Building a successful Jira Service Desk requires a lot of moving parts. It can be difficult to find the perfect balance between ease of use for your agents (those who work on requests) and your customers (those who submit requests). One of the most important ways of achieving that balance is to create a great Confluence Knowledge Base (KB). If your articles are relevant, concise, and easy-to-navigate, your customers can avoid submitting a request, giving time back to both the customer and agent. Below are some common mistakes to avoid as you work towards creating your ideal Confluence Knowledge Base that is a reliable, single source of truth for your agents and customers.
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One of the most important metrics for IT and Customer Service teams that solve problems and answer customer questions is mean time to resolution, commonly referred to as MTTR. Atlassian defines MTTR as the average time it takes for an issue to reach a resolved state, as measured from the time the ticket was created. It’s an exceedingly important metric to track, especially for IT teams because it is one of the few great ways to quantify team productivity. When tracked and reported over time, it becomes possible to determine the efficacy and ROI of business process improvements. While Jira gives us an easy way to track service level agreements (aka SLAs), there is no great built-in tool for tracking MTTR (yet).