Articles

Optimizing Time and Cost Efficiency in Delayed Construction Project Using Project Crashing Approach (A Case Study of a Geothermal Power Plant Operator in Indonesia)

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Electricity is a fundamental need that supports modern life across household, industries, and public sector. To ensure the sustainability of electricity in Java and Bali, PT GSE,a Geothermal Power Plant in Pengalengan, West Java, conduct a base structure replacement project for cooling tower which innitialy using the wooden base structure into the Fibre Reinforced Polymer (FRP). This project, known as Project X, was executed by PT XYZ as the EPC contractor. During the execution, cooling tower unit – 1 faced significant delay, posing financial and reputational risks. This research aims to identify the root causes of the delay, evaluate the losses, and proposed solutions for time and cost efficiency using the project crashing method. This research combine interview with key personnel and secondary company data. The critical path analysis conducted by using the Activity on Node (AON) approach, activity mapping using Precedence Diagram Method (PDM), and calculation for additional cost due to overtime conducted by using minimum wages (UMK) for Kabupaten Bandung in 2025. S Curve analysis shows 10 weeks of delay, mainly due to frequent bad weather that prevented outdoor activities according to the HSSE policies. Financially, if there is no corrective action to handle the delay, PT XYZ would be subjected to a project penalty of Rp 2.734.770.052, as stipulated in the cooperation contract with PT GSE. To anticipate the losses, the proposed solution is project crashing by conducting overtime to the critical path activites, which is safer dan more efficient comparing to adding new additional resources. The implementation of project crashing calculated need extra funding about Rp 399.544.839 which only 14,61% compared to the potential penalty sanction. Beyond the financial impact, this strategy also maintains client trust and strengthen future business opportunities.

Engagement Analytics and Employee Retention: Challenges and Opportunities

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Employee retention is one of the major challenges for organizations, especially in IT sector, where high turnover rates can impact performance and increase costs. This study explores the role of engagement analytics in mediating the relationship between overtime, Job Satisfaction, and employee attrition. Utilizing secondary data from Kaggle and with the help of python’s libraries like Numpy, Pandas, Seaborn, Scipy stats, matplotlib and Networkx for analysis and visualizations, the study conducts correlation analysis to determine whether Job Satisfaction affects employee engagement to find that Job satisfaction is positively associated with engagement levels and mediation analysis among Overtime and employee attrition keeping engagement as a mediating variable to find that engagement has a minimal mediating effect on attrition whereas overtime highly positively affect attrition. The study leaves scope for further research governing unexplored factors affecting engagement and retention through primary data. The study also informs about the opportunities and challenges of integrating engagement analytics in driving employee retention.