A table that captures the predicted number of successes (or failures) to the observed number of successes (or failures).
Published in Chapter:
Use of Data Analytics to Increase the Efficiency of Last Mile Logistics for Ecommerce Deliveries
Gaurav Nagpal (Birla Institute of Technology and Science, Pilani, India), Gaurav Kumar Bishnoi (Birla Institute of Technology and Science, Pilani, India), Harman Singh Dhami (Birla Institute of Technology and Science, Pilani, India), and Akshat Vijayvargia (Birla Institute of Technology and Science, Pilani, India)
Copyright: © 2021
|Pages: 14
DOI: 10.4018/978-1-7998-3053-5.ch009
Abstract
With the increasing share of digital transactions in the business, the way of operating the businesses has changed drastically, leading to an immense opportunity for achieving the operational excellence in the digital transactions. This chapter focusses on the ways of using data science to improve the operational efficiency of the last mile leg in the delivery shipments for e-commerce. Some of these avenues are predicting the attrition of field executives, identification of fake delivery attempts, reduction of mis-routing, identification of bad addresses, more effective resolution of weight disputes with the clients, reverse geo-coding for locality mapping, etc. The chapter also discusses the caution to be exercised in the use of data science, and the flip side of trying to quantify and dissect the phenomenon that is so complex and subjective in nature.