Airline Resourcing For A Superior Customer Check-in Experience
A new customer-queuing functionality enables airlines to forecast the right check-in resources to provide an exceptional customer experience. The new optimizer has been tested with actual airline data, and it has determined potential savings opportunities of up to 5 percent for queuing scenarios in medium- to large-size stations.
For air travelers, the mere process of getting to an airport can be a challenge. Whether it’s traffic, crowded public transit, finding parking, navigating airport shuttles or ensuring the entire family arrives together and on-time, travelers face a barrage of unexpected challenges that can leave them utterly stressed before arriving at the airport for check-in.
With all of the hurdles passengers must clear before they walk in the front door of an airport, airlines know how important it is to ensure travelers have a quality experience during the initial point of contact. As the first impression with an airline’s staff, the check-in experience can set the stage for the rest of the traveler’s journey
There are numerous factors that determine overall quality of the check-in experience, but how the check-in facility is resourced by an airline has a major impact on passenger satisfaction. Resourcing has a direct link to wait times, but airlines must balance the cost of incremental resources against the service experience they want for their customers.
Adding to the complexity, the intervals at which passengers arrive at the airport is random, with an array of market characteristics, airport infrastructure conditions and individual passenger behavior continually influencing arrival patterns. Check-in resourcing is undoubtedly one of the most complex staffing functions to plan for at an airport.
5 Percent Cost Savings
Airlines can achieve potential savings of up to 5 percent using a new customer-queuing functionality to forecast the right check-in resources while providing an exceptional customer experience.
Comprehensive Queue Planning
For well over a decade, Sabre AirCentre® Staff Planner has provided global airlines with queue-resource forecasting functionality, encompassing operational variables such as passenger arrival rates, service times and quality targets. However, check-in environments at airlines around the world have changed, including:
- Focus on performance metrics and quality standards as a competitive differentiator,
- Global adoption of self-service and mobile check-in technology,
- Increase in the frequency of flight schedule variations,
- Widespread availability of detailed check-in data, which drives resource forecasting.
To address these changing needs, the airport management operations research team for Sabre Airline Solutions® has re-invented check-in resource optimization, with a focus on service quality and cost management for a dynamic, self-service check-in environment.
A Unique Check-in Experience
One of the key objectives in the new Staff Planner queuing optimizer is enhanced sensitivity to quality parameters. Within the new optimizer, airlines will have greater flexibility to tailor check-in resourcing based on the level of service desired in the operation.
For instance, premium-cabin check-in queues can have higher wait-time quality parameters, while main-cabin queues have lower quality standards. Quality parameters also allow airlines with varying operating models to easily construct queue-resource forecasts based on the overall business strategy. As an example, a low-cost carrier may set a higher wait-time threshold as opposed to a full-service airline.
Maximum Agent Requirements
When examining the passenger arrival rate and corresponding agent service levels, there are four major passenger arrival peaks around 8:00, 16:00, 18:00 and 21:00. Because of the “peak cut” around 16:00, the head counts (maximum agent requirements) can be set to nine instead of 10, and the passenger surge around 21:00 is significantly relieved by letting passengers wait in queue to be serviced afterward when there are fewer arrivals, while the service-quality target is maintained.
Check-in Resourcing Consistency
The inherent nature of many flight schedules results in “peaks and valleys” of passenger demand throughout a typical day. Station managers are constantly challenged to maintain budgetary constraints and maximize staff productivity, all while meeting service-quality standards. With a “peak-and-valley” flight schedule, it can be difficult to achieve all of these objectives.
The new queuing optimizer keeps resourcing levels as consistent as possible throughout time intervals in the operational day, while meeting service-quality targets. As compared to previous optimization methodologies, increasing resourcing levels ahead of periods of higher passenger demand enables airlines to address the passenger demand as it builds, rather than a reactive approach that may increase resourcing levels in the middle of a peak.
Forecasting Self-Service Resources
For most airlines, mobile and self-service check-in is now dominant across global airports. To improve the precision of forecasting resource requirements, the queuing optimizer contains multiple self-service models, encompassing a dedicated service to optimize self-service machine requirements and optimization to forecast staffing requirements for self-service functions. All models include the ability to define quality parameters, as with the optimization methodology for full-service check-in queues.
Agent requirements are forecasted based on a segment of the overall population of passengers using self-service check-in, including kiosks, Web and mobile check-in. If a subsequent agent service is required, such as dropping a checked bag or resolving a ticketing issue, the self-service component of the queuing optimizer can forecast agent requirements based on a modified passenger arrival pattern, passenger volume data and quality standards.
Ample Check-in Resources
Myriad factors determine overall quality of the check-in experience. However, how an airline staffs the check-in facility has a substantial effect on passenger satisfaction. While resourcing is directly linked to wait times, airlines must balance the cost of incremental resources against the service experience to achieve a win-win situation.
The queuing optimizer is a multi-stage algorithm that utilizes both optimization and simulation techniques. Multiple runs of the optimization model with randomly generated passengers produce agent demands for different passenger arrival patterns, which are then consolidated to a single output. Afterward, the optimizer uses a simulation model to identify hot spots of tension or inefficiency in the consolidated solution, and adjusts it accordingly to ensure compliance with quality standards. This comprehensive analysis produces a solution with increased precision to ensure wait-time goals are being met in the operation.
In addition to check-in, Staff Planner’s design will allow airlines, ground handlers or governmental agencies to use the queuing optimizer to forecast other queue-based operational situations, such as baggage service, security, immigration or customs.
The new queuing functionality provides real value for airlines by forecasting the right check-in resources for the passenger experience they want to deliver to customers, while achieving optimized operational cost management for this important function at the start of each passenger’s journey.