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Enhancing Helpdesk Performance: Strategies for Increased User Satisfaction and Efficiency

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6 diapositives · 200 Views · Aug 16, 2014

This report outlines the current state of the helpdesk service, detailing call statistics and user perceptions. With an average of 600 calls weekly, only 20% of issues are resolved on the first contact. To improve, the objectives include increasing first-time resolution rates to 80% and user satisfaction to 75%. Key elements for success involve better training, improved procedures, and enhanced tools for helpdesk personnel. The findings suggest significant discrepancies between user expectations and actual performance, with a promising "Backing Up" model showing potential in improving support.

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  1. Helpdesk Changes Desktop Forum L. Pregernig, 2000-05-29

  2. Helpdesk Changes: Current Situation • Some statistics – “Average Week” • “Average week”: 600 calls • Answered “first time”: 215 • Escalated: 160 by design (eg, EDMS), 225 unresolved to Level 2 • Figures correspond to expected performance at the contract level • User perceptions • “Helpdesk not functioning” • Translates into: “support chain not working”,because users typically refer to the “entry point” (Helpdesk) • Call avoidance • User strategies: ask a colleague, email a friend, call Helpdesk • Comparison with industry (Gartner Group):Industry: 1-2 calls per month and desktopCERN: 0.3-0.6 calls per month and desktop

  3. Helpdesk Changes: Objectives • Objectives • Increase first-time problem resolution (as seen by the users) from “20%” to 80%, reach user satisfaction level of 75% • Higher skills at Helpdesk • Extend time (now 10’) to find a solution at first call • Improved procedures: close open loops with service providers (information), quality assurance of replies, ticket flow (user wants a problem solution), • “Engineer in charge”: responsible to the user for problem resolution, quality assurance, user information (Zephyr, Web content, service status), link between users and service providers • Better tools: content of, and access to, knowledge database (Q&As), automated support actions (quota?)

  4. Helpdesk Changes: Getting There • Reaching the objectives • Information gathering • Shifts with Helpdesk • Industry comparisons • Helpdesk backing up • Analyze findings • Shifts with Helpdesk (Feedback given to Helpdesk): communication, “personal” approaches, training, user expectations, working conditions • Industry comparisons: somewhat difficult Remedy tickets “domain oriented” (eg, mail, Web), industry uses Gartner Group categories (“How to”, “Break/Fix”), data mining done • “Helpdesk backing up”: during 2 weeks Helpdesk backed up with one staff from IT-US: jump in first-call resolution observed • Redesign current model • “Backing up Helpdesk” looks very promising • In-depth test during 4 weeks, running since 6 May

  5. Helpdesk Changes: Summary • Summary • Discrepancy between user expectations/perceptions and contract performance • Contract funding subject to CERN policies • “Backing Up” model looks very promising • Implementation target: “Summer 2002”

  6. Helpdesk Changes: Statistics