Start Date
11-12-2016 12:00 AM
Description
Selling has long been considered as an “art” driven by personal intuition and native sales talent. However, significant changes have occurred over the past 30 years, as a result of technological advances and changing customer expectations. As one answer to these changes, practitioners and scholars have promoted the idea of “sales as a science”, relying on documented, repeatable ways of selling that reflect scientific methods. We argue that process mining is a relevant candidate for empowering “sales as a science” via its capacity to analyze, discover, and enhance end-to-end processes. Through a design science approach, we propose a framework for applying process mining to sales, comprising a refined notation and seven process mining analysis scenarios. Our study represents a first step towards gaining a better understanding of real-world sales processes based on digital traces from operational systems e.g., customer relationship management (CRM) systems, or emerging technologies e.g., smart watches.
Recommended Citation
Bernard, Gaël; Boillat, Thomas; Legner, Christine; and Andritsos, Periklis, "When Sales Meet Process Mining:
A Scientific Approach to Sales Process and Performance Management" (2016). ICIS 2016 Proceedings. 15.
https://aisel.aisnet.org/icis2016/ISDesign/Presentations/15
When Sales Meet Process Mining: A Scientific Approach to Sales Process and Performance Management
Selling has long been considered as an “art” driven by personal intuition and native sales talent. However, significant changes have occurred over the past 30 years, as a result of technological advances and changing customer expectations. As one answer to these changes, practitioners and scholars have promoted the idea of “sales as a science”, relying on documented, repeatable ways of selling that reflect scientific methods. We argue that process mining is a relevant candidate for empowering “sales as a science” via its capacity to analyze, discover, and enhance end-to-end processes. Through a design science approach, we propose a framework for applying process mining to sales, comprising a refined notation and seven process mining analysis scenarios. Our study represents a first step towards gaining a better understanding of real-world sales processes based on digital traces from operational systems e.g., customer relationship management (CRM) systems, or emerging technologies e.g., smart watches.