Operational Risk Management Research Articles

Differentiating “must–have” and “should–have” supply chain capabilities for enhanced performance: a necessary conditions analysis

Purpose This study aims to identify the “should have” and “must have” capabilities required to boost a supply chain’s robustness and operational performance. Research on supply chain capabilities and their impact has long been central to the supply chain discipline. However, empirical studies continue to report mixed results regarding the relationship between integration and performance or agility and robustness. Using a novel methodological approach, this study explores how supply chain integration, agility and supply chain risk management activities influence the operational performance and robustness of supply chains. Design/methodology/approach Data was collected through surveys and analyzed using SmartPLS 4 and necessary condition analysis (NCA). This combined approach shifts focus from average trends to identifying the required levels of capabilities, offering insights into the necessity logic of supply chain strategies. Findings The study reveals that supply chain risk management and internal integration significantly influence operational performance and robustness. It also supports agility as a precursor to enhancing supply chain robustness, aligning with contemporary theoretical perspectives. Practical implications The findings suggest the importance of integrating risk management and internal processes to enhance supply chain performance and robustness. Additionally, agility emerges as a critical strategy in navigating disruptions, emphasizing the need to prioritize it in supply chain management. Originality/value By adopting a holistic approach grounded in dynamic capability theory, this study contributes to understanding the interplay of supply chain strategies amid unprecedented challenges. The combined use of SmartPLS 4 and NCA offers a novel perspective, shedding light on the necessary logic of supply chain capabilities.

IOT IN CONTAINER SHIPPING INDUSTRY: APPLICATIONS AND EXAMPLES OF SOLUTIONS

The study analyzes the participation of technologies related to the development of the Internet of Things (IoT) network concept in the intermodal container transportation system. Since the beginning of the XXI century, IoT-related technologies have been dynamically spreading in almost all areas of international business, and this has changed the understanding of cargo owners about the quality of transportation services, among other things. Since transparency in monitoring the location of high-value goods is extremely important for transport companies, cargo owners, and all other stakeholders, and the intermodal transportation system is extremely complex due to the number and diversity of communications, the need to use IoT is obvious. As analysts predict that the introduction of IoT technologies in containerization will become widespread in the coming years, a study to assess the level of research on the introduction of such technologies and implementation in the practical activities of transport enterprises is relevant. The aim of the proposed review is to determine the degree of IoT implementation in the container transportation industry, areas of research on the topic, and identify factors that may impede the predicted rapid development of IoT in containerization. The proposed study includes an analysis of scientific publications related to the use of the Internet of Things in the field of international container transportation, identifies the main priority areas of such publications, establishes the areas of current implementation of IoT technology and determines the prospects for its use. Since the solutions that can potentially be obtained with the help of IoT are quite heterogeneous, the literature analysis is organized by grouping such publications into the following areas: container monitoring and tracking, enhancing supply chain transparency and visibility, optimization of operational efficiency, security and risk management, environmental impact and sustainability, challenges and barriers. The paper provides examples of online platforms and applications currently offered by major container operators that are related to this technology.

Conceptualizing an Institutional Framework to Mitigate Crypto-Assets’ Operational Risk

Extent ecosystems of crypto financial assets (crypto-assets) lack parity and coherence across the globe. This asymmetry is further heightened with a knowledge gap in operational risk management, wherein the global landscape of crypto-assets is characterized by unprecedented external risks and internal vulnerabilities. In this study, we present a critical examination and comprehensive analysis of current crypto-asset operational guidelines across geographies. We benchmark these guidelines to the Basel Committee for Banking Supervision (BCBS) risk classification framework for crypto-assets, identifying gaps in the operations across organizations. We, hence, conceptualize a novel institutional framework which may help in understanding and mitigating the gaps in operational risks’ regulation of crypto-assets. Our proposed Crypto-asset Operational Risk Management (CORM) framework determines how operational risk associated with crypto-assets of financial institutions can be mitigated to respond to the increasing demand for crypto-assets, cross border payments, electronic money, and cryptocurrencies, across countries. Applicable to firms irrespective of their size and scale of operations, CORM aligns with global regulatory initiatives, facilitating compliance and fostering trust among stakeholders. Strengthening our argument of CORM’s applicability, we present its efficacy in the form of alternate hypothetical outcomes in two distinct real-life cases wherein crypto-asset exchanges succumbed to either external risks, such as hacking, or internal vulnerabilities. It paves the way for future regulatory response with a structured approach to addressing the unique operational risks associated with crypto-assets. The framework advocates for collaborative efforts among industry stakeholders, ensuring its adaptability to the rapidly evolving crypto landscape. It further contributes to the establishment of a more resilient and regulated financial ecosystem, inclusive of crypto-assets. By implementing CORM, institutions can navigate the complexities of crypto-assets while safeguarding their interests and promoting sustainable growth in the digital asset market.

Reasons for difficulties in isolating the causative organism during food-borne outbreak investigations using STEC as a model pathogen: a systematic review, 2000 to 2019.

IntroductionFood-borne disease outbreak investigations use epidemiological, microbiological and food chain evidence to identify the implicated food and inform risk management actions.AimsWe used Shiga toxin-producing Escherichia coli (STEC) as a model pathogen to investigate the success of outbreak strain isolation from food or environmental samples during outbreak investigations, and examined the factors influencing the chance of isolation.MethodsWe searched for reports of food-borne STEC outbreak investigations worldwide in peer-reviewed and grey literature in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.ResultsWe found a total of 223 outbreaks suitable for inclusion. Food and/or environmental samples were available for testing in 137 investigations, and the outbreak strain was isolated in 94 (42%) of investigations. We found no significant effect of STEC serovar or size of outbreak on likelihood of successful outbreak strain isolation. Isolation success ranged across different implicated commodities from 86% for beef-related outbreaks to 50% for salads and leafy greens. In 20% of outbreaks with samples available for testing, an additional STEC strain was isolated alongside the outbreak strain and in 6.6%, only an alternative STEC strain was isolated. Risk management action was taken on epidemiological evidence alone in 21 incidents.ConclusionThe principal reasons why the outbreak strain was not isolated were lack of sample availability and methodological issues concerned with laboratory isolation. We recommend strategies that could improve the likelihood of isolation including the rapid collection of samples based on epidemiological intelligence.

The Effectiveness of Operational Residual Risk Assessment: The Case of General Aviation Organizations in Enhancing Flight Safety in Alignment with Sustainability

Operational risk management (ORM) is crucial for every aviation organization. The assessment of operational risk (OR) is a critical area of study, as organizations must continuously evaluate and mitigate potential risks to maintain high levels of performance and safety. The motivation for writing this paper was to address the cognitive gap identified through literature analysis. The aim of this paper is to assess the effectiveness of operational residual risk assessment in general aviation (GA) organizations, with a specific focus on its role within the decision-making process to enhance flight safety in line with sustainability. By addressing a cognitive gap identified in the literature, this study seeks to determine whether current risk management practices adequately assess and mitigate residual risks, especially in organizations where operational risk is inherently high. Based on a literature review, the authors present adopted concepts of ORM and OR. The survey methodology involved a questionnaire on OR assessment, consisting of 32 questions completed by respondents twice—before and after 63 series of flights. The survey was carried out across two groups with significantly varying levels of flying experience (students and instructor pilots), with a particular focus on the influence of human factors. The conclusions are based on a comparative analysis of the difference in the results obtained after and before the series of flights in both surveyed groups. The survey was conducted in three selected general aviation organizations in Poland using nonprobability convenience sampling. The results demonstrate an overall significant underestimation of OR in both student and instructor groups. Therefore, it can be concluded that operational risk assessment in the selected organizations was not sufficiently effective. Additionally, it was shown that staff experience affected the effectiveness of OR assessment. Moreover, this study identified specific aspects of operational risk that were most underestimated. By addressing the cognitive gap, this study enhances both the theoretical and practical understanding of residual risk management, particularly in relation to safety and efficient resource use in aviation. It also offers the Operational Residual Risk Underestimation Index (ORRUI) as an actionable parameter developed to quantify and standardize the level of underestimation of operational residual risks in civil aviation.

Global HSE regulatory frameworks and their impact on operational efficiency in the energy sector

The global energy sector operates within a complex regulatory environment shaped by Health, Safety, and Environmental (HSE) frameworks that aim to protect both human health and the environment while enhancing operational efficiency. This study examines the key HSE regulatory frameworks implemented across various regions and their impact on operational practices in the energy sector. By analyzing regulations such as the European Union’s REACH (Registration, Evaluation, Authorisation, and Restriction of Chemicals) and the United States' OSHA (Occupational Safety and Health Administration) standards, alongside other national and international policies, the paper identifies the critical aspects of HSE regulations and their influence on risk management, safety protocols, environmental sustainability, and business performance. The findings highlight that while stringent HSE regulations contribute to reducing operational risks and enhancing corporate social responsibility, they may also increase compliance costs and operational complexities. The paper argues that a well-structured HSE framework can lead to improved long-term operational efficiency by reducing accidents, optimizing resource utilization, and enhancing sustainability practices. However, the balance between compliance and cost-effectiveness remains a significant challenge for energy companies operating in diverse regulatory environments. Recommendations are provided for harmonizing regulations and fostering innovation in compliance strategies to support sustainable development and enhanced operational efficiency.

Integrating AI in financial risk management: Evaluating the effects of machine learning algorithms on predictive accuracy and regulatory compliance

This research focuses on adopting ML models in risk management and how such factors influence predictive abilities and compliance with relevant rules. With more financial institutions using some of these advanced AI technologies in their decision-making capacities, a clear understanding of their effectiveness and what legal compliance would mean for their growth becomes vital. This research presents a comprehensive literature review of traditional risk management methods compared to the newer, AI-based methodologies by meticulously evaluating difficult standard measurements, including accuracy, precision, and recall. Further, the research analyses the compliance risks that arise with AI, especially concerning significant regulations such as Basel III and GDPR, which are essential in preserving financial stability and customer confidence. The study shows that applying AI approaches enhances predictive efficiency to a very high degree and the pressing and major legal concerns that institutions face. Moreover, the studies reveal the beneficial sectors for applying machine learning for operational risk management and provide guidelines for employing AI. To improve and strengthen risk management approaches and guarantee strict compliance with current and future implementing regulations, this study offers pertinent information to current discourses regarding the future of finance within the rising context of technological advancements.

Managing Risk in the Digital Era: A Generational Approach-Z on Personal Risk Management

Risk management should be applied not only at the corporate level but also on a personal level. As technology becomes increasingly integral to daily life, implementing personal risk management in digital activities warrants examination. This study explores personal risk management within the context of online shopping. It investigates factors influencing personal risk management, including privacy concerns, perceived security threats, and internet self-efficacy. The study focuses on individuals from Generation Z, the first generation to grow up in a fully digital environment. Data were collected through online questionnaires, yielding 972 responses, of which 466 were analyzed further. The data were processed using SEM-PLS. The findings indicate that privacy concerns, perceived threats, and internet self-efficacy directly impact personal risk management, which in turn directly influences purchase intentions. This research offers valuable insights for regulators in crafting digital security regulations, for individuals in evaluating and enhancing their personal risk management strategies, for online retailers in designing robust data security measures, and for researchers as a contribution to the limited literature on this topic.

Evaluating the Role of ISO Standards in Enhancing the Performance of Medical Laboratories

The role of ISO standards in enhancing the performance of medical laboratories has become increasingly significant in ensuring quality and reliability in healthcare services. This review evaluates the impact of ISO standards, particularly ISO 15189, on the operational efficiency, diagnostic accuracy, and risk management of medical laboratories. It highlights the key components of these standards, including quality management systems, personnel competence, and continuous improvement, and examines their contributions to patient safety and institutional credibility. The article also explores the challenges of implementing ISO standards, such as financial constraints and resistance to change, and proposes strategies to overcome these barriers. The findings underscore the importance of ISO standards in promoting a culture of quality and innovation within medical laboratories, ultimately improving healthcare outcomes.

I'm Not Feeling It: The Role of Affective Diversity in Risk Management and Team Performance

ABSTRACTTeam performance is contingent on nuanced approaches to risk management—demanding both risky and cautious strategic orientations. However, research surrounding how teams navigate this balance is limited. We argue that both positive and negative affective diversity can aid team performance, through affective diversity's impact on the team's risky and cautious behaviors. Furthermore, we argue that team trait regulatory focus strengthens these relationships. Using a controlled laboratory setting with 58 teams in a complex, uncertain team task that requires both risky and cautious strategies for successful performance, results indicate that positive affective diversity relates to team performance through promoting risky behavior, while negative affective diversity relates to team performance through promoting cautious behavior. Teams high in trait prevention‐focus are more attuned to the information signals in teams with negative affective diversity, but we did not find that promotion focus impacted outcomes of positive affective diversity.

Credit Risk Management and Bank Performance

Risk is indispensable part of the banks. Bank performance is affected with the credit risk. The objective of the study is to analysis impact of credit risk on bank performance. The study uses secondary data to analyses the performance for 5 years. Different ratios are used to analyses performance of the banks. The findings show that credit risk is the one of the most important factor affecting performance of the bank. Notably, policy maker should be aware of the issue and take strategic decision before making investment.

Evaluating the Impact of Technological Innovations on Operational Risk Management in Financial Institutions

This study evaluates the impact of technological innovations on operational risk management in financial institutions, focusing on how emerging technologies influence risk identification, mitigation, and management processes. Employing a qualitative approach through literature review and library research, this study synthesizes recent findings on the integration of technologies such as artificial intelligence (AI), blockchain, big data analytics, and cloud computing within financial risk frameworks. Findings indicate that these technologies offer substantial improvements in risk management by enhancing accuracy in risk detection, increasing response speed, and reducing human error. AI and machine learning models, for instance, are shown to enable real-time monitoring and predictive analytics, allowing institutions to identify potential risks before they materialize. Blockchain technology improves transparency and security in transaction processing, thereby mitigating fraud-related risks. Big data analytics provides insights into customer behavior, which can help detect anomalous activities and improve decision-making. However, the study also highlights challenges, including the need for robust cybersecurity measures, potential regulatory gaps, and skill shortages in handling complex technological systems. This study provides insights for financial institutions aiming to balance technological integration with effective risk management, underscoring the need for comprehensive frameworks that align technological advancements with regulatory compliance and organizational capability. Future research should focus on empirical studies assessing the long-term implications of these technologies on risk management efficacy in diverse financial settings.

Effective Internal Control Towards Business Sustainability of a Selected Company in Shenzhen, China

In the vibrant and innovative landscape of Shenzhen, China, a certain company has achieved long-term sustainable business development through a series of efficient and rigorous internal control mechanisms, thereby setting a benchmark within the industry. As a pioneer of China's reform and opening-up, Shenzhen's business environment is marked by intense competition and rapid change, which imposes high demands on a company's adaptability and flexibility. The internal controls of this company not only address financial and operational risk management but also delve into the shaping of corporate culture and the fulfillment of social responsibilities. By constructing a comprehensive risk management system, optimizing internal processes, and enhancing information communication, the company has not only weathered market uncertainties but also progressively established a solid brand trust and market competitiveness. The effective implementation of internal controls has enabled the company to pursue economic benefits while achieving harmonious development in environmental, social, and governance (ESG) aspects, forming a unique sustainable business model. This model not only helps the company maintain a leading position in the rapidly changing market but also provides valuable experience and reference for other enterprises.

Ground Deformation and Damage Assessment using SAR Observations: A Case Study of Hinatuan, Philippines in the 2023 Surigao Del Sur Earthquake

Abstract. Earthquakes are among the major hazards that lead to economic loss every year. Rapid damage assessment is essential for a more efficient disaster response. The 2023 Surigao del Sur earthquake in the Philippines with moment magnitude (Mw) 7.4 occurred on December 2, 2023, with Hinatuan as the nearest municipality located 12 km south of the epicenter. Thus, this study examined the co-seismic impacts in Hinatuan using Synthetic Aperture Radar (SAR) observations. Using phase interferometry and displacement maps to estimate the ground surface deformation, results show that the phase interferograms, Line-of-sight (LOS) displacements, and vertical displacements were consistent, with most of Hinatuan experiencing an uplift of up to 7.2 cm. In contrast, subsidence as low as –9.0 cm was observed in some isolated areas. The damage assessment conducted through change detection analysis revealed 6.15 ha (6.4%) of built area out of the total 84 ha was significantly damaged. The damage mainly occurred in the uplifted regions between 0 to 5 cm. Building codes, land-use planning, and risk management and assessment can be improved and strengthened with these findings for a more earthquake-resilient community. The findings will be a basis for disaster risk reduction and management actions. These may, furthermore, serve as a reference for the development planning of local government units, especially for urban and built-up areas. These can also be used in developing Information, Education, and Communication (IEC) materials and advisory for residents in Hinatuan and the vulnerable adjacent regions.

Risk Management As A Determinant Of Indonesian Banking Financial Performance: A Systematic Literature Approach

This study aims to understand how risk management affects financial performance in the Indonesian banking sector. In a business environment full of uncertainty, especially in the banking sector, risk management is key to ensuring financial stability. Systematic Literature This review (SLR) analyzes the findings of articles published between 2016 and 2022, focusing on the main risks faced by banks: credit risk, market risk, liquidity risk, and operational risk. The selected articles were obtained from leading journal sources in the fields of economics and business. The literature selection process includes the stages of identification, screening, and thematic analysis to identify trends and correlations between risk management and financial performance indicators such as Return on Assets (ROA) and Return on Equity (ROE). The results of the study indicate that credit risk and operational risk have the most significant impact on financial performance, while market and liquidity risks show varying effects depending on the market situation and internal conditions of the bank. These findings underline the importance of a proactive approach to risk management, including the implementation of integrated risk mitigation policies and the use of effective internal controls. Thus, risk management not only serves as a safeguard against potential losses but also as a support for business sustainability. This study recommends further research to explore new risks such as cyber threats and regulatory changes, which are increasingly relevant in the context of the modern banking industry. These results are expected to provide insights for financial practitioners and banking leaders in improving the resilience and financial performance of their companies.

Risk Management Strategies and Performance of Selected Insurance Companies in Nairobi City County, Kenya

The insurance industry plays a vital role in the management of risk and therefore helps to support and facilitate business activities. The performance of insurance companies is impacted by various challenges related to their risk management strategies. These challenges can arise from both internal and external factors, and they can have significant implications for the financial stability and profitability of insurance companies. Changes in regulatory requirements can impact the risk management strategies of insurance companies, requiring them to adapt their practices and systems to remain compliant. Therefore, this study seeks to investigate the influence of risk management strategies on the performance of selected insurance companies in Nairobi City County, Kenya. The study was guided by the balanced scorecard model, agency theory, portfolio theory, risk aversion theory, and prospect theory. A descriptive research design was employed. The study targeted 95 respondents, comprising 10 senior-level managers, 30 middle-level managers, and 55 departmental heads from the insurance companies operating in Kenya. A census of 95 respondents was conducted. The study used a structured questionnaire. A pilot group of 9 individuals was selected from the target population. Content validity was applied to the study. Cronbach’s Alpha coefficient was computed for all components of the questionnaire, and their assessment was provided. Descriptive analysis was computed using mean, frequencies, and percentages. Regression analysis tested the relationship between the study variables. The regression model assessed the relationship between the independent variables and the dependent variable. The findings were presented using tables and figures. Through regression analysis with a linear model result showed a strong relationship between risk management strategies and performance. The resulting value of regression coefficient at .000 (p<0.05) indicated existence of relationships that were relatively strong. The study thus concluded that performance of insurance companies is dependent on the careful choice or selection of risk management strategies. It is expected the results will benefit various stakeholders, including the government policy makers, Insurance sector players, and academia. Further studies exploring more strategies to manage risks in other entities including other sectors such as the finance sector could be undertaken by scholars.

A Data Assimilation-Based Method for Real-Time Monitoring and Estimation of Gas Influx Size and Distribution During Gas Migration in a Marine Drilling Riser

Effective well control is essential in marine drilling operations to prevent catastrophic blowouts that endanger human lives and cause severe environmental damage, including long-lasting impacts on marine ecosystems. Accurate real-time monitoring and management of well conditions after taking gas influxes are critical for maintaining safety and environmental protection during offshore drilling operations.When a gas influx becomes trapped in a closed marine drilling riser, its upward migration can result in excessively high surface pressure, presenting significant risks to offshore drilling and well control. Therefore, the accurate estimation of downhole gas influx size and distribution during gas migration events is crucial for effectively managing these situations. The complexities of wellbore two-phase flow and gas migration make direct measurements challenging, leading to potential inaccuracies in traditional modeling approaches. This study introduces a Data Assimilation (DA) technique, employing the Ensemble Kalman Filter (EnKF), to improve the real-time estimation of gas influx rates and distribution, thereby enhancing the accuracy of two-phase flow models in marine drilling.This research utilizes full-scale gas influx migration experiments conducted at Louisiana State University, where gas was injected from the bottom of an experimental well to simulate a riser gas event in a Water-based Mud (WBM) system. Key real-time measurements, including downhole pressure gauges at multiple depths and Distributed Acoustic Sensing (DAS) data, were employed to validate the estimated gas influx size and distribution within the riser using the EnKF. The overall gas influx distribution was captured through the real-time estimation of a dimensionless distribution index (DI), offering additional insights into the spatial characteristics of the migrating gas. Additionally, a Drift Flux Model (DFM) calibrated online through DA was used to predict flow parameters such as gas void fraction profiles within the riser during migration. The validation of these predictions demonstrated a strong correlation between the estimated and measured values.The outcomes of this study underscore the effectiveness of the proposed method in estimating parameters that are otherwise difficult to measure directly, thereby improving the predictive accuracy of gas influx behavior in marine drilling risers. This method offers significant practical value by enhancing real-time decision-making and risk management in marine drilling operations that involve gas migration, contributing to the broader goals of offshore drilling safety and marine environment protection.

Innovative clearance data model for demining operational data collection: Insights from field trials in Zimbabwe

From September 2023 to March 2024 a field trial on a live manual demining site was conducted to test a new and innovative approach for the collection and analysis of operational data. The approach, titled the Clearance Data Model, involved the collection of sixty-six data attributes for each mine found. For the first time the mine itself would become the accountable unit of demining data, against which an expanded range of relevant attributes particular to that specific mine would be recorded. This novel approach represented a considerable expansion to the operational data collected concerning Victim Operated Explosive Devices such as mines, booby-traps and victim operated Improvised Explosive Devices from the field. Previously few if any details about individual accountable mines were collected. The trial proved that is it entirely practical to collect such levels of data without impeding operational efficiency. It also showed that such data has significant benefits for quantitative operational risk management, as well as overall operations and quality management. For example, the recording of mine depth alongside excavation times enables oversight of individual excavation speed and management of any risk identified.

ESG Risk and Audit Firm Reputation

Purpose: The importance of ESG continues to grow day by day, and ESG risk management has become crucial for corporate sustainability. Understanding ESG risk management is an urgent and crucial issue that cannot be delayed any longer. This study aims to examine the relationship between ESG risk management and audit firms’ reputation. Design/methodology/approach: This study investigates the correlation between the reputational effect of audit firms and ESG risk management, using companies listed on the TWSE and the TPEx in 2023 as the target population. We further develop two research models: first, a regression model (1) to examine whether the brand reputation effects of Big4 and non-Big4 audit firms are associated with corporate ESG risk management scores and set up an Ordered Probit model (2) to investigate how the reputation effect of Big4 and non-Big4 audit firms is related to corporate ESG risk ratings. Finding: The empirical results show that companies audited by the Big 4 audit firms have better ESG risk management performance than those audited by non-Big 4 audit firms, and that companies’ ESG risk management performance varies depending on the specific Big 4 audit firm engaged. Furthermore, the association between ESG risk management performance and the reputation effect of audit firms depends on the firm’s business model and corporate governance structure. The family-owned business model and strong corporate governance environment synergistically enhance the reputation effect of audit firms, thereby contributing to the improvement of ESG risk management performance. Finally, the choice of earnings management strategy affects the relationship between ESG risk management performance and the reputation effect of audit firms. Risk-averse companies that adopt conservative earnings management strategies benefit from the positive impact of the Big 4 audit firm reputation effect on ESG risk management performance. Research limitations/implications: The research limitations of this study stem from the difficulty in accessing ESG information, which constrains the sample size. Originality/value: First, this study provides a comprehensive examination of the ESG risk management performance of listed companies in Taiwan, contributing to a deeper understanding of the current status of ESG strategy development and implementation among Taiwanese companies. Second, by examining corporate ESG risk management, the study explores the impact of audit firms’ reputation on corporate ESG risk management performance. Third, our findings contribute to academic research on ESG issues by incorporating the potential impact of audit firms’ reputation into the analysis.

Applying FMEA for Operational Risk Management: Lessons from Minestar Implementation at PT. Borneo Indobara

PT Borneo Indobara (BIB) is planning to implement Minestar, an integrated mining management system, in 2025 to enhance operational efficiency and safety. However, the implementation of this system poses several operational risks that require careful management to ensure success. The aim of this research is to develop a comprehensive risk matrix and propose effective mitigation strategies for the Minestar implementation at BIB, using the SNI ISO 31000:2018 risk management framework. The research employs a mixed-method approach, combining qualitative techniques such as semi-structured interviews and focus group discussions (FGD) with quantitative analysis using Failure Mode and Effect Analysis (FMEA). Data was collected from key stakeholders directly involved in the Minestar project to assess the severity, occurrence, and detection of each identified risk, which were then used to develop a risk matrix. The results of the study identified and prioritized several critical operational risks, with a three-dimensional risk matrix providing a clear visualization of their severity, occurrence, and detection levels. This structured approach allows BIB's management to prioritize risks and allocate resources effectively for risk mitigation. The findings of this research contribute to operational risk management in the mining industry, particularly for the implementation of advanced technologies like Minestar. The practical insights provided can serve as a reference for similar projects in the industry, helping organizations to address operational challenges proactively.