Pipkins is The Accurate Workforce Management Solution.

This is the result of the advanced forecasting algorithms we utilize in our software. Our Merlang^® algorithms make older Erlang-C based models obsolete. You need more sophisticated mathematics to account for the increased complexities of modern multi-channel and omni-channel contact centers. Older Erlang-C algorithms are simply not applicable in today’s environment.

Pipkins’ Merlang improves upon traditional Erlang-C algorithms by eliminating the assumptions that queues are infinitely long, callers never abandon the queue, and all calls have to be answered by one group of agents. Merlang equations offer several advanced features that are not available from software packages that use Erlang-C, including the prediction of the number of abandons and busies, and the optimal distribution of agents within skill groups.

The traditional way of expressing a service level as a percent answered within a given time is provided, along with percent calls answered, maximum percent busies, maximum percent abandons, and maximum average speed of answer. Not only are the results far more accurate than what is produced from Erlang-C, you get the right answers the first time without having to resort to costly trial-and-error simulation methods.

Merlang equations offer the following advanced features and capabilities that are not available from software packages that use Erlang-C:

• Correct modeling of queue sizes – allows for the prediction and limiting of the number and percent of busies.
• Modeling caller abandon rates – allows for the prediction and limiting of the number and percent of abandons.
• Calls handled, a complement of busies and abandons, can be used as a service level type.
• Occupancy is calculated, and caps on it may be taken into account when determining agent requirements.
• The traditional way of expressing a service level as a percent answered within a given time is provided, along with percent calls answered, maximum percent busies, maximum percent abandons, and maximum average speed of answer. Results are more accurate than what is produced from the Erlang-C equations due to the modeling of the effect of busies and abandons on the call volume.
• Accounts for indirectly occupied time of agents (bathroom breaks, supervisor queries, etc.).
• Accounts for retries of both busies and abandons.
• Accounts for skill group queue assignments, queue priorities, and overflow.
• Calculates requirements in a multi-skilled environment, avoiding repetitive analytical simulations.
• Predicts the number of abandons and busies, and the optimal distribution of agents within skill groups.
• Results are far more accurate than what is produced from Erlang-C; therefore, you get the right answers the first time without having to resort to costly trial-and-error simulation methods.

Want to know more? Read about our Vantage Point workforce management (WFM) solution for additional information about the advanced forecasting and scheduling made possible by our Merlang algorithms.

You may also be interested in  learning more about Pipkins’ State-of-the-Art Schedule Optimization, based on a Sum of Squares figure of merit analysis.

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