🧮 For a while, I've wanted to share a post about Erlang. Not the programming language, but the Erlang C formula - a statistical tool for call centers and customer service operations.
☎️ Erlang was a Danish engineer/mathematician who analyzed the early XX century telephone networks. He discovered and proved that a special case of the Poisson distribution predicted the behavior of queue-like systems such as random telephone traffic, taxi requests, time between purchases, and even disease incidence by age.
🤔 Why is Erlang C Relevant?
📞 This is applicable to Salesforce Omni-Channel, Service Cloud Voice and Amazon Connect.
The formula determines a probability that a calling customer will have to wait given the number of agents and average traffic intensity. This provides a way to estimate the number of agents required for a given Service Level Agreement (SLA) and forecast the workload.
It seems feasible to extract the number of calls/hour and average handle time by querying the VoiceCall object. Then we would apply the formula so that a call center administrator can:
👉🏽 determine the ideal number of agents for the current workload
👉🏽 gauge where resources might be trimmed without compromising service quality
👉🏽 project the increase in business to the number of calls per hour to determine when to hire new agents to maintain the support level
👉🏽 adjust staffing for peak periods and scenario modeling for unexpected spikes
What other tools or formulas have you used for optimizing call centers or any other applications? 👇🏼💬
