KPI ASSESSMENT USING BUSINESS PROCESS ANALYSIS, DETERMINISTIC AND STOCHASTIC MONTE CARLO SIMULATION. CASE: KPI FUEL RATIO (LT/BCM/KM)

• Main Author: Artha Putra, Gilang
• Format: Theses
• Language: Indonesia
• Subjects: Manajemen umum
• Online Access: https://digilib.itb.ac.id/gdl/view/62509
• Institution: Institut Teknologi Bandung

The study investigates a Key Performance Indicator (KPI) named Fuel Ratio that measures fuel efficiency in mining operation, expressed in lt/bcm/km unit. Fuel efficiency becomes one of critical success factors in mining operation performance because the cost of fuel takes the largest portion for around 40% to 60% of total mining cost. The mentioned Fuel Ratio KPI measures input-output rate from three variables: Fuel consumption volume (liters), material production volume (bcm-bank cubic meter) and hauling distance (km). In actual, unfortunately, the KPI fails to measure the fuel efficiency. Instead, it has created confusion among analysts and decision makers in a mining company by its anomaly. Whenever the fuel efficiency strategy by reducing haul distance and haul truck number unit is executed, this KPI will show a higher number and interpreted as inefficiency. This investigation is a part of a KPI Life Cycle which known as KPI Assessment phase to review if the KPI still has the capability to provide a good measurement. The method of this research is using combination of both qualitative and quantitative approach. Started with Business Process Analysis (BPA) approach to modelling current KPI formulation into a flow chart diagram with cause-effect technique. Then the results from BPA phase are validated through simulation analysis in both deterministic and stochastic Monte Carlo methods. To support the validation phase, actual operational data is collected from database. The assessment discovered that anomaly of this KPI was occurred because current formulation incorporating parameters that irrelevant with haul distance variable. Once the irrelevant parameters were eliminated from the calculation in the simulation experimentation, the anomaly of the KPI was disappeared. The output of this research suggests that the KPI requires a new formulation that has different treatment for each fuel component variable based on their relevancy to haul distance variable. The outcome from the solution is mining operation with the help from new KPI Fuel Ratio will be more confident in doing their fuel efficiency strategy and take more profit without fear of the false alarm.