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The delivery system for Base Transceiver System (BTS) to strengthen the telecommunication network throughout Indonesia maritime country is needed to speed up the process due to uneven distribution of sufficient telecommunications infrastructure. PT. Gunadhya Rajawali Logistik (GRL) is a third-party logistics company that focuses on transportation and warehouse management and delivery for telecommunication equipment tools. Unfortunately, in delivering BTS installation part throughout Indonesia, PT. GRL received several warning letters and had to pay a penalty from one of customers, for being late in reporting the delivery proof. This study aims to analyze the root causes of late submission of Soft Copy of Proof of Delivery (SCPOD) to avoid penalty given by the customer and determine suitable solutions to improve the process. The approach used in this study is lean six sigma with the help of Define, Measure, Analyze, Improve, and Control (DMAIC) roadmap. According to the interview with the employees related, the root causes of late submission of SCPOD are irresponsible drivers, indiscipline drivers in carrying out deliveries, and lack of data management in the transportation system. To be able to solve this problem, several proposed solutions can be applied. The proposed solutions to overcome the root causes that should be applied by the company are to hire a document control, retraining the Standard Operating Procedure (SOP) for drivers, utilize transportation management system application, and apply incentive systems for drivers. In the future, it is recommended for PT. GRL to have a minimum standard in recruiting the drivers for example only recruit who possess a minimum of high school education to ease the completion of administrative tasks.  

This research aims to observe current inventory management applied by one of the medical equipment distributors specializing in eye health devices, and provide recommendations for an optimal inventory management system to achieve cost efficiency afterward. The method used in this research is quantitative, focusing on processing and analyzing numerical data obtained from the company to calculate safety stock and the number of orders. In addition, ABC classification is also used in data processing to group items based on their value. Items belonging to class A (having a value of 80% for the company) will be used in the data processing. The next step is to conduct forecasting simulations for demand forecasts. The results of the forecast will be used for calculating the safety stock and order quantity. The output from the results of data processing and analysis in this study shows 67 items included in class A, which will then be processed using Minitab software for forecasting. Based on comparing the four forecasting methods, the one with the lowest error value is Trend Analysis. If the company can apply the storage method according to the fixed-time period model calculation, there is a potential savings of US $ 717,133 or 63% of the total overstock