November 2001
 

BY BRIAN SPRAETZ, IEX CORP.

A long time ago, Darwin proposed that nature had an innate process for determining the best choice between options. Natural selection, in his view, worked to ensure that species best equipped to survive would flourish, while those less capable of dealing with the harsh realities of life would disappear. Life moved onward and upward in lockstep with the Theory of Evolution, innovating and improving in order to survive in an increasingly competitive environment.

There are, however, some notable exceptions to this generalization. Sharks, alligators and sea turtles, among other species, remain seemingly immune to change. Perhaps change is not an absolute requirement for survival. Maybe simply maintaining the status quo is sufficient to get by' but for how long? In the area of contact center scheduling, a strikingly similar parallel exists. Just like sharks, many organizations cling to an agent scheduling method that is quagmired in evolutionary muck'a method in which agents bid for work assignments through a process called schedule bidding. Is this status quo approach sufficient to ensure survival in today's business environment? Before rushing to a judgment based on the ever-popular 'newer is better' theory, it's worth taking a closer look at the pros and cons of schedule bidding and a popular alternative approach, preference scheduling.

The Evolution Of Scheduling Systems
Scheduling of employees was not a major issue until the turn of the 20th century, at which time the nation's telephone system began to grow rapidly. Before automated switching equipment was invented, telephone callers had to be connected manually by operators. Telephone companies began to experience problems with staffing and scheduling as hundreds, even thousands, of operators were needed to handle the increasing call volumes. A variety of approaches were conceived to address this scheduling problem, most of which relied on hands-on experience, seat-of-the-pants judgments and more than a touch of luck. Eventually, Mr. A. K. Erlang and his magic formulas appeared in the early 1920s.

Still in use today, Erlang's equations for determining the number of agents required to meet a desired service level, with a forecasted calling volume, provided mathematical rigor to what had largely been a guesswork approach to the scheduling problem. With a scientific method for calculating the number of workers needed during each specific time interval of the day, the focus switched from trying to figure out how many people were needed to finding an efficient way to schedule and allocate working assignments. Enter schedule bidding.

Schedule Bidding
The process where employees select, or bid, on the working shifts they prefer from a master list of all possible schedules was seen as a fair and equitable method of allocating assignments, at least to the employees with the most seniority. Schedule bidding is basically a two-step process in which a set of schedules is created to cover the forecasted workload requirements and then those schedules are presented to employees for bidding in some sort of pecking order such as seniority.

Giving employees the ability to choose among the alternatives provided workers with a feeling of control over their assignments. Even when given only a 'lesser-of-evils' decision, the fact that they were personally making the decision, rather than having it dictated to them, helped foster an environment conducive to improved job satisfaction. Unfortunately, Erlang's equations and the schedule bidding process did nothing to address the issue of what schedules were best for the organization in terms of meeting service goals and optimizing resources. Enter modern workforce management systems.

With the advent of mainframe computer technology in the 1960s, larger organizations began to attack the scheduling optimization problem. The development of in-house solutions, coupled with the PC computing revolution of the 1980s, eventually led to the introduction of packaged workforce management solutions in the early 1990s, which continued to evolve into the robust applications available today. These marvels of applied technology, capable of considering thousands of possible scheduling combinations in seconds, optimize the matching of scheduled resources to forecasted volumes, lowering staffing costs without compromising service levels.

Preference Scheduling
What appeared to be the sole remaining advantage of schedule bidding over the emerging solutions, allowing employees to exert a degree of control over their working assignments, was overcome through the addition of agent preferences to the automated scheduling process. By predefining an agent's personal preferences about schedule tradeoffs, total automation of the schedule generation and allocation process was made possible in a way that addressed the individual desires of employees while still conforming to the operating goals of the enterprise. Schedule bidding as an allocation method was surely destined to follow in the footsteps of the dinosaurs.

Sharks predate dinosaurs by thousands of years, and more important, outlasted them by thousands more. Like the shark, the decades-old method of scheduling bidding still flourishes in today's contact center. Although especially prevalent in a few vertical industries, such as airlines and car rental companies, its popularity spans a wide spectrum of service industries. There must be some underlying rationale for this successful longevity.

First, there are some downsides to schedule bidding as a work allocation process. In a bidding environment, schedules are typically fixed for much longer periods of time -- months or even years in some cases, as opposed to the agent preferences approach were they are often prepared only a week or two in advance. These longer time frames do have a practical basis for their existence. Schedule bidding's two-stage process, often paper intensive and requiring a high level of manual involvement, is not something an organization would want to repeat often. Longer time horizons, however, increase the possibility that staffing changes caused by employee turnover, or changes in the volume of contacts coming into a center, result in an increasing number of coverage problems as time progresses. The heavy reliance on manual involvement in the bidding process also leads to higher labor costs and a greater potential for human error than a fully automated approach.

Resistance To Change
Given the seeming superiority of using automated preference-based scheduling in a contact center, why does schedule bidding continue to remain in use? One possible explanation is found in the theory of organizational inertia, or the resistance of an organization to change. Even in the face of convincing and viable reasons to change, enterprises often elect not to do so. This resistance to change can result from a highly ingrained corporate culture or by being constrained in the ability to change due to labor management issues. Whatever the underlying reasons, many organizations find change a difficult concept to embrace.

Employees' active involvement in choosing work assignments in the schedule bidding process presents another possible reason for resisting change. Active involvement fosters a greater perception of control. Although arguably a false perception compared to the use of agent preferences, it is still a real concern when it comes to the impact on employee morale. Letting employees bid on schedules, taking their fate into their own hands, is often a more attractive alternative than spending supervisory time compiling and presenting proof that a computer really did provide the most desirable schedule for a particular agent.

A New Era For Schedule Bidding
Today's version of the shark does differ in some ways from its pre-dinosaur-era ancestors. Change has occurred, even if it is not readily apparent. Likewise, the computational power and sophistication of modern workforce management solutions has brought about underlying improvements in the schedule bidding process. These improvements provide organizations using schedule bidding opportunities to achieve additional benefits without switching their scheduling process.

Improved forecasting accuracy, combined with the ability to quickly evaluate multiple scheduling alternatives, generates schedule sets for bidding that better optimize resource use and meet service goals. Closer matching of schedules to forecasted volumes reduces the amount of time supervisors must spend manually manipulating and adjusting schedules. This time can be better spent evaluating the cost impact to the organization of alternative scheduling policies through 'what-if' analysis, or looking for other areas of potential improvement.

Modern schedule bidding systems replace the use of paper-based forms and reports with electronic versions, speeding up the bidding process, reducing the potential for human error and making it all more convenient for supervisors as well as agents. Once bidding is closed, agents' selections can be evaluated against bidding rules and schedules automatically assigned without the need for supervisory involvement. Schedules that have not received any bids can be easily identified, enabling prompt action to resolve potential coverage issues. Agents who have not input bids within the allowed time window can be similarly identified, allowing proactive investigation into the reasons.

The effects of agent turnover and changes in contact volumes occurring over those longer scheduling time frames typically associated with schedule bidding can be alleviated by alerting supervisors to potential problems ahead of time. This early warning provides time to seek alternatives and resolve these issues before they become critical.

Mixing The Two Approaches
The debate over which scheduling approach is best has been going on since the advent of the preference-based models. This debate is likely to continue for a long time, quite possibly never producing a clear winner. Perhaps the greater benefit resides in a combination of the two approaches, where the strengths of each are leveraged.

For operations using schedule bidding, the effects of agent turnover and changes in contact volumes between bid cycles could be addressed quite effectively by using preference scheduling to fill in the gaps with newly hired agents, part-time agents or contract labor. Schedules that did not receive bids could also be automatically assigned by preference scheduling, using either the same labor pool or agents who were eligible for bidding but did not place bids.

Conversely, in a preference-based scheduling environment, bidding could provide an effective means for fair and impartial allocation of overtime work assignments. For organizations supplementing in-house staff with contract labor, long-term, fixed-schedule contracts could be allocated through the bidding process while using preference scheduling to maximize the use of the in-house agents. In a similar manner, long-term fixed schedules could be offered to a center's high performing agents as a reward component of a strategic employee retention program.

Contact center operations spanning multiple sites may be forced to deal with differences in work provisions or labor management issues between the sites. The requirements for some sites may be best addressed through the use of schedule bidding while others may be more suited to a preference scheduling approach. In cases such as this, the ability to combine approaches within a single workforce management system enables centralized planning, reporting and analysis across the enterprise as opposed to managing these sites individually.

Like the shark, schedule bidding has survived the tests of time with relatively little change. Fine tuning the bidding process continues through additional automation and improved analysis and reporting features. Workforce management systems supporting both types of scheduling approaches no longer force contact center organizations into making a decision of using one method exclusively over the other. Further, a hybrid approach combining the best of both processes, and offering potential benefits greater than either approach used alone, may be the ultimate evolutionary result.

Brian Spraetz is the director of marketing for IEX Corporation. He has over 15 years of experience in bringing high-technology solutions to the customer service and contact center markets. IEX is a provider of workforce management and intelligent call routing solutions.

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