There is an analytically distinct solution that optimizes the mix of skills within a contact center. To reach a specific recommendation these analytical solutions should be derived from empirical data gathered during the course of a small pilot within the center.

However, there are generalities and trade-offs that can be considered at the management level before introducing too much complexity with intermixed skills across the center.

While current technology makes complex routing of skill mixes possible across a center, or even multiple centers, there is still the issue of human limitations. In numerous experiments with multi-function centers the same result has always been obtained: peak throughput results from functional specialization. Throughput, in this case, is calculated across the process

life cycle. There is still the open question of whether peak throughput is equal to optimal throughput; this must be decided case-by-case.

It is a terrible mistake to examine only front line throughput, or theoretical first call resolution, under these circumstances, as the error rate has a dramatic impact on process life cycle versus first call resolution. Simply put, multi-function representatives have a lower accuracy rate than representatives that are functionally specialized. In most cases they also have lower raw throughput. Where the throughput is comparable, the accuracy differential shows an even greater penalty.

This result has been confirmed in everyone from brain surgeons to fighter pilots; there is an enormous efficacy lift from repetition. All other things being equal,

doctors who perform the most heart surgeries also have the lowest adjusted mortality rate. Humans adapt best to functionally specific practice. Despite the calls for cross-training, world class athletes actually train in activities that mimic the characteristics of their main sport; they do not take up bowling to improve their tennis serve.

There is a tendency in a contact center to expect that merging email responses, telephone inquiries, telemarketing opportunities, and inquiry handling will optimize efficiency. Without careful management the reverse is more often the case. The limiting factor here is the plasticity of our neural pathways. As recent research has shown the brain actually adapts itself, throughout our life, in response to specific tasks and our neural pathways re-wire

in response to repetition.

Watch a really good data entry operator perform their job to clearly see this adaptation response. An untrained operator will look at the number, look at the keypad, type the first character of the number, look at the number, look at the keypad, type another character from the number and so forth. A trained operator will look at the number, stuff the entire number into short term memory, begin to type the number into the keypad, then look back at the next page to read the next number-while completing the typing of the first number without checking back. A trained operator splits their neural pathways to perform two tasks at once, without confusing either one, much

like a professional drummer beating out a different rhythm with each hand. The speed and accuracy difference between the trained and the untrained operator is staggering: a few thousand keystrokes and hour versus 10 or 12 thousand an hour.

Given this understanding there are three trade-off decisions on the other side of the equation that could push the center toward a multi-functional organization.

First, some tasks are not sufficiently different to degrade performance. While very few people can successfully handle both telephone inquiries and telemarketing responses, most people can handle a multitude of products within the framework of a telemarketing response. The core competencies required in each skill need to be mapped to determine the degree of overlap. Email response

skills are almost entirely different from telephone inquiries, but email skills might translate better to case management. Current technology is also lessening the distances between various skills by providing scripted workflows, expert assistants, and extensive databases with detailed customer information that reduces the impact of the representatives’ memory capacities.

Second, larger queue sizes provide more efficient work distribution. Small queues associated with extreme functional specialization waste resources because these small groups cannot be scheduled efficiently to maintain appropriate workloads. This is the principle economic trade-off associated with skill mix analyses. Throughput and accuracy rates have to be compared to staffing efficiency to formulate a reasonable recommendation.

Third, there are development considerations that might outweigh the raw productivity impacts for a

select group. Representatives being developed for supervisory jobs may benefit from exposure to a wider range of center jobs. In addition, there is a definitive quality benefit from exposing representatives to tasks throughout the value-chain that are essentially customers of their outputs. Cross-functional exposure to various steps in the process can bring numerous suggestions for breakthrough improvements across the entire process. This cross-functional awareness also provides a critical backstop in the event of unplanned volume surges. It is impossible to economically staff for these peak occurrences and a cross-trained staff can eliminate customer backlogs where there is no other alternative.

At the end of the day these decisions require detailed analytical study to make the appropriate trade-off decisions with multi-functional

centers and functional specialization. This broad overview of some central issues may help to frame the analysis.

Steven Grant is a former customer service executive from American Express with over 25 years devoted in Fortune 500 companies analyzing, improving and delivering on enhanced customer experiences. Share your experiences and suggestions on improving the customer experience at http://www.customerresearchcenter.com or email Mr. Grant at [mailto:scgrant@customerresearchcenter.com]scgrant@customerresearchcenter.com