Effective risk management is crucial for organizational success across various sectors, impacting supply chains, software development, public-private partnerships, pharmaceuticals, and project management. Risk identification, the initial step in risk assessment, is paramount. Existing approaches are often complex, subjective, and require multiple skilled individuals, failing to uncover hidden risks. This study aims to determine which risk identification method (business process or work breakdown structure) is more effective in identifying a greater number of risks, while controlling for the knowledge of the individuals performing the risk identification. The importance of identifying hidden risks, which often lead to significant organizational losses, is highlighted.

The researchers reviewed literature on risk management and risk identification, noting the complexity and subjectivity of existing methods. They highlight the need for practical, less complex approaches that can be performed by a single individual. The business process approach and the work breakdown structure (WBS) approach are presented as potential solutions, referencing previous studies that utilized similar, yet not identical methodologies, in areas such as quality control, hazard analysis, and project management. The paper acknowledges variations in the execution of these approaches and proposes refined procedures for both.

This study employed an experimental design. Eighty-six business students from a top Indonesian university were randomly assigned to three groups: a placebo group (no training), a business process (BP) group, and a work breakdown structure (WBS) group. Each group received a case study about an accounting department and was tasked with identifying as many risks as possible. The BP and WBS groups received training on their respective methods before completing the case study. A multiple-choice questionnaire on accounting assessed the participants' knowledge of the context. One-way analysis of covariance (ANCOVA), controlling for accounting knowledge, was used to compare the number of risks identified by each group. Tukey's HSD post-hoc test further analyzed the significant differences. The researchers ensured that no outliers or missing data affected the analysis.

The ANCOVA revealed a statistically significant difference (F(2, 35.69) = 12.72, p < 0.05) in the number of risks identified across the three groups, showing that the choice of risk identification method significantly affects the outcome. Accounting knowledge also significantly affected the number of risks identified (F(1, 45.79) = 16.32, p < 0.05). Tukey's HSD post-hoc test indicated that the BP approach identified significantly more risks than both the WBS approach (p < 0.05) and the placebo group (p < 0.05). The WBS approach did not significantly outperform the placebo group (p = 0.34). The mean number of risks identified was 4.93 for the BP group, 3.14 for the WBS group, and 2.46 for the placebo group. The effect sizes for both the risk identification method and accounting knowledge were large, suggesting the sample size was adequate to detect these effects. The BP method identified, on average, approximately 1.57 times more risks than the WBS method and 2.00 times more risks than the control group.

The results support the hypothesis that the choice of risk identification method impacts the number of identified risks, even when contextual knowledge is controlled. The BP approach proved superior, likely due to its systematic, step-by-step procedure that guides users through the process of identifying potential loss events within each activity of a business process. This contrasts with the top-down approach of WBS which may not be as effective in uncovering hidden risks. These findings are consistent with prior research indicating the impact of contextual knowledge on risk identification. The practical implication of this study is that organizations should utilize the business process approach to improve the effectiveness of their risk identification process.

This study demonstrates that the business process approach to risk identification is superior to the work breakdown structure approach in identifying a greater number of risks, notably those that might be hidden or overlooked. The structured nature of the business process approach seems to be more effective in revealing potential risks than the more top-down approach of WBS. Future research could explore the applicability of these approaches across different organizational contexts and industries, and compare these methods with other risk identification techniques.

The study used a sample of business students rather than experienced professionals in organizational settings. While this allowed for control of contextual knowledge, it limits the generalizability of findings to real-world organizational contexts. The focus on two specific risk identification methods limits the scope; future research should compare more approaches. The case study used focused on the accounting department; future research should test the generalizability across different departments and organizations.