few support issues are resolved by a single point of contact, tracking total cost per contact lets you establish: 

  1. The actual cost of support where multiple channels are used to gain a resolution; For example, if your chatbot costs £3 per contact, and live chat £15 per contact, an issue resolved by chatbot alone saves you £12; but if live chat is still needed after the chatbot to achieve resolution, then the chatbot has pushed costs up by £3.
  2. ii) the true total cost of providing support when self-service is being offered; You’ll be able to see whether, across a period, support costs less, or actually costs more, as a result of your self-service tools.

In the end, you’ll want to see your Total Cost Per Contact going down, meaning that the availability of your self-service tools is improving support productivity, with savings being made as a result.

KPI 2 - Measure your self-service Success Rate

 Simply measuring how many issues access your self-service support portal without requiring subsequent assistance from 1st line is not an adequate way to gauge the Success Rate you’re achieving at self-service.

If self-service successfully deals with 100/100 requests, but is not used at all for 10,000 other requests it might have resolved, then the 100% success rate it indicates is being delivered to only 1% of issues. To establish your Success Rate usefully, you need to look at self-service portal searches of your service request catalog and of your knowledge base.

Knowing how well your self-service provision enables products to be ordered from your service request catalog, as well as the percentage of service catalog requests being entered as free text in a ‘miscellaneous’ form and so requiring human processing, tells you how easy your catalog is to use, as well as how well its contents meet your users’ requirements.

Determining the percentage of times that a portal search takes a user in a single click (and then also in three clicks) to a knowledge base article that provides at least a partial solution to their issue lets you assess the quality of the content and search tools you are providing.

Ultimately, you will of course need to see your self-service Success Rate going up, showing that more users are turning to, and finding a solution from, your self-service portal or knowledge base.

KPI 3 - Record self-service Failure Rate

This is not a measure of how frequently issues taken to self-service fail to provide the user with a solution. Rather, it’s a measure of the rate at which your self-service provision is failing to be used for issues which it would have been capable of resolving. Given that, according to Gartner, up to 75% of contacts to the IT Service Desk are for issues which could potentially be solved at self-service, the significance of this metric is clear.

To work out at what rate your self-service is experiencing failure, you need to measure how many issues that could potentially be resolved at self-service are finding their way directly to Level 1. Doing this involves tagging and identifying tickets which should be Level 1 resolvable.

This will include:

  • issues for which a solution is documented in a user-accessible knowledge base;
  • issues which are repetitious and so for which a solution could be, but is not, included in a knowledge base; and
  • issues whose contact category is tagged ‘automate’ in an eliminate, automate or leverage (EAL) analysis.

You’ll want to see your self-service Failure Rate falling, meaning that more of your users are finding support solutions via self -service.

KPI 4 - Monitor Fulfillment Time

It is a critical criterion for self-service support that it should resolve issues for users faster than were they to seek help via phone or email. Unless it achieves this, it’s impossible to see why usage should increase.

With automation, many requests should be fulfilled within minutes. Regardless of whether your organisation has blocked email and phone service requests, or your system requires manager approval of automated updates or resets, for example, your self-service support is failing the business if overall fulfilment times (taking into account both process and portal design) are static or increasing.

KPI 5 - Measure End User and Organisation Satisfaction

You need to be able to measure both the satisfaction of end users with the service available to them, and that of your organisation with the ROI being achieved with self-service support as an element of overall IT support. This can be trickier to measure than some of the earlier KPIs, given that satisfaction is largely an emotional response.

A well designed and provisioned service that delivers successful resolutions in good time could still score poorly on End User Satisfaction if a grudging user base cannot overcome the earlier luxury of attention to every request via telephone or email. Temporary drops in satisfaction will frequently occur where Level 0 tools and policies are introduced, making it critical to sustain sensitive monitoring.

A resource which continues to deliver low End User Satisfaction will produce a poor return for the organisation, with the potential for uncomfortable outcomes.

The best way to establish that IT Support overall, with its self-service component included, is meeting the needs of the business, and that End User and Organisation Satisfaction is improving or at least holding stable, is with a mix of surveys, feedback and Net Promoter Scores.

KPI 6 - Factor in Peer Support Overhead

According to Gartner, while 57% of business end users rank calling IT Support as their first preference to resolve an IT issue, only 11% placed ‘using a self-service knowledge base’ first, and only 4% ‘using a virtual support agent’.

In contrast to this, 48% of users said that their preference was simply to “ask a colleague”.

Peer support, whether at the casual level of asking a colleague at the next workstation for help, or via a formal peer-to-peer assistance platform provided by the organisation as part of its support resource, is difficult to measure, but can clearly play a significant role in issue resolution.

Measuring peer support is not an exact science. Observation and interviews both afford insight into its extent and nature, while time-tracking tools can help to quantify time spent (and time saved). However, caution is needed to avoid this in itself becoming a disruption to productivity.

In the end, peer support is most valuably considered in tandem with the other KPIs above.

Increased peer support, with acceptable time spent, alongside a good overall user satisfaction score would be a positive finding, showing that users are helping each other as an active component of an all-round successful support offer.

Increased peer support alongside general user dissatisfaction, however, would suggest that users are turning to each other out of frustration at the inadequacies of the support on offer.

Two 1st line support KPIs in need of updating

The 6 KPIs we’ve considered so far all relate to the performance of self-service support itself. Self-service does not, however, exist in a vacuum, and the KPIs and metrics generally used to measure Level 1 support require some modification if they are to be used to provide accurate insights.

KPI 7 - Contextualise consideration of First-Contact Resolution (FCR) Rate

FCR Rate has its place, and indeed remains the go-to KPI for IT management in many situations. But FCR Rate is a flawed indicator when it comes to understanding the value of self-service support, and the interaction between self-service and their Service Desk.

Traditionally, we point to a high FCR Rate as indicative of a well-performing Service Desk capable of resolving a high proportion of issues without escalation to costly 2nd line or 3rd line support.

But in very many situations, 1st line requests will include a high volume of simple issues such as password resets. As these could easily be automated and shifted left to self-service, this could bring about a reduction in the volume of such issues presenting at 1st line. Consequently, it would be likely that a Service Desk then concentrating a higher proportion of its time on more complex issues less likely to be resolved at first contact would see a resultant lowering of its FCR Rate.

Clearly, if understood and judged correctly in the wider context of omni-channel support, this is not a bad thing. However, without a proper understanding of the dynamics at C Level, IT management risk unmerited challenges to the efficiency of their Service Desk resource.

KPI 8 - IT Service Desk Call Volume

Really a metric, rather than a KPI, call volumes to your Service Desk are useful for assessing operational need, but should not be relied on to indicate the performance or value of self-service support.

Simply because Service Desk call volumes are down does not mean that self-service support is performing efficiently or effectively. Consequently, a more valuable metric to track is the experience of contacting the IT Service Desk.

This will, of course, be heavily influenced by other productivity, efficiency and satisfaction metrics but if, for example, Wait Time is stable and Call Time is up, it’s reasonable to infer that your Service Desk is spending more time per call dealing with issues which cannot be solved at self-service.

However if Wait Time is increasing, then either your self-service is not entirely successful, or else your support needs cannot really be fulfilled by automation and you may well be in need of greater 1st line.

In similar vein, if Call Time were stable but Wait Time were decreasing, you might conclude that self-service is proving itself appropriate for  many of your support needs and that pressure on your Service Desk is being lessened as a result. This would give you the options to reduce staffing levels, redeploy resources, or focus on longer, leveraged phone conversations.

Conclusions for understanding your self-service support

Our view at Plan-Net, in line with that of Gartner, is that to draw valid conclusions from your data, self-service KPIs must be interpreted in terms of your organisation’s specific user demographics.

Gartner found that younger users, or more confident and adventurous users, were more likely to choose self-service for preference. Conversely, the less confident users were, the less likely they were to attempt to find a solution using Level 0 provisions.

In the end, if you are able to identify specific factors which mean that a greater or lesser preference for self-service support can be attributed to an individual department or location or level within your business, then you’ll be able to establish a greater, and so more valuable, understanding of the KPIs discussed.

If you’d like to talk to us about self-service support, and about how to implement and monitor its impact on your users, as well as on your total IT Support strategy, do get in touch.

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Pete Canavan
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