Business Process Analysis and Improvement for a Third Party Logistics Provider in Indonesian Cold Chain Logistics

Abstract

Indonesian consumer awareness to seek for quality fresh food products is increasing. Therefore, a cold chain logistics is required to deliver agricultural and fishery products across islands. The number of logistics providers in Indonesia are continuously growing, especially for cargo services. Our objectives are to identify the business processes and related activities in a cold chain logistics provider, to analyse problems and to provide recommendations for improvement. We conducted an in-depth interview and analysed the business process using Integration Definition for Function Modelling (IDEF0). The results showed that the major problems are lack of proper cold chain logistics and knowledge in supply chain management. Then, we recommended to improve efficiency in the major activities. These could be the direction for further development to enhance Indonesian cold chain logistics especially for other third party logistics providers to improve their competitive advantages.

Utilizing an Intervention Forecasting Approach to Improve Reefer Container Demand Forecasting Accuracy: A Case Study in Indonesia

“…This case study was conducted at a third party logistics company that specializes in transportation and is located in Surabaya, East Java, Indonesia. The company was quite familiar with the researchers due to past project partnerships and thus felt comfortable sharing their internal/confidential supply chain issues (Pradita and Ongkunaruk, 2019). Based on an in-depth interview with Indonesian practitioners, poor forecasting practices were found to play a significant role in reefer circulation issues.…”

“…The second problem is multiple sources of uncertainty, such as market conditions, and the third problem relates to the handling and sharing of operations information. These problems affect every third party logistics provider, increasing their operational costs as well as creating a shortage of containers and reducing their income (Pradita and Ongkunaruk, 2019). Previous research on container demand forecasting in the area of reefer containers has been as follows: Wang and Meng (2019) compared three forecasting models for the number of inbound of containers, while Tang et al (2019) studied container throughput forecasting at Lianyungang Port and Shanghai Port by comparing the Gray model, triple exponential smoothing model, multiple linear regression model, and backpropagation neural network.…”

The Use of Supply Chain Risk Management Process (SCRMP) in Third-Party Logistics Industry: A Case Study in Indonesia

“…1. Lack of Strategic Forecast (R1) Previously, company implementation of forecast strategy was only based on experience from the manager of the sales and marketing department, not with the aid of historical data by the use of forecasting tools (Pradita & Ongkunaruk, 2019). Container forecasting was also combined between export containers and local containers, resulting in a forecasting error that caused delays in shipping and reduced the customer service level.…”

“…Tanjung Perak port is one of the largest and busiest ports in Indonesia. Its capacity has remained the same since 2000, but activities such as loading and unloading of cargo in Tanjung Perak port have recently seen an exponential increase (Pradita & Ongkunaruk, 2019). The resulting overcapacity created a congestion issue, with long queues presenting daily during the loading process.…”

“…This logistics company delivers food products, such as seafood and temperature controlled meals, across Eastern Indonesia for the food companies they serve. Despite having much experience in cold chain transportation, the company must keep improving its business performance to compete with other companies (Pradita & Ongkunaruk, 2019). As global competition becomes more challenging and supply chains become increasingly complex, the possibility of failures in the supply chain can arise due to the risks.…”