Whether your contact center is undergoing an upgrade or being built from scratch, the question of efficiency and effectiveness is always very sensitive.
Traditionally, contact center simulation tools have focused on improving call center efficiency (i.e., finding new ways to reduce costs). However, not much attention in simulation models has been given to the revenue side of the equation.
We measure efficiency by taking the total cost of the contact center operation and dividing it by the number of FTEs. Because personnel makes up approximately two-thirds of a contact center cost, it is easy to see why contact centers tend to focus on efficiency. With fewer people doing the same amount of work, operating costs are much lower. However, by focusing on efficiency and not on effectiveness with customer, it can actually end up costing the contact center more.
Being effective means delighting the customer into a continuous state of loyalty and satisfaction and a willingness to recommend the company’s services and products to others.
A monetary value can be placed on customer effectiveness and so the simulation model must be in a position to calculate the value the call center has to the business. By summarizing all of the calls over a specific period of time (1/2 hour, hour, day etc.) the model can produce performance reports for that period.
In summary, the typical contact center simulation tools measure the internal performance of the call center based on the rules and parameters established in the model. This information, by itself, is not sufficient to measure the performance of the call center. Adding external customer satisfaction measures to the model will help in determination if the service level generated from the internal metrics is meeting the customer’s expectations.
Data Synergy’s approach to evaluating the contact center using simulation is based on incorporating customer satisfaction measures into the simulation model as a four-step process.
The first step develops the relationship between the customer’s feedback and the internal metrics of the call center. It provides a gauge of where we are today. This is followed by calculating the costs and benefits generated by the customer contact to determine the contact center’s ROI. Once performance measures, revenues, and costs are added to the model, sensitivity analysis can determine which metrics are the most sensitive to change. Finally, potential improvement alternatives are tested using a “what-if” approach. The four steps are:
Aligning caller satisfaction with internal performance measures
Calculating contact center ROI
Performing customer sensitivity analysis
Optimizing contact-center designs