Scheduling Optimization

Scheduling-Optimization

One technician calls in sick. Another technician runs late on a job. Yet another discovers they must pick up a spare from the depot because an additional problem was identified. One of your technicians is stuck in traffic and is going to miss a planned call. At the same time, two high priority calls come in that require service within the next four hours or will result in penalties. How should the schedule be adjusted to compensate for all of these conditions?


Your Most Proactive, High-Performance Approach to Dealing with Dynamic Schedules

This is just an average day for many dispatchers, and they usually have some interesting ways to solve the problem. Not by following a simple set of rules, typically, but the ability to make trade-offs between different options. The problem is that as the options grow more complex and there are more factors to consider, a dispatcher can only handle so much. Subdividing technicians and dispatchers to territories can help, but that simplification does not allow for optimization across the business. How can the trade-offs between schedule attainment and productivity be managed? Service companies have to deal with the realities of not having enough resources, having too much work to do, coping with schedules that are hard to predict, and trying to meet continuously increasing customer expectations for service.

Many service businesses have a much more complex environment than manual processes can effectively manage. As the number of different factors that must be considered increases, the number of possible solutions increases exponentially. As the situation becomes less static, the ability to keep track of—let alone optimize—dispatch decisions becomes less feasible. And as the number of tradeoffs that must be made increases, the ability for a human to address this manually or with a simple tool like a planning board or spreadsheet becomes inefficient and cannot provide optimal results. Improved management of service processes can help increase customer satisfaction and profitability. In addition, applying scheduling technology and proven optimization practices is providing many companies a solution to the complex problem. Scheduling optimization technology, formerly reserved for large companies or mission-critical issues, is now coming into the reach of smaller companies.

Service Lifecycle Management (SLM) solutions are adopting this proven technology and infusing it with service management capabilities. Given increased customer demand, tighter Service Level Agreements (SLA), more complex customer-driven contract options, reduced profit margins and more complex equipment that requires the need to deploy a more diverse range of technician skills—the time is right to apply field service scheduling software to solve the growing service scheduling and dispatching challenge as part of an overall Service Lifecycle Management (SLM) strategy.

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