Intelligent quantity control method for service capability

Abstract

The invention relates to an intelligent quantity control method for service capability, and the method comprises the steps: carrying out the quantification of the service capability, and obtaining thetotal capacity; determining deducted capability according to the order information; when a query request is received, calling the total capacity and the deducted capacity of the specified time according to the query request, and calculating the remaining capacity; and feeding back the query request according to the remaining capacity. According to the scheme, the service capability is quantified,the remaining quantity of the service capability is dynamically calculated, and the service capability information is fed back in time, so that the service capability can be accurately controlled, the service capability is uniformly and orderly released, the situation that the service cannot be provided on time after reservation is avoided, and the user experience is improved.

Description

technical field [0001] This application relates to the technical field of data maintenance and forecasting, and in particular to an intelligent control method for service capabilities. Background technique [0002] For service products, such as after-sales service, it is not possible to choose a service appointment time on some e-commerce platforms. There are also some platforms that can choose the service appointment time, but the control of service capacity is subjectively maintained by the operator based on experience, historical orders, and the number of engineers summarized by the full-time personnel in the region. [0003] In related technologies, due to the lack of an objective method to accurately calculate the number of engineers in different regions and different service categories, it is easy to have insufficient engineers' ability in actual business, so that the scheduled service cannot be provided at the scheduled time. This further leads to a high rate of pass...

AI Technical Summary

Problems solved by technology

[0002] For service products, such as after-sales service, it is not possible to choose the service appointment time on some e-commerce platforms

There are also some platforms that can choose the service appointment time, but the control of the service capacity is subjectively maintained by the operator based on experience, historical orders, and the number of engineers summarized by the full-time personnel in the region.

[0003] In related technologies, due to the lack of an objective method to accurately calculate the number of engineers in different regions and different service categories, it is easy to have insufficient engineers in actual business, so that the scheduled service cannot be provided at the scheduled time

This further leads to high passive rebooking rates, poor service experience, and high complaint rates among consumers

[0004] In addition, many services need to consider seasonal factors. If the number of service personnel is maintained at the off-season level, the operating capacity required for peak season service orders cannot be guaranteed.

If there is temporary personnel reinforcement during the peak season, the operation staff at the headquarters cannot obtain the personnel reinforcement information in time, resulting in inaccurate control data

[0005] For service providers, the lack of objective regional and category actual engineer job arrangements can easily lead to insufficient or excess regional capacity and inaccurate appointment service time. The complaint rate is high; when the regional capacity is excessive, it is more difficult to manage service providers and engineers

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