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Improving the efficiency of the return process : the case of JD Logistics warehouse

Wang, C. (2022) Improving the efficiency of the return process : the case of JD Logistics warehouse.

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Abstract:Problem definition As an operation intern at the Return department, I am responsible for monitoring the daily performance and communicating with leaders in the warehouse to make resource adjustments. During the internship, JD Logistics on average received 20 email complaints when customers could not receive their refund in a short valid time, and this huge number had a negative effect on customer satisfaction. Furthermore, the company internally stated that they had a low margin when considerable working hours need to be paid to operators. The action problem is revealed by the company that JD Logistics is now having low efficiency of the return process in the warehouse. Two potential core problems are defined: first, the Return department has poor resource management strategies which leads to both inaccurate return order forecasts and inappropriate labor arrangements. They will further affect operators’ performance and then reflect on the low return efficiency. Second, the operation process within the return system is complicated. Numerous user-unfriendly steps waste operators’ time and hence lead to low return efficiency. As a result, the main research question is defined as: How can operation process optimization and resource management strategy improve the return process efficiency? To answer this question, an investigation into the operation process and resource management is conducted as perspectives of improving the return process performance. Research methods The Managerial Problem-Solving Method (MPSM) is the main methodology for this research. The first step is to analyze the current situation. In this phase, the current situation of the company is analyzed by observations of the return processes, communication with employees at the Return department and operators in the warehouse. Data analysis of operators’ performance is also conducted. By implementing the problem cluster, the potential core problems can be identified. Then literature review is conducted to perform the historical study on organization efficiency and select my theoretical perspective. Business Process Management is selected as my theoretical perspective to gain insights into problem-solving. To operationalize the variables within the research, KPIs need to be defined and selected. They include mobility, of operators, effective working hours, productivity per task, overall productivity and customer satisfaction. The inspiration for new solutions can be obtained through the literature review and brainstorming session, existing solutions are supported by literature whereas new solutions are generated through a brainstorming group. Solutions are based on two different perspectives: operation process and resource management strategy. Operation process aspect: • Cancel put-away containers • Advance the refund point • Transfer putaway task to AGV zone • Change the current pre-inspection information input method o Partial scan method o Full scan method Resource management aspect: • Control operators' mobility in the warehouse • Forecast the return order numbers • Arrange resource allocation reasonably Due to the time limit, only operation process concerned solutions are selected to be implemented. JD Logistics also agrees that the operation process has a higher priority than resource management in the current circumstance and optimizing the return process is imminent for the company. However, the historical performance data also provide information for resource management and through systematic statistics of data, recommendations based on resource management are made to JD Logistics based on the As-Is situation. Results Systematic statistics of data exported from WMS have to be analyzed through MS Excel functions. Evaluation of performance based on KPIs will result from the observed data and in form of graphs to support decision-making objectives. By applying the VLOOKUP to the data used in the WMS, the objectives on the respective level will be visualized within MS Excel. Based on the graphs, the company gains insights into the relationships of KPIs and makes decisions. The results show that by canceling put-away containers, the productivity at the pre-inspection increases from 11 orders per hour per operator to 15 orders per hour per operator. Overall return process productivity increase by 38.18% from 44.87 to 62 orders per operator per day. The refund point advance solution increases customer satisfaction by 27.5%. The full scan method increases the pre-inspection productivity from 11 to 15 whereas the partial scan method improves the pre-inspection productivity from 11 to 17. The overall return process productivity increase by 15.9% and 21.9% respectively for these two methods. Putaway to AGV zone has a putaway task productivity improvement from 19.3 to 23.3 orders per operator per hour, the overall return process productivity increase by 5.2%. Conclusions JD Logistics is suggested to implement all operation process solutions in-depth in the future except for the putaway solution. In terms of the overall productivity, putaway to AGV zone has relatively small improvements compared to other operation process solutions. Therefore, the company needs to take further consideration. In terms of resource management strategies. Maximum task mobility of two at the return process is suggested. During the investigation of the historical performance of operators, operators have the best and most stable performance if one person at most does two types of tasks at the return process. An accurate return order forecast should follow the outbound order quantity from historical days. The datatrace shows that most outbound orders arrive at the warehouse as return orders equally between 7 to 9 days after shipment. Furthermore, two types of outbound order types are recognized and their proportion of the total outbound orders can be gained. Therefore, a forecast of return order quantity to be received on day x can be estimated by historical outbound quantity back to 7 to 9 days before. The operator allocation for the return process should follow the theoretical operators needed for each task to finish the same target orders. The performance history shows when there are 1000 return orders, the closer the allocation proportion to pre-inspection: transfer: putaway = 11: 3: 6, the better efficiency the return process has. Due to the time limit, operator performance solutions did not manage to implement, the company is advised to test the reliability and validity of resource management-related solutions as one of their further research directions.
Item Type:Essay (Bachelor)
Faculty:BMS: Behavioural, Management and Social Sciences
Programme:Industrial Engineering and Management BSc (56994)
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