Improving Sales Process of an Automotive Company with Fuzzy Miner Techniques

Abstract

The main objectives of this paper is to investigate and study the sales process of an automobile company by applying Fuzzy Miner process mining technique on a set of data/event logs previously collected from the sales department of the company. The current work aims to analyze the behavior of unsuccessful (or bad) employees in the automobile's sales department with the intention of benchmarking the performance of the sales operation management team leading to increased/improved efficiency, effectiveness and productivity. After initial analysis of the collected event logs (data), it was found out that although each employee in the sales department has played a role (i.e., contribution) in the selling car process, but the time spent in each stage to accomplish the assigned job, in addition to the accuracy of the tasks performed by each individual, were not the same. Accordingly, it was realized that 3% of the sales staff could not achieve the selling targets successfully and therefore they were ranked amongst the Bad Sellers. However, 30% of the employees could outperform the defined selling targets and therefore they were ranked amongst the Excellent Sellers, while 67% of the sales people exhibited an average performance and therefore they were considered as the Normal Sellers. Consequently, the appliance of the Fuzzy Miner technique could help the sales administrators/managers to track, trace, visualize and simulate the behavior of Excellent and Bad Sellers in novel ways. The discovery and revelation of such information could be beneficial to improve the overall performance of the sales department leading to increased amount of sales, improved customer satisfaction and emergence of more opportunities for the automobile company.

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