ISM Supply Management Integration Exam Questions

Standardization ensures that products meet uniform quality standards, reducing variability and enhancing customer satisfaction. This advantage is vital in maintaining brand reputation and streamlining production processes.

To calculate the Mean Absolute Percentage Error (MAPE), we follow these steps:

1. Find the absolute error for each month.

2. Convert the absolute error to a percentage of the actual demand for each month.

3. Find the average of these percentage errors over the six-month period.

Here's the calculation:

* January: 100,00080,000100,000100=20%\left| \frac{100,000 - 80,000}{100,000} \right| \times 100 = 20\%100,000100,00080,000100=20%

* February: 105,00090,000105,000100=14.29%\left| \frac{105,000 - 90,000}{105,000} \right| \times 100 = 14.29\%105,000105,00090,000100=14.29%

* March: 110,000100,000110,000100=9.09%\left| \frac{110,000 - 100,000}{110,000} \right| \times 100 = 9.09\%110,000110,000100,000100=9.09%

* April: 70,000100,00070,000100=42.86%\left| \frac{70,000 - 100,000}{70,000} \right| \times 100 = 42.86\%70,00070,000100,000100=42.86%

* May: 90,000110,00090,000100=22.22%\left| \frac{90,000 - 110,000}{90,000} \right| \times 100 = 22.22\%90,00090,000110,000100=22.22%

* June: 100,00090,000100,000100=10%\left| \frac{100,000 - 90,000}{100,000} \right| \times 100 = 10\%100,000100,00090,000100=10%

MAPE=(20+14.29+9.09+42.86+22.22+10)6=19.41%20%MAPE = \frac{(20 + 14.29 + 9.09 + 42.86 + 22.22 + 10)}{6} = 19.41\% \approx 20\%MAPE=6(20+14.29+9.09+42.86+22.22+10)=19.41%20%

Thus, the MAPE for the six months of data is approximately 20%. Reference:

* Chase, R. B., Jacobs, F. R., & Aquilano, N. J. (2006). Operations Management for Compet-itive Advantage. McGraw-Hill/Irwin.

* Hyndman, R. J., & Athanasopoulos, G. (2018). Forecasting: principles and practice. OTexts.

In a highly competitive market like office supplies, the most critical cost associated with shortag-es is typically lost sales. If PQR, Inc. experiences shipping delays and cannot maintain continuous inventory, customers are likely to turn to competitors to meet their needs. This can result in im-mediate lost sales and potentially long-term loss of customer loyalty. The cost of lost sales often outweighs other costs like idle workers or production downtime because it directly affects revenue and market share. Reference:

* Chopra, S., & Meindl, P. (2015). Supply Chain Management: Strategy, Planning, and Op-eration. Pearson.

* Christopher, M. (2016). Logistics & Supply Chain Management. Pearson UK.

A decision tree is an effective tool for evaluating potential costs and benefits under conditions of uncertainty, such as varying forecasts for future sales. It allows the supply manager to visually map out different decision paths and their associated costs, probabilities, and outcomes. This helps in comparing different scenarios and making informed decisions about the raw materials needed for a new product launch. Decision trees are particularly useful in situations with multiple possible outcomes and complex decisions. Reference:

* Clemen, R. T., & Reilly, T. (2013). Making Hard Decisions with DecisionTools. Cengage Learning.

* Heizer, J., Render, B., & Munson, C. (2017). Operations Management: Sustainability and Supply Chain Management. Pearson.

A Warehouse Management System (WMS) is designed specifically to manage and optimize ware-house operations. It provides real-time data on inventory levels, storage locations, and warehouse capacity, enabling supply managers to understand and maximize the utilization of distribution centers. A WMS can track and improve the efficiency of receiving, putaway, picking, and ship-ping processes, providing a comprehensive view of the warehouse's capacity and performance. Reference:

* Frazelle, E. (2002). World-Class Warehousing and Material Handling. McGraw-Hill.

* Richards, G. (2017). Warehouse Management: A Complete Guide to Improving Efficiency and Minimizing Costs in the Modern Warehouse. Kogan Page Publishers.