Increasing Inventory Turnover Rate at CV Adil
CV Adil is a construction material retail company residing in Bandung. As a retail company, inventory management is a crucial factor for CV Adil. However, after analyzing the inventory data, it is found that their inventory turnover rate (2.5) is way smaller than the average inventory turnover rate...
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Format: | Theses |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/31735 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | CV Adil is a construction material retail company residing in Bandung. As a retail company, inventory management is a crucial factor for CV Adil. However, after analyzing the inventory data, it is found that their inventory turnover rate (2.5) is way smaller than the average inventory turnover rate of the industry (5.9). This problem has been going on for quite some time and, unfortunately, went undetected by the owner because of their conventional principle and business methods. <br />
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Through conceptual framework, it is found that overstock, non-moving inventory, and weak sales are the factors that influence the inventory turnover rate. On the other hand, the low inventory turnover rate increases the inventory cost which leads to net profit decrease. Current business processes in CV Adil are described using Business Process Modelling and Notation (BPMN) diagram. After further analysis using Current Reality Tree (CRT), three root causes of were found. With consideration of several limitations, two of these root causes are discussed further, which are: no inventory planning system and poor monitoring system. <br />
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Several business solutions were generated from further analysis. The first one is a recommendation of applying the best forecasting and inventory planning model for CV Adil, which are linear regression forecasting and Q-Model. Regarding their monitoring system, CV Adil is suggested to develop their own software by recruiting programmers and conduct a scheduled stock opname procedure. For future research, it would be better if Q-model is combined with the linear regression forecasting method. |
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