Competition in the auto financing industry drives the need for creative and effective ways to meet and exceed customer expectations. The company’s Auto Financial Services (AFS) believes in the need to wow, and is constantly researching ways to stay ahead of its customers’ needs.
AFS, a global automotive finance company and one of the companies 28 businesses, is headquartered in Midwest. It operates in over 22 countries, and employs approximately 1,200 people. It maintains more that $25 billion in assets, with 950,000 leased vehicles. Given its vast reach and commitment to excellence, it was essential that AFS continually strives for process improvement in order to “wow” its customers.
As a response to the competitive market and their own internal quest for quality, AFS went to the source and conducted customer surveys to help it narrow down a goal. The survey responses, coupled with the company’s wish to capture a greater portion of the auto financial services market, led AFS to a target: customer service needed to be revved-up. Because of the high volume of credit applications, services were becoming bottlenecked and bogged down. Customer service goals were set to service customers more quickly, efficiently and effectively. It was evident application turnaround time and timely response of credit managers to the customer were the keys to success. Upper management and customers expected middle management to solve these issues. To help solve this challenge, middle management execs turned to ProcessModel simulation modeling for process improvement.
Customers supplied a significant amount of information relating to the originations (credit) area, therefore management decided to channel its efforts there. A cross-functional team was established to model the existing credit process.
The surveys submitted by the AFS customer base identified three critical requirements to improve their processes:
- Turnaround time of applications
- Accessibility of credit managers
- Predictability of credit decisions
To simplify the process, the team narrowed its scope to model turnaround time and the use of the credit managers.
In order to understand the model, it’s necessary to understand the origination (credit or underwriting) process. It begins when an application for credit is received from the dealership via email. Data entry personnel enter the application data (e.g., name of applicant, address, employer, social security number) and request a credit bureau on the applicant. The application data and bureau information is then forwarded on to the credit manager. The credit manager reviews the bureau score and application data and then decides to either approve or decline the application. That decision is emailed to the dealer.
Before the cross-functional team was established, originations management brainstormed and identified potential scenarios to improve the service provided to dealers.
One area that management thought could be improved was making sure the work hours of credit managers reflected those of the customers. They also brainstormed that service might be enhanced by combining prime and subprime credit manager teams. The process simulation software let the team put their ideas to the test.
The team modeled two different credit process scenarios to improve their processes. One scenario consisted of establishing credit manager regional teams aligned by time zone. The other, a “pod model,” modeled matching up credit manager schedules by sales force coverage along with combining the prime and subprime credit managers.
The team found that applied simulation modeling is accurate, scalable and versatile as long as input is precise. This fact drove the team to an even greater level of quality. For example, initial time estimates for various process steps that were input into the model were simply not accurate. These measurements had to be replaced by more exact readings obtained through stopwatch analysis. As the team became more versed with the process of applied simulation modeling, they found that ProcessModel offered them an invaluable tool to achieve greater quality–quicker and more accurately than with previous systems. The system was even comprehensive enough to handle whole dimensions of a process, such as elaborate shift schedules for underwriters. The pod model reduced turnaround time by 58% and increased credit manager usage. The simulation helped AFS understand and improve the process in record time.