Articles

Strategic Decision-Making: Implementing Artificial Intelligence for Customer Experience in XYZ Electricity

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This case study outlines the challenges in resolving customer complaints at XYZ electricity provider, where the industry achieves only 89.16% against a 100% service level agreement, leading to poor customer experience (CX). The objective of this paper is not only to identify the root causes of poor CX and validate artificial intelligence (AI)’s potential role as a solution, but also to pioneer the identification of critical success factors (CSFs) and strategic areas for AI implementation, leveraging computational ratings to enhance decision-making processes. This research employs comprehensive data collection methods, including primary data from interviews and workshops involving 300 participants and secondary data from observation and literature studies. It utilizes an integrative strategy framework (ISF) to strategically synthesize internal and external analyses. Additionally, it ranks critical areas for AI implementation using the analytic hierarchy process (AHP) based on pairwise judgment and Likert scale surveys from ten experts. The most significant findings reveal that direct impact on customers, at 28.54%, is the strongest CSF, while customer service, 14,63%, is the most impactful implementation of AI in the XYZ to fix poor CX. A pilot project on customer service can improve CX, revenue, and cost savings. The authors suggests that another researcher implement and evaluate AI in various businesses and specific client categories.

Measuring the Critical Success Factor of Safety Program in Drilling and Well Intervention Operation at PT. MHK, Ltd.

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The drilling and well intervention division implements various safety initiatives to prevent incidents. Despite its multiple activities, an assessment has yet to be conducted to determine the program’s efficacy. This paper aims to determine the elements that impact the effectiveness of safety program execution in drilling and well intervention operations in MHK, Ltd. The Author conducted measurements utilizing variables related to the critical success factor of the safety program, as outlined in the cross-reference research article. Subsequently, the author introduces a system of incentives in variables quantified as a novelty of this research based on input from subject matter experts. By understanding the variables that influence the efficacy of the safety campaign, the safety campaign initiatives will be more focused on mitigating accidents within the drilling and well intervention divisions. The research was conducted utilizing a quantitative approach, where data was gathered through a questionnaire that employed a Likert scale. The population comprises individuals employed in the Drilling and Well Intervention roles at many locations, including the site, field, barge, rig, and town. The data is further analyzed using the Partial Least Squares Structural Equation Modelling (PLS-SEM) technique, employing the smartPLS4 software. The study findings indicated that three out of five variables examined had a favorable and significant impact on the efficacy of the safety program at DWI MHK, Ltd.: management commitment, reward and punishment, and safety arrangement. We propose strengthening identified elements and addressing weaknesses, including utilizing digitalization and artificial intelligence for safety monitoring.