Managerial Accounting Case study - Group 7

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York University *

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MISC

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Management

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Apr 3, 2024

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Uploaded by harisingh3700

Introduction to Managerial Accounting Group 7 Javed Aqib - 220828679 Bina Baral - 220402780 Santhoshini Roopa Munaganuri - 220109534 Hari Singh - 20227625 Arati Sunar - 220700787

Table of Contents Executive summary Case Identification – Issues Analysis Alternatives Implementation Recommendation Executive summary Major Electronics, a multi-plant assembler of computer products, is grappling with challenges in its traditional manufacturing overhead (MOH) allocation method. With a changing cost structure and uncertainties in cost drivers, the company faces two primary concerns: the interpretation of regression analysis results and the allocation of underutilized capacity costs. The analysis revealed that correlation coefficients, while insightful, have limitations in providing a comprehensive understanding of the relationships between cost drivers and MOH. Factors like causation, confounding variables, non-linear relationships, and omitted variables bias necessitate a cautious interpretation of correlation results. To address the underutilized capacity issue, we recommend transitioning to an Activity-Based Costing (ABC) system. This approach involves identifying specific cost drivers for each MOH sub-classification based on activities. This solution aims to enhance accuracy in cost allocation, improve resource efficiency, and provide a nuanced understanding of product profitability. The implementation of ABC comes with both advantages and challenges. While it offers improved cost accuracy, better resource allocation, and enhanced decision-making, it requires careful consideration of complexities, potential resistance to change, and the need for accurate and detailed data. To align strategic objectives and performance indicators, we propose a Balanced Scorecard encompassing financial, customer, internal business processes, and learning and growth perspectives. This framework will guide Major Electronics in monitoring key performance indicators across different dimensions, allowing for adaptability based on evolving organizational needs. In summary, Major Electronics is advised to approach cost allocation with a nuanced understanding of correlation analysis limitations and consider transitioning to an ABC system for more accurate and informed decision-making. The Balanced Scorecard offers a comprehensive framework to align strategic objectives and monitor performance across crucial perspectives.

Case Identification – Issues Two primary concerns have emerged from the committee's deliberations: 1. Interpretation of Regression Analysis: There is a lack of clarity on how positive correlation coefficients imply a relationship between cost drivers and MOH. 2. Allocation of Underutilized Capacity Costs: Some overhead costs relate to capacities greater than current production needs, leading to inefficiencies and potential unfairness in the allocation process. Analysis Major Electronics, a multi-plant assembler of computer products, is facing challenges with its traditional manufacturing overhead (MOH) allocation method. The evolving cost structure, characterized by a decline in direct labor costs and an increase in direct materials and MOH costs, necessitates a review and revision of the existing MOH allocation process. Current MOH Structure and Analysis The MOH at Major Electronics is divided into three main groups: procurement, production, and support, each with further sub-classifications. A survey conducted across 40 plants identified significant cost drivers for MOH, and an analysis was performed to determine their correlation coefficients with MOH and its subcategories. This analysis revealed no uniform pattern across the plants, indicating the need for a tailored approach to MOH allocation. Alternatives Solving Issue #1 Quantitative Approach Analyzing the relationship of Cost drivers with MOH Total Manufacturing Space: Positive Relationship with Total MOH (0.57): There is a strong positive correlation between the total manufacturing space and total MOH. This suggests that as the manufacturing space increases, the total MOH also tends to increase. Average Total Head-Count in Manufacturing:

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Positive Relationship with Total MOH (0.86): There is a very strong positive correlation between the average total head-count in manufacturing and total MOH. This indicates that as the number of employees in manufacturing increases, the total MOH also increases significantly. Direct Labour Dollars: Positive Relationship with Total MOH (0.73): There is a strong positive correlation between direct labor dollars and total MOH. This implies that as the direct labor costs increase, the total MOH tends to increase. Direct Material Dollars: Negative Relationship with Total MOH (-0.17): There is a weak negative correlation between direct material dollars and total MOH. This suggests that as direct material costs increase, the total MOH may decrease slightly, although the correlation is not very strong. Number of Part Numbers: Positive Relationship with Total MOH (0.13): There is a weak positive correlation between the number of part numbers and total MOH. This indicates that as the number of part numbers increases, the total MOH also slightly increases. Percent of Parts Inspected on Receipt: No Significant Relationship with Total MOH (0): There is no correlation (0 correlation coefficient) between the percent of parts inspected on receipt and total MOH. The two variables do not show a linear relationship. Number of Products: Positive Relationship with Total MOH (0.53): There is a strong positive correlation between the number of products and total MOH. This implies that as the variety of products increases, the total MOH also tends to increase. Number of Customer Orders per Month: Negative Relationship with Total MOH (-0.05): There is a very weak negative correlation between the number of customer orders per month and total MOH. This suggests a minimal decrease in total MOH as the number of customer orders increases. Average Cycle Time in Days: Positive Relationship with Total MOH (0.10): There is a weak positive correlation between the average cycle time in days and total MOH. This indicates that as the average cycle time increases, the total MOH also slightly increases.

Reason why above correlation analysis is not effective Correlation coefficients reveal linear relationships but don't imply causation or provide a comprehensive view. Limitations include confounding variables, unclear causation direction, neglect of non-linear relationships, sensitivity to outliers, and potential bias in small sample sizes. Correlation might oversimplify complex relationships, assumes homogeneity, and lacks consideration for temporal sequences. Understanding these limitations is crucial to avoid misinterpretations in data analysis:  Correlation Does Not Imply Causation: Correlation coefficients indicate the strength and direction of a linear relationship between two variables but do not establish a cause- and-effect relationship. The observed correlations might be influenced by unaccounted factors in the analysis.  Confounding Variables: There may be confounding variables that affect both the cost drivers and the manufacturing overhead, leading to a spurious correlation. Without considering all potential variables, the observed correlations may be misleading.  Non-Linear Relationships: Correlation coefficients assume a linear relationship, and they might not capture non-linear relationships between variables. Real-world relationships can be intricate, extending beyond the accuracy of a linear model.  Omitted Variable Bias: If important variables are omitted from the analysis, the correlations observed may be biased. Omitted variable bias can lead to incorrect interpretations of the relationships between the variables.  Lack of Time Dimension: Correlation coefficients do not account for changes over time. Manufacturing processes and costs may evolve, and a static correlation analysis might not capture these dynamics.  Specific to the Data Set: Correlation coefficients are specific to the dataset at hand. They may not generalize well to different conditions or time periods.  Small Sample Size: The reliability of correlation coefficients increases with larger sample sizes. If the dataset is small, the observed correlations may be less reliable indicators of the true relationships.  Variable Measurement Issues: If the variables are not measured accurately or consistently across all plants, it can introduce measurement errors that affect the reliability of the correlations. Solving Issue #2 In order to solve the second issue of the case study Major Electronics needs to transition from traditional approach to a new alternative cost approach. Our suggestion: Activity-based Cost (ABC) system

To conduct an Activity-Based Costing (ABC) approach, you need to identify cost drivers that have a significant impact on the consumption of resources and the incurrence of costs in each activity. Here are suggested cost drivers based on Exhibit 1 for each sub-classification of Manufacturing Overhead Costs: Procurement: Cost Driver Cost Driver Description Rationale Stores Number of Purchase Orders The more purchase orders, the higher the costs associated with storing and managing inventory. Purchasing Number of Suppliers The diversity of suppliers may impact the complexity of the purchasing process and associated costs Materials Material Types/Components Different types of materials may have varying costs and procurement complexities. Engineering Number of Design Changes Changes in design may lead to additional engineering efforts and costs. Production: Cost Driver Cost Driver Description Rationale Direct Labor Payroll Taxes and Benefits Direct Labor Hours The number of direct labor hours may influence payroll taxes and benefits costs. Occupancy Square Footage of Occupied Space Occupied space may impact occupancy costs. Direct Labor Supervision Number of Direct Labor Employees The number of direct labor employees may affect supervision costs Other Indirect Labor Number of Production Shifts Multiple production shifts may impact other indirect labor costs Support: Cost Driver Cost Driver Description Rationale Production Engineering Number of Engineering Change Orders Changes in engineering may impact production engineering costs Process Engineering Number of Process Changes Changes in processes may influence process engineering costs Manufacturing Management Number of Production Meetings The frequency of production meetings may impact manufacturing management costs Quality Assurance Percentage of Defective Products The level of quality assurance required may vary based on the percentage of defective products.

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Implementation Qualitative Approach Understanding effectiveness of ABC costing in terms of implementation Pros and Cons of Using ABC Cost Approach: Pros:  Cost Accuracy: ABC provides a more accurate reflection of actual costs by tracing indirect costs to specific activities and products.  Resource Allocation: It facilitates better allocation of resources by identifying the true drivers of costs, enabling more informed decision-making.  Product Profitability Analysis: ABC allows for a more precise analysis of the profitability of individual products or services.  Efficiency Improvement: It highlights areas of inefficiency and provides insights for process improvements.  Enhanced Decision-Making: Managers can make more informed decisions based on a better understanding of the cost structure. Cons:  Complexity and Cost: Implementing ABC can be complex and costly, requiring significant time and resources.  Subjectivity: Assigning costs to activities involves subjective judgment, and different individuals may have different views on cost allocation.  Data Intensity: ABC relies on detailed and accurate data and obtaining this data can be challenging.  Resistance to Change: Employees and management may resist the shift from traditional costing methods to ABC.  Not Universally Applicable: ABC may not be suitable for all industries or companies, and its benefits may vary depending on the context.  Continuous Maintenance: The system requires continuous maintenance to ensure ongoing accuracy, and changes in the organization may necessitate updates to the ABC system.

Recommendation This Balanced Scorecard provides a framework for Major Electronics to align its strategic objectives with key performance indicators across different perspectives, fostering a comprehensive approach to performance management. Adjustments and refinements can be made based on the evolving needs and insights of the organization . Financial Perspective: Objective: Ensure Cost Efficiency and Profitability Key Performance Indicators (KPIs):  Total Manufacturing Cost  Profit Margins  Return on Investment (ROI) Custom Objec Satisfa Key P    Internal Business Processes Perspective: Objective: Improve Efficiency and Effectiveness in Manufacturing Processes Key Performance Indicators (KPIs):  Cycle Time Reduction  Production Yield  Utilization of Manufacturing Space Learn Objec Adapta Key P    References Costing Methods: Types of Costing in Cost Accounting. (n.d.). Katana. https://katanamrp.com/costing-methods/ Kenton, W. (2023, March 7). Activity-Based Costing (ABC). Investopedia. https://www.investopedia.com/terms/a/abc.asp#:~:text=Key%20Takeaways

Kaplan, R. S., & Norton, D. P. (1992, January). The Balanced Scorecard—Measures that Drive Performance. Harvard Business Review; https://hbr.org/1992/01/the-balanced-scorecard-measures-that-drive-performance-2

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