As digital channels have multiplied, so too has the demand for multi-skilled contact center agents―those who can handle different tasks or have expertise in a product or service but who can also handle general customer inquiries. During periods of peak volume, these employees can handle a range of calls, emails, and messages, providing flexibility and capacity when it’s needed most, but they introduce a not-insignificant challenge to efficiently meeting service-level objectives in multi-channel environments.
The old adage, “Hope for the best but prepare for the worst,” may be sage advice, but exactly how do contact centers juggling multiple channels ensure they’re properly staffed for an unexpected spike in demand—without overstaffing?
Too many contact centers today rely on legacy workforce management (WFM) solutions that fail to account for multi-skilled employees in the forecasting process. Some WFM solutions simplify the challenge with a first-in, first-out approach or split an agent’s time 50-50 between two tasks. Still others employ a most-to-least-skilled hierarchy, which can result in a loss of productive time and cause contact centers to rely on simply hoping that they will have enough capacity when demand spikes.
“Hope” is a poor planning method because it disregards the specific conditions that warrant sharing an employee between multiple work streams. Some WFM solutions attempt to eliminate the “hope method” by relying on historical data as a predictor of skills usage, but this method frequently falls short because it is rare that the schedules, work volume, work time, and queuing conditions of the past will be replicated in the future, especially as contact volume rises with digital channels.
Moving Beyond Hope as a Strategy
A growing number of forward-thinking organizations are leveraging modern WFM solutions that harness the power of artificial intelligence (AI) and machine learning to move beyond hope to an approach that enables them to anticipate business demands and optimize the workforce.
Among those modern solutions is NICE WFM, which is consistently recognized by industry experts and analysts as a leader. NICE WFM automatically evaluate dozens of forecasting algorithms to determine the model with the greatest accuracy. It allows the contact center to define for itself how it accounts for simultaneous contact handling in forecasting.
And it’s the only WFM solution that uses the simulator feature for the entire WFM process, from forecasting and scheduling to intraday management. The simulator can be used for Automated Call Distribution (ACD) routing; this allows the planning team to test distinct types of call routing: precision routing, attribute routing, percentage routing and skills-based routing.
NICE WFM also harnesses AI to move beyond challenges with skills-based routing. Beyond increasing staffing efficiency, skills-based routing allows centers to prioritize preferred channels and quickly recognize when a manager must be called upon to handle a tough situation. This type of routing is nearly impossible for traditional WFM solutions that rely on outdated mathematical formulas and historical data to predict skills usage, because such formulas tend not to work in the current multi-channel, multi-skilled employee environment.
NICE WFM’s skills-use assessment is based on a predictive AI analysis embedded in the simulator―no assumptions or user input needed. It accounts for all eventualities of how employees of various skill profiles might be used in any given interval on any given day. The model is then able to predict when, and to what degree, a particular skill will be needed, unlocking the mystery of contact center staffing and eliminating the need for hope.
If contact centers are to thrive in an ever-evolving digital world, they must be able to manage all their channels properly all of the time, and that starts with staffing. Ready to abandon all hope (as a strategy)? Learn more about how NICE WFM can give your business the tools it needs to understand future workforce needs in a multi-skilled, omnichannel world.