Spreadsheet Planning

How to Apply Erlang C in Call Center Planning with Excel

Michael Lambarena 4 min read Download as PDF
How to Apply Erlang C in Call Center Planning with Excel

All it takes is one glance at the Erlang C formula to wonder if there’s a simpler way to send humans to Mars...I mean, to calculate staffing requirements. 

mars-astronaut-erlangcErlang C, the mathematical formula behind the call center queuing model of the same name, is the tried and true method used to calculate call center staffing requirements for inbound calls. 

But how exactly do you use it, and what are the pros and cons? Let’s find out.

Erlang calculators are your friend

Based on a given number of incoming calls, an average handling time and a desired service level, planners around the world use Erlang C to calculate the number of staff needed per interval.

The good news is that you don’t need to be both a workforce planner and a math professor to use Erlang C with success. These days it’s common practice to simply use an Erlang calculator!

Interestingly, among workforce planners there isn’t a standard definition of what an ‘Erlang calculator’ actually is or what it should be, and this can be slightly confusing at first.

Yet the general idea behind any such ‘Erlang calculator’ is essentially a tool that provides a shortcut to an accurate approximation of how many agents your call center needs to meet its service level target.

Understand the Pros and Cons of Erlang C in Excel

An important caveat to know about the Erlang C formula is that it’s built upon a simplified picture of a call center traffic model. This means it assumes no abandonment in the queue and that calls will arrive according to Poisson distribution.

With that being said, quite a few Erlang calculator tools can be found online—many of them free to use. These range from mobile apps serving as handy shortcuts for common calculations, all the way to complete Excel spreadsheet solutions at the other end of the spectrum.

Free Calculator
Erlang calculator for Contact Centers

Calculating required staffing is a vital part of the workforce management (WFM) process.

With a simple user interface, the free injixo Erlang calculator enables you to do the basic calculations on the fly.

How to use Erlang C in Excel

For call centers that haven’t made the switch to workforce management software yet, Excel spreadsheets are a common alternative.

>> Still using Excel? Check out this blog post: The Best Way to Use Excel for Workforce Planning.

Typically, this means finding a spreadsheet template with built-in macros, add-ins or automatic input sequences. There are various templates available online and many are free to download, too.

One of the reasons why Excel-based ‘Erlang calculators’ are so popular is because they’re cheap and simple to set up, and therefore quicker to integrate into workforce planning processes.

Keep in mind, however, that relying on Excel-based Erlang calculators often means living with risky drawbacks.
Excel spreadsheets fall short when it comes to integrating critical variables like shrinkage and occupancy rate. They don’t take care of automatically importing contact history.  What’s more, manual maintenance, limited calculation options and outdated user interfaces quickly turn into the pains that cause workforce planners to recognize that Excel spreadsheets are merely a short-term solution.

Get started through trial and error

In lieu of WFM software like injixo, we recommend trying various calculators and tools to find out what works best with your existing workforce management setup.

Start by exploring the links in this post, and feel free to browse other posts on our blog for more insights on how you can harness workforce management to go from planning to performance.

1) Gans, N., G. Koole and A. Mandelbaum. 2003. Telephone call centers: Tutorial, review, and research prospects. Manufacturing & Service Operations Management 5: 79-141.
2) Robbins, T., Medeiros, D., Harrison, T. 2010. Does the Erlang C model fit in real call centers? Conference: Proceedings of the 2010 Winter Simulation Conference, Baltimore, Maryland, USA, 5-8.
3) https://en.wikipedia.org/wiki/Poisson_distribution

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