Designing Work for Online-Offline Service Integration through Process Mining: A Case of Food and Beverage Business in Bangkok Metropolitan Area
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Abstract
Modern service businesses must enhance their capability to operate and manage efficiently within the Future of Work framework. The advent of digitalization and artificial intelligence does not only play a part in the application of technology but also influences the way services are provided. Designing and improving service processes must consider the aspects of workforce augmentation due to the inevitable higher degree of interaction between service providers, technology, and customers. This study collected data on 6,520 recorded events within customer orders from 1,630 customers over a one-month sales period. The data were gathered from the point-of-sale system and combined with surveillance data from that period. The samples of event records, sales data (customer orders), and surveillance data were then analyzed using a process mining approach. Service processes and tasks performed by employees when providing services to the customers, interacting with the point-of-sale system, and facilitating customer payments in online and offline manners were analyzed to enable the discovery of work patterns and the acquisition of valuable insights aimed at enhancing service provision. The results showed that throughput time per customer order increases by 41.4% when services operate under online-offline mode. Inefficient activities when the staff work collaboratively consist of online order processing, offline customer service, online customer service, online-offline customer order taking, and online-offline customer payment. The findings are useful for the business in designing new workflows that foster appropriate levels of interaction and augmentation for its service delivery.
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