PHARMACEUTICAL PRODUCT DISTRIBUTION WITH DEMAND INFORMATION SHARING AT PT DEXA MEDICA AND PT ANUGRAH ARGON MEDICA
The rapid growth of pharmaceutical industry in Indonesia led to the increasing demand uncertainty faced by PT Dexa Medica. As one of the largest ethical pharmaceutical company in Indonesia, PT Dexa Medica should show a better performance than its competitors in order to meet customer demand. Unfortu...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/18707 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | The rapid growth of pharmaceutical industry in Indonesia led to the increasing demand uncertainty faced by PT Dexa Medica. As one of the largest ethical pharmaceutical company in Indonesia, PT Dexa Medica should show a better performance than its competitors in order to meet customer demand. Unfortunately, during the year 2011, average PT Dexa Medica’s order fulfillment is only 78% from the target of 100% and this low order fulfillment resulting stock out at the Regional Distributor Center level. The number of Regional Distributor Center experiencing stock out is 10 Regional Distributor Center from the 37 Regional Distributor Center or approximately 30% of the entire Regional Distributor Center. This research aims to develop a process simulation model for determine the best possible business solution to improve order fulfillment in PT Dexa Medica and to reduce stock out in Regional Distributor Center.Demand and supply actual data during January – December 2011 was used to modeling existing system. Root cause analysis showed that root causes of this symptom were: capacity of granulation machine is not sufficient, marketing division is using method that does not fit top predict the seasonal demand, sales forecast is not supported by information sharing and data updates and rationing of products are based only on sales forecast. The possible solutions offered include the addition of granulating machine capacity,using selected forecasting method in accordance with demand pattern to predict demand,forecast updating using demand data from Regional Distributor Center, and using new inventory management policy. The result of analysis identifies 12 possible business solution scenarios.These scenarios then simulated using Monte Carlo simulation to assess the optimal operational performance for the company.Simulation results showed scenario with the addition of granulating machine capacity,forecast updating every 3 months using forecasting method 3 month weighted moving average and decentralization periodic distribution predicted to give order fulfillment 100%, the lowest stock out and total cost. |
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