Skills-based routing allows contact center to route different types of calls — for example sales, service, and payment processing — to the agents who have the skill necessary for that call. When agents are cross-trained, so that some or all have more than one skill, skills-based routing can increase the amount of time agents spend handling calls, offering significant cost savings and improved service levels without additional staff.Implementing skills-based routing adds new workforce management challenges for contact centers. The process of creating accurate forecasts and developing efficient schedules for agents in contact centers that handle only one call type is well understood; achieving the same goals when the contact center handles different types of calls is much more complex.

In order to realize the full benefits of skills-based routing, it becomes more critical to create accurate agent requirement forecasts, and agent schedules that maximize the potential efficiency of multis killed agents. Poor quality in forecasts or schedules can completely undermine the value of skills-based routing, and even decrease performance.Workforce management systems employ several different approaches to forecasting and scheduling to address the unique complexities of skills-based routing. Many of these approaches have proven inadequate because they fail to account for the complexity in call distribution between cross-trained agents. A true skills-based routing approach must consider the actual logic of the ACD routing rules and efficiencies from multi-skilled agents using an integrated simulator to return accurate forecasts, and efficient schedules.

Forecasting Using Erlang C in a contact center that is not using skills-based call routing, agent requirements can be derived through simple mathematic calculations. Forecasts of call volume and average handling time over the desired time intervals and service level goals can be input into an industry-standard Erlang C formula that calculates the number of agents needed for each time interval. However, using a mathematical formula by itself to calculate agent requirements does not yield accurate or optimal results in skills-based routing environments. Mathematical formulas like Erlang C always result in overstaffing when applied in skills-based routing environments, because they do not account for sophisticated ACD call routing logic and efficiencies from multi-skilled agents. When agents have multiple skills, there is a greater likelihood that an agent with the necessary skill for an incoming call will be available, so fewer agents overall are required to manage the same number of calls at the same service level.

Erlang C assumes each agent handles a single call type on a first-come, first-served basis. This assumption is not valid for skills-based call routing because some, or all, agents will have more than one skill and can handle multiple call types. Call types may also have different priorities, allowing Platinum-level customers to reach an agent before Gold-level customers, so all calls may not be offered to agents on a first-come, first-served basis.Most importantly, in a skills-based routing environment, agent availability depends on other agents’ skills and schedules. Since agents scheduled for one particular call type may also be utilized for other call types, the number of agents needed for one call type depends on which agents are scheduled for every other call type. Further, determining the percentage of time an agent will spend handle a certain call type in a skills-based routing environment depends on dynamic call routing rules such as conditional queuing, changing call priority, queuing to backup skills, time of day, and day of week — and cannot be calculated with simple mathematics formulas.

Creating effective schedules in skills-based call routing environments is a circular problem that can not be solved by mathematics alone: the exact number of agents required can only be determined after schedules are created; and, before schedules can be created, it is necessary to know how many agents are required to be scheduled.In spite of these issues, some workforce management systems still use Erlang C alone to calculate agent requirements for skills-based call routing. Agent requirements for each call type are calculated independently, then an arbitrary efficiency factor is applied to lower the requirements to estimate the greater efficiency provided by multi-skilled agents. A variation on this approach adds the call volume of all call types and calculates the weighted AHT for each interval. But, in this combined workload variation, the results of the Erlang C calculation are based on the assumption that all agents are fully crossed-trained in all skills. Using this approach, the number of agents must therefore be increased by an arbitrary factor to account for the fact that not all agents are fully cross-trained. A combined workload also means that calculations are based on one service level for all call types, which is often not realistic or appropriate.

 

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