Margins of error
Increasing familiarity with the system for external reporting eventually led StateFleet to look at deepening its use of the SAS-based analytics for more complex data analysis -- including the type of predictive modelling that would reduce the risk associated with its leasing forecasts.
StateFleet worked with SAS to identify the business factors involved in its processes, including both basic figures such as car purchase and disposal prices, and external factors such as changes in interest rates. Each of those factors was then weighted as part of a more comprehensive predictive model, which provides both standard measures of variability and the ability to change them to suit changing market conditions in the long term.
When your entire business all but depends on the success of such a model, you consider it extremely carefully. Actuarial support and the involvement of SAS industry specialists helped refine the model further, yet Wright says there were reservations about changing the forecasting model so dramatically.
"Some people questioned what was happening," Wright concedes. "There are always people who will question something that gets spat out of a model compared with what their gut feeling says."
Many critics were silenced, however, after runs of the new models against historical data proved that it was quite effective at forecasting major industry changes. Based on this work, StateFleet has gradually transitioned onto the new system to support its forecasts of vehicle value.
A new forecasting platform
The results of the new forecasting model won't be known until early 2008, when the first vehicles managed under contracts created with the new system come off of lease. However, judging by the organisation's work so far, Wright is optimistic that the SAS solution has increased the accuracy of its latest forecasts.
With such high revenues involved, even a one percent improvement in forecast accuracy could increase revenues by as much as AU$2 million, says Wright -- more than justifying the time, money and effort involved in the project.
In the long term, the SAS platform will be integrated with a new fleet management system (FMS) currently being rolled out across StateFleet. Further refinement of the SAS model is on hold until the new FMS -- which will ditch StateFleet's antiquated Ingres-based system for a new Oracle-based environment -- goes live later this year.
Wright expects the combination of a highly refined analytics system and a robust FMS to provide a strong new foundation on which StateFleet can continue to improve its business. "It's something we're still refining, and we will continue to refine it," he says.
"It has been a valuable tool that has made us more accurate, and given us more confidence in the numbers that we put out. We weren't that far out to begin with, and have been able to get more accurate since we started [with the new system]. If we'd had this system in the past, [our forecasts] would have been even closer. We think the marriage of the two systems will make life even better."
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