| Demand-driven Workforce Scheduler (DdWS) Reduces Labor Costs and Improves Customer Service Levels |
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Introduction
Before the introduction of Demand-driven Workforce Scheduler (DdWS), managers of a major car rental company generated work schedules for their staff using a heuristic approach based on each manager’s experience as well as data from previous transactions and upcoming customer reservations. Their seat-of-the-pants approach was sometimes on target but was very time consuming and lacked consistency. Among other responsibilities, this would keep him or her in the back office, away from the front counter solving immediately pressing customer-related issues. This company sought after a system to improve their scheduling methods to reduce labor costs and improve customer service levels across their facilities in North America. The selected simulation-based scheduling software solution, named DdWS, developed by PMC, fulfilled this requirement by integrating lean methods, simulation, and scheduling algorithms in a software environment.
Overview of DdWS
DdWS is a demand-driven scheduling software designed to generate a schedule based on the simulation of the real system while meeting certain performance measures. Workgroups are automatically allocated based on a forecasted weekly volume of transactions and past business demand patterns (last week, last year same week, or any week). The number of resources deployed within a week follows daily and hourly fluctuations in business demand. The software uses custom-designed scheduling rules and takes into account expected customer service levels derived from management. As customer service levels change over time (e.g., maximum waiting time to see a Rental Sales Agent, maximum waiting time for a Greeter), the scheduling system allocates the workforce requirements accordingly.
Development of DdWS
Process Optimization and Data Gathering
The first step in developing DdWS required visits to several car rental facilities to understand operational differences and standardize the processes followed by the different work groups. At the macro-level, the operation flow was analyzed and improved with Value Stream Mapping. At a micro-level, processes were studied and optimized using time-and-motion analyses, and Standard Work Instructions were developed and posted at each workstation. Once the processes within a facility were standardized, data collection forms were developed and customized to reflect the operational differences at each facility. Time studies were conducted at key points throughout the system, and the data were fit into statistical distributions to account for variability in each process.
Model Building
Enterprise Dynamics® stood out as the simulation engine of choice due to its ability to effectively and accurately model virtually any problem, and its animation capabilities. The ability to visualize the solution to the stated problem in a virtual 3D environment greatly added appealed to the customer. Customized 3D icons were built to represent the airport terminals, rental office, cleaning station, car wash, guard post, in addition to the vehicles and people moving within the system itself.
Custom 3D animation greatly added appeal for the customer
Customers enter the system according to the forecasted weekly volume of transactions that can be narrowed into 15-minute intervals. Rental customers typically arrive at the airport, at which point a Courtesy Bus Driver shuttles them to the car rental facility. Upon arrival, some customers may wait in a queue to see a Rental Sales Agent, obtain their vehicle, and leave the facility. Other rental customers may directly go to the rental lot to obtain their vehicle and leave the facility. Customers returning a vehicle are acknowledged by a Greeter and shuttled back to the airport. Upon return, most cars are cleaned and washed by a Service Agent and returned to the rental lot. Some returned cars also go through the maintenance service before they are returned to the rental lot.
The simulation model records time stamps at key points throughout the system to track customer as well as vehicle waiting and processing times. In addition, utilization statistics are gathered for each workgroup in the system. These data were important in determining the optimal schedule for the facility staff.
User Interface / Data Management
A crucial step of the development phase lay in the user interface design since the user experience is vital to acceptance. The main application screen acts as a control panel. It clearly displays the week to schedule, facility location, and effectively stores records for the site with data input tabs. Users are able to accurately generate, save, and retrieve multiple what-if scenario schedules quickly.
How DdWS Works
Schedules are generated for the four main groups of resources staffed at the car rental facility: (1) Rental Sales Agents (RSAs) who process incoming rental customers, (2) Greeters (GRs) who process customers returning their cars, (3) Service Agents (SAs) who clean and wash the returning cars, and Courtesy Bus Drivers (CBDs) who drive customers between the rental facility and the airport. Mechanics who provide maintenance to the cars are also scheduled in the system but at a lower level of detail than the other resource groups.
Expected rental transactions drive the schedules of RSAs. An increase in expected rentals triggers an increase in RSAs needed in order to meet the service level specified. Similarly, rentals and returns drive the need for GRs and SAs, and rentals and round-trip travel time drive the need for more CBDs. The output schedule depends mainly upon transaction volume and variation throughout the day and week and the service level desired at several areas during a customer’s experience at the facility (for example, if the manager specifies that customers should wait no longer than 5 minutes to see an RSA, the software will schedule RSAs to accommodate this request).
Achieved Results
The staffing schedules generated by DdWS provide the car rental company with a solution to improving their scheduling system. Under- and over-staffing is evident when comparing actual past schedules with DdWS- generated optimal schedules for the same periods. Resources are now staffed following daily and hourly fluctuation in business demand, resulting in a reduction in labor costs and an improvement in customer service levels. The estimated reduction in labor costs is about eight million dollars annually for the rental company in their North America facilities while customer service remains consistently high at the desired levels.
DdWS schedules reduce labor costs and improve customer service levels