Capacity Crunch at SupportWorks
SupportWorks is a managed service provider running a 24/7 service desk for 60 clients. It employs 18 agents; utilisation is 87%, voluntary attrition is 20%, and overtime equals 12% of scheduled hours. The desk handles 1,200 tickets a month with an average handle time of 14 minutes, but first-contact resolution is 52%. Demand is forecast to grow 25% in six months. Only two engineers have automation skills, and the training budget is frozen. Cloud hosting costs have risen 30% and the main supplier has tightened its service credits. Client satisfaction is falling, and two clients have invoked contractual service review meetings. The operations director wants a resource plan that covers people, skills, technology and suppliers without simply hiring 25% more agents.
1. Prepare a resource plan for the next six months. Quantify the capacity gap and propose a mix of demand management, workforce, automation and supplier actions.
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Quantify the gap. Current demand is 1,200 tickets a month at 14 minutes, about 280 agent-hours of handle time, plus wrap-up, breaks, training and 24/7 coverage. At 18 agents and 87% utilisation, effective capacity is tight. A 25% volume increase implies roughly 350 hours of handle time unless average handle time or demand mix changes.
Do not simply add 25% headcount. Model coverage by hour and day, because 24/7 staffing is driven by shift minima, not monthly averages. Actions include demand management through self-service, password reset automation, service request automation and deflection of low-value contacts; workforce actions such as cross-skilling, adjusted shift patterns and part-time or follow-the-sun arrangements where contracts allow; automation for triage, suggested responses and knowledge search; and supplier actions such as renegotiating the cloud contract and using co-sourced overflow for non-critical tickets.
Quantify each option in hours saved or coverage gained. Keep a contingency for attrition: 20% attrition on 18 agents means about 3.6 full-time replacements a year, which consumes training capacity. Show gap closure month by month.
2. How would you apply workforce and talent management, capacity and performance management, and supplier management to this situation? Identify trade-offs.
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Workforce and talent management: define required competences for the next six months, especially automation, cloud cost analysis and client relationship skills. Use a skills matrix and targeted training despite the freeze, through vendor-funded training, peer coaching and automation apprenticeships.
Capacity and performance management: forecast demand by client and time band, and set utilisation targets that leave slack for improvement and unplanned work. An 87% utilisation rate is too high for a support desk with 20% attrition. Supplier management: review the cloud contract, service credits and exit clauses. If the supplier has tightened credits, assess risk and consider reserved capacity or a multi-supplier approach.
Trade-offs are real. Raising utilisation improves short-term cost but increases attrition and errors. Hiring adds capacity but also training load and cost. Automation reduces handle time but requires upfront engineering. Choose a balanced portfolio: automate the top five request types, introduce tiered service offerings to shift low-value demand, and use supplier overflow only for non-critical work. Measure forecast accuracy, utilisation, attrition, overtime, first-contact resolution, cost per ticket and client satisfaction.
3. What risks would you flag to the operations director, and which measures would show whether the plan is working?
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Flag service failure during peaks if attrition or demand exceeds plan; automation failures affecting clients; supplier lock-in or penalty exposure; skills concentration in two engineers; and contractual breaches with clients already invoking service reviews. Mitigate with a capacity buffer, documented runbooks, cross-training, a supplier contingency plan, and phased automation with rollback. Also flag the risk of cutting training to protect margin, because it raises attrition and long-term cost.
Use leading and lagging measures: demand versus capacity by week, utilisation band, overtime percentage, attrition, first-contact resolution, average speed of answer, backlog age, client satisfaction, automation adoption, cost per ticket and supplier credit events. Review monthly with the operations director and quarterly with clients.
If leading indicators such as backlog, overtime and attrition worsen before service levels do, trigger the contingency earlier. The plan should be a living forecast, not a one-off headcount request.