Premium customer, quickest service? Not so fast, at least in a world of agentic AI-driven services
It's conventional wisdom in the business world: Premium customers get a pass to the front of the line. Think airports or amusement parks. But new research from the University of Michigan finds the best approach—at least in the realm of data processing services—may be placing those big spenders in the "better-but-later" queue and completing the smaller jobs first.
In the realm of data processing services, including those powered by artificial intelligence, a new study from the University of Michigan suggests that premium customers may not always benefit from being placed in the front of the line. According to researchers Mojtaba Abdolmaleki, Izak Duenyas, and Roman Kapuscinski, completing smaller jobs first could actually increase profit by 2.5% in comparison to a first-come, first-served approach, and by nearly 5.5% compared to conventional high-value-first scheduling.
The researchers argue that premium AI services should receive a quality lane, rather than a fast lane, as dedicating resources to the most demanding jobs may cause smaller, less complex tasks to wait. For instance, a simple tax return requiring minimal analysis could be completed within a minute, while a comprehensive filing for a business with multiple entities, forms, and transactions could take hours.
If the longer job were placed first, the shorter one would experience a significant wait, but by processing the quicker job first, the total waiting cost could be reduced by around 58%, despite the more complex job being delayed by only a minute. This approach ensures that customers are informed about the expected completion time, rather than receiving an inferior service under the guise of prioritizing high-value work.
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