Many contact center supervisors consider the idea of a scheduleless contact center as blasphemous. Assuming agents will just work is along the lines of letting the inmates run the asylum.
But a quick look at Uber, the ride-hailing company, tells us that we should perhaps view the age-old tradition of scheduling as optional rather than core. Uber manages to maintain an average pickup time of less than five minutes in 412 cities across 55 countries, including most U.S. cities with populations of 25,000 or higher -- and it does so without any schedules.
Bill Gurley, general partner at Benchmark Capital, provides some details into Uber's lack of scheduling in a recent post. I couldn't help but think that many of these benefits apply to contact centers as well.
Uber drivers, or "driver-partners," unilaterally decide when and where they want to work. Uber accomplishes this fascinating achievement with the assistance of semi-automated and algorithmic management systems. And that's what brings me to the contact center.
What Makes Scheduling So Complex?
Let's look at the scheduling conundrum that many supervisors need to manage. Scheduling is so complex because of the number of variables that need to be optimized. It's so complex that an entire industry is associated with contact center scheduling, and scheduling is often a core component of workforce management software.
First, are the hours of operation, which don't typically align with normal 40-hour-per-week shifts. There's the anticipated load, or call volume, which has multiple peak periods in a day and may or may not be similar to the previous week's load. There are quality-of-service metrics, such as average speed to answer. Schedules need to address different skills as well as agent preferences and seniority -- yet be responsive to personal issues such as vacations or medical leave. These are just some of the variables. The list goes on, as do the granular details, such as the need to schedule lunch breaks.
However, managing physical transportation on a global basis should be more complex than routing calls. Uber, for example, has to deal with actual physical locations. A spike in demand in one region cannot overflow to a different physical region. Also, service time per ride varies widely and unpredictably.
On the other hand, Uber and contact centers share quite a bit in common. Both heavily monitor their operators while working. While Uber can see things like routes, speed, and instant feedback performance, contact centers supervisors have even more "visibility." Supervisors can see things like outcomes and, thanks to newer speech analytics, can even monitor sentiment.
Potential Benefit: Exponentially Larger Workforce
Once we get our heads around a scheduleless possibility, we can see a lot of potential benefit to the approach. Uber tapped into a huge neglected and willing workforce. A lot of Uber drivers are people who are unavailable for or uninterested in full-time employment.
Two common examples are students who can only work between classes or stay-at-home moms who may only be available for a few hours per day during school hours. It's also a great option for retired people who still want (or need) to work. A few hours may seem trivial, but peak demand times vary across time zones.
It's important to note that Uber has attracted drivers generally across cities, towns, and countries. It's not as if all of these people simply had no other alternative -- they voluntarily chose Uber, and may choose other ad-hoc employers as they become available.
A huge benefit of the modern contact center is that agents can work from anywhere. For employers, speech and noise analytics can quickly identify unacceptable situations such as barking, slurred speech, or even anger. Few, if any, jobs have so many tools for monitoring of remote personnel.
Continue to next page: Meeting new requirements and making scheduleless work