Beyond First Call Resolution Diagnostic and Measurement Practices for KM
Knowledge management (KM) initiatives are one way of improving technical support organizations, driving support margins through efficiency and increased customer loyalty. However, it is one thing to implement different practices in KM in your organization and another to know that the practices are contributing to your organization's bottom line. In what follows, we outline best diagnostic and measurement practices for judging the effects of new KM practices.
Increasing "first contact resolution" (FCR) is often one of the first goals specified in a project. Organizations often believe a significant reason their satisfaction is low and costs are high is that calls or cases are not solved on the first contact. They regularly point to long elapsed times for cases, poor satisfaction scores and lowered support margins as indicators that they need to improve the expertise of their front-line support personnel and the explicit knowledge that supports their efforts. As we shall see below, this is only partly true. Pursuing this path alone may not fully address the FCR problem and the corresponding cost/satisfaction issue.
Following common best practices, let's examine the situation:
1. Map and model current process: For complex technical support centers, there are multiple interactions or activities, often including three or more touch points with the customer, before any troubleshooting starts. Support engineers may require logs, configuration and sample files just to start their assessments. Adding expensive experts to your front line will only exacerbate the problem. The experts will have to go through the same set of iterations and activities with customers before they get started.
2. Establish metrics: Measuring first call resolution alone does not give you the whole picture. In this case, you need to measure the number and content of the iterations. How much time and over how many iterations does it take an engineer to get the appropriate information from the customer? What is the average elapsed time that cases are open, and what are the cut-off points for customer delight and customer pain?
3. Perform a diagnostic: We often find that the multiple iterations required before troubleshooting can get started do not need to be handled by an expert. In the vast majority of cases, there are technology solutions. In our experience, we can automate the collections of the knowledge required to initiate troubleshooting. Self-service wizards can walk the customer or front-line agent through the critical information required to initiate troubleshooting.
4. Set clear goals: Monitor the underlying processes. Monitor your customers' and agents' quantity and success with the wizards, the elapsed time cases are open and how often the users (customers or agents) get the correct log info to the engineer before they start the troubleshooting process.
5. Develop your future state: Only for some of the problems can wizards collect log and configuration information. Specifying the set of applicable problems for which this is possible is a pre-requisite to quantifying the benefit.
6. Quantify the benefit: Develop word equations to specify the savings. For example, the potential savings from collecting logs automatically is (% of time engineers spend collecting sys files) X (% of time sys files are needed) X (% of time the collection could be completed in a wizard) X (% of time cases are submitted online). The result of this is an efficiency improvement for your engineers. Similar word equations assess the reduction in elapsed time cases are open.
7. Run a continuous improvement process: Using technology to solve problems requires ongoing effort. Make sure you are assessing which problems are likely to apply to this process. Set 30- to 90- and 120-day assessment periods and add/ modify/delete wizards as necessary. You can see that low FCR is a proxy for a host of underlying processes. Measuring your process today and theorizing how your new processes will help you close gaps that underlie problems can help remedy core problems. Continuing to improve and benchmark processes allows you to know how changes improve your organization. Over time incrementally improving and benchmarking improvements will help you reach your customer satisfaction and efficiency goals.
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