Performance Measures For Supply Chain Management

32performance Measures For Supply Chain Managementassignment Case

Evaluate the company's supply chain performance by analyzing shipping, warehouse costs, and financial data. Calculate cost per unit shipped for each warehouse in 2018 and 2019, identify the best and worst performers, assess percentage differences, and recommend which warehouse to close. Complete a Strategic Profit Model based on provided income statement and balance sheet to illustrate overall financial health. Analyze the impact on Return on Assets (ROA) if transportation costs are reduced by 10%, and produce an updated Strategic Profit Model reflecting this change.

Paper For Above instruction

Assessing supply chain efficiency involves analyzing multiple financial and operational metrics to identify areas for improvement and strategic decision-making. This report delves into the performance of various warehouses in a manufacturing firm by calculating cost per unit shipped over two years, identifying the top and bottom performers, and offering recommendations based on these findings. Additionally, a comprehensive Strategic Profit Model is developed to contextualize the company's financial health, followed by an analysis of how cost reduction strategies could impact key financial ratios, particularly Return on Assets (ROA).

Introduction

Effective supply chain management (SCM) is vital to maintaining a competitive advantage for manufacturing firms like Widget Company. An efficient SCM system reduces costs, enhances customer satisfaction, and bolsters profitability. This report leverages financial data from 2018 and 2019, including shipping, warehouse costs, income statements, and balance sheets, to analyze warehouse performance and overall company health. By focusing on cost per unit shipped and their percentage differences, the analysis provides insight into operational efficiencies and strategic directions.

Cost per Unit Shipped Analysis

The calculation of cost per unit shipped provides a granular view of warehouse efficiency. For 2018, the cost per unit for each warehouse was computed by dividing warehouse costs by units shipped:

  • Chicago: $156,562 / 16,540 ≈ $9.46 per unit
  • New York: $63,562 / 7,562 ≈ $8.41 per unit
  • Atlanta: $246,263 / 27,506 ≈ $8.95 per unit
  • Denver: $151,585 / 15,685 ≈ $9.66 per unit
  • Tampa: $150,562 / 15,621 ≈ $9.63 per unit
  • San Antonio: $136,563 / 12,658 ≈ $10.80 per unit
  • Bakersfield: $72,125 / 9,526 ≈ $7.58 per unit
  • Seattle: $119,956 / 11,526 ≈ $10.41 per unit

In 2018, Bakersfield had the lowest cost per unit ($7.58), indicating high efficiency, while San Antonio had the highest ($10.80). For 2019, the costs were:

  • Chicago: $178,000 / 17,800 ≈ $10.00 per unit
  • New York: $65,263 / 7,562 ≈ $8.63 per unit
  • Atlanta: $265,856 / 26,585 ≈ $10.00 per unit
  • Denver: $176,000 / 15,685 ≈ $11.22 per unit
  • Tampa: $152,365 / 15,621 ≈ $9.75 per unit
  • San Antonio: $145,256 / 12,658 ≈ $11.48 per unit
  • Bakersfield: $78,526 / 9,526 ≈ $8.25 per unit
  • Seattle: $120,636 / 11,526 ≈ $10.47 per unit

The analysis shows Bakersfield again maintained the lowest cost per unit ($8.25), while San Antonio was the most costly ($11.48). The increases in costs per unit highlight areas requiring efficiency improvements.

Performance Comparison: Best and Worst Warehouses

The warehouses with the best performance in 2018 and 2019 were Bakersfield, based on lowest cost per unit. Conversely, San Antonio exhibited the worst performance. The percentage change in cost per unit indicates varying efficiencies:

  • Chicago: ((10.00 - 9.46)/9.46) * 100 ≈ 5.6% increase
  • New York: ((8.63 - 8.41)/8.41) * 100 ≈ 2.6% increase
  • Atlanta: ((10.00 - 8.95)/8.95) * 100 ≈ 11.7% increase
  • Denver: ((11.22 - 9.66)/9.66) * 100 ≈ 16.2% increase
  • Tampa: ((9.75 - 9.63)/9.63) * 100 ≈ 1.3% increase
  • San Antonio: ((11.48 - 10.80)/10.80) * 100 ≈ 6.3% increase
  • Bakersfield: ((8.25 - 7.58)/7.58) * 100 ≈ 8.9% increase
  • Seattle: ((10.47 - 10.41)/10.41) * 100 ≈ 0.6% increase

While most warehouses experienced cost increases, Bakersfield maintained low costs, underscoring its operational efficiency.

Warehouse Closure Recommendation

Based on the analyzed performance metrics, the warehouse in San Antonio consistently had the highest cost per unit and the greatest percentage increase, indicating poor efficiency. Given the company's goal to optimize expenses, it is recommended to close the San Antonio warehouse. This decision would redirect resources towards more cost-effective operations, aligning with strategic supply chain management principles.

Strategic Profit Model Analysis

The Strategic Profit Model (SPM) offers a comprehensive view of the company's financial health by relating assets, profitability, and efficiency. Calculations include:

  • Total Expenses = Operating costs + Interest + Taxes = $2,317,915 + $111,000 + $72,000 = $2,500,915
  • Net Profit Margin = Net Income / Sales = $532,008 / $3,958,555 ≈ 13.4%
  • Return on Assets (ROA) = Net Income / Total Assets = $532,008 / $3,486,806 ≈ 15.3%

These ratios suggest the company is moderately profitable, with efficient asset utilization. The high current assets, particularly inventory and receivables, indicate areas for further optimization.

Impact of 10% Reduction in Transportation Costs

A 10% reduction in transportation costs would decrease expenses by $65,856 (10% of $658,562). Adjusted expenses would be:

  • Total Expenses = $2,500,915 - $65,856 = $2,435,059

Recalculating net profit:

  • New Net Income = Original Net Income + Savings from cost reduction = $532,008 + $65,856 = $597,864

Revised ROA:

  • ROA = $597,864 / $3,486,806 ≈ 17.1%

This demonstrates a significant improvement in asset efficiency, emphasizing the importance of cost control strategies.

Conclusion

Through detailed analysis of warehouse performances and financial ratios, it is evident that operational efficiencies directly influence profitability and strategic decision-making. Closing the underperforming warehouse (San Antonio) and reducing transportation costs could substantially improve financial outcomes. Implementing such measures aligns with best practices in supply chain management, fostering sustained competitive advantage.

References

  • Chopra, S., & Meindl, P. (2016). Supply Chain Management: Strategy, Planning, and Operation. Pearson.
  • Christopher, M. (2016). Logistics & Supply Chain Management. Pearson UK.
  • Harrison, A., & Van Hoek, R. (2014). Logistics Management and Strategy. Pearson.
  • Simchi-Levi, D., Kaminsky, P., & Simchi-Levi, E. (2008). Designing and Managing the Supply Chain. McGraw-Hill.
  • Waters, D. (2014). Supply Chain Risk Management: Vulnerability and Resilience in Logistics. Kogan Page.
  • Slack, N., Brandon-Jones, A., & Burgess, N. (2018). Operations Management. Pearson.
  • Mentzer, J. T., et al. (2001). Defining Supply Chain Management. Journal of Business Logistics, 22(2), 1–25.
  • Lysons, K., & Farrington, B. (2012). Purchasing and Supply Chain Management. Pearson.
  • Mentzer, J. T., & Moon, M. (2004). Understanding demand management. Supply Chain Management Review.
  • Olson, D. L., & Wu, D. (2018). Supply Chain Management Best Practices. CRC Press.

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