FINANCIAL RISK EARLY WARNING SYSTEM FOR PT DELTA DUNIA MAKMUR TBK IN FACING DISRUPTION OF SUPPLY CHAIN

• Main Author: Kiky Adhisti, Ariesti
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/70777
• Institution: Institut Teknologi Bandung

Business environment has changed a lot lately. Most of the factors that fueled are supply chain disruptions, Covid-19, and have been exacerbated by the war in Ukraine and the resulting sanctions on Russia. These conditions can negatively impact companies in a way of higher operational cost and the risk of low supply of the materials. During quarter 1 to 3 of 2022, the highest material’s price increase is fuel 91%, Ammonia 27%, tyre 13,8%, spare parts 9%, and lubricant 10,8%. High material prices will increase operational cost and reduce the profit margin. From the supply side, during quarter 1 to 3 of 2022, spare part’s OTIF is 81,8% and tyre is 57,2%, both are below the target level of 95%. It can delay the maintenance of heavy equipment and delay the production. This research is divided into four sections: assessment of risk, z-model analysis, ratio analysis, and risk treatment construction. After conducting the risk assessment of internal and external factors, the author found the main risk sources. Z-score model analysis resulting in the company posing great risk of profitability. Further analysis of financial ratios of profitability ratio resulting in being below the industry average. Combining these qualitative and quantitative analysis leads to the company focusing on supply chain disruption risk. Thus, the early warning system is constructed and the risk prevention formulation is defined. The indicators of an early warning system consist of operational indicators and financial indicators. Each of the indicators has their own measurement unit and is divided into 3 criteria values, named as Green, Yellow, and Red. Risk prevention actions also prepared are divided into 3 time spectrum of completion, which are short term (1-6 months) to minimize the negative impacts, medium term (6-12 months) to optimize business operations, and long term (1-3 years) to transform value chain structure. The early warning system in this study is constructed qualitatively. The future study should do additional analysis to validate whether the indicators put in have the right correlation with the risk source. So, it will minimize the possibility of mismatches between the early warning indicators and the risk source.