Erlang C has been a WFM firm favorite for decades. Now there is an alternative. Rebecca Philp at Telelopti explains the differences and five advantages of Erlang A.
For many years, contact centers have used the Erlang staffing calculator to forecast how many agents they require to meet agreed service levels. Calculations are based on two mathematical formulae: Erlang C and Erlang A. Paradoxically, Erlang C came first, invented by Danish mathematician A K Erlang in 1917 followed by Erlang A which was devised by Swedish statistician Conny Palm in 1946.
Erlang C is predominantly used for queuing calculations based on call volumes and the number of agents necessary to achieve certain service levels. However, Erlang C assumes that people have infinite patience and while waiting times might appear to decrease, the queues grow infinitely. Erlang A, on the other hand, better reflects the psychological realities of customer patience. It recognizes that every customer has a finite patience span before they become frustrated and simply hang-up. By estimating average patience time or average time to abandon (ATA) to calculate average waiting probability, contact centers have a better chance of creating accurate forecasts and schedules that are relevant in today’s multi-channel world.
Of course, all contact centers really want is better forecasting accuracy – at least that’s what Teleopti’s customers tell us and whether they apply Erlang C or Erlang A principles, is a matter of choice and largely depends on the individual merits of their own contact center.
For the purposes of this exercise we throw the spotlight on the advantages of Erlang A and how they relate to automated Workforce Management (WFM) solutions.
Consider the latest WFM solutions as vast vessels of knowledge that capture those all-important average abandon rates now and in the past. Understanding historical data to predict the future helps contact center leaders build proactive rather than reactive schedules.
Most contact centers know the total number of calls they receive, the number answered and the number abandoned. Simply key this information into a WFM system using Erlang A to do all the work of calculating average patience times to give accurate schedules for staffing levels. The changes might only be small but can make all the difference between irate customers, abandoned contacts and a smooth customer experience.
By taking average patience times into account and then using Erlang A to calculate the number of employees required to meet demand, and maintain service levels, typically fewer resources are needed. This can reduce the temptation to overstaff and therefore reduce costs too.
With better forecasting, more efficient schedules and reduced costs, boost productivity by maximizing idle time. Use WFM technology to schedule offline activities such as administration, training and weekly huddles. Allowing employees to give their full attention to customers during busy periods.
With rising customer expectations of what good service means, abandonment rates are an extremely important indication of how well service levels are achieved. The problem is that most contact centers didn’t have the technology to view them easily or analyze them properly – until now. Fortunately, modern WFM systems promote intelligent resourcing. By tapping into real-time data, contact center managers have the power to predict how many agents they need regardless of channel with a little help from either Erlang C or Erlang A.
At Teleopti, the laws of mathematics are essential to continual improvement and form an intrinsic part of our product development program. We apply both Erlang A and Erlang C principles to enhance and develop a comprehensive range of new technologies that drive efficiencies and performance in today’s contact centers. You simply choose the option that suits your set up best to give you the most benefit.
Speaking of driving efficiency - try out our Teleopti WFM Calculator and find out how you can benefit from investing in a WFM solution
Publish Date: March 25, 2019 5:00 AM
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