Design and Deployment of Dynamic Performance Targets for the Lastmile Field Executives in eCommerce Logistics Industry

Introduction

In today’s World of enhanced competition, the selling price of the products are governed by the market forces of demand and supply, and the firms enjoy a very little influence over the same. So, they have no option available than to resort to operational excellence for lean processes and reduced waste. They need to attack the problems as soon as they rise, in a smart manner. The ever-increasing competition and ever-decreasing profit margins have made it all the more essential to survive using operational excellence as the savior. The field executives are the key pillars for achieving operational excellence. The last leg of delivery is handled by the delivery staff or field executives (FEs) and thus their performance directly impacts the company overall performance as a logistic service provider. Hence, there is a need to design a monitoring system on the FEs which showcase their performance on day to day basis and at the same time over a period of time relative to other FEs in the same DC (Distribution Center) and also across the country. This not only helps the higher authority to keep an eye on FEs performance but also helps FEs to improve their performance as they get real time analysis on their performance respect to other FEs in the company. This, in turn, creates a sense of competition among the FEs which is beneficial for the company. There is need for a transparent system which would judge people solely on their performance and eliminate the middlemen intervention in the hiring or incentive process.

Since the eCommerce transactions happen in a humongous quantity, they generate a lot of data related to the influence of the shipment specific factors on the delivery performance which can be used the eCommerce delivery service providers to come up with a dynamic rating system for the FEs.

Since the lastmile logistics industry is being run by the field executives, it becomes essential to manage and monitor the performance of the field executives. Verill (2016) said that only what is measured can get improved, and emphasized on rewarding the aspects like attendance and regularity, and on quantifying the wow moments. The performance management consists of a set of activities starting with the setting of the targets. Therefore, this paper attempts to create a target setting framework for the field executives of the lastmile logistics industry.

Supply chains can perform well only if the human resources operating the same are well motivated and rewarded for the performance, while being penalized for the under-performance. This requires a fair, transparent and scientific method of appraisal which considers the shipment-related factors impacting their performance. Supply chains are more likely to be successful when the human resource factors create a competitive advantage (Gowen and Tallon, 2003 and Huo et al, 2015).

There has been a surge in eCommerce transactions in India and globally. This has led to creation of lot of employment opportunities in the eCommerce Sector. With the new employee acquisition, there comes a more important responsibility to retain the talent. An important pre-requisite to retain the talent is to ensure rewards to the performing talent in a fair and transparent manner. However, by virtue of its nature, the logistics sector in India has been an unorganized one. The delivery boys are generally outsourced to an outside organization. Also, since the job profile is more transactional and less cognitive in nature, the workforce in the doorstep delivery is at the lower end of intellectual spectrum of workforce. There is a prevalent practice of favoritism being displayed by the supervisors in hiring as well as the career progression of the field staff.

Also, the currently used evaluation models in this industry have not incorporated the impact of variability in location, payment mode and shipper type on a FE’s performance to convert a shipment. For instance, the chances to convert a prepaid Flipkart shipment vs chances to deliver a cash on delivery (cod) HomeShop18 shipment differ drastically. Similarly, the field executives serving higher order density localities will tend to appear more productive than the ones serving the low order density localities. Also, these evaluation models have the dependency on the delivery center heads for field executive’s ratings, thereby bringing in the respective heads and supervisor’s bias against a particular FE.

This research work describes the setting of smart and dynamic productivity targets for the field executives (which are function of delivery location, number of shipments, nature of shipments, etc.) given that each delivery location, and each shipment type has its unique characteristics which are beyond the control of the field executive.