APICS CSCP Exam With Confidence Using Practice Dumps

Moving average represents a time series forecasting technique for the following reasons:

Smoothing Technique: Moving average is used to smooth out short-term fluctuations and highlight longer-term trends or cycles in the data. It calculates the average of a fixed number of past observations and moves forward through the time series data.

Forecasting: This method helps in predicting future values based on the average of past data points. By considering a specified number of previous observations, it provides a simple yet effective way to forecast future trends.

Reduction of Noise: By averaging a number of past observations, the moving average technique reduces the impact of random variations and noise in the data, making it easier to identify underlying trends.

Versatility: Moving averages can be adapted to different periods (e.g., short-term, medium-term, long-term) by adjusting the number of observations included in the average. This flexibility makes it useful for various types of time series data.

Application: It is widely used in various fields, including finance, economics, and supply chain management, for tasks such as inventory forecasting, demand planning, and trend analysis.

References

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

Makridakis, S., Wheelwright, S. C., & Hyndman, R. J. (1998). Forecasting: methods and applications. John Wiley & Sons.

After successfully integrating internal supply chain management systems and functions, the next logical step is to extend these efficiencies externally by:

Collaboration with Trading Partners: Engaging with suppliers, distributors, and other partners to streamline the entire supply chain.

Reducing Redundancies: Identifying and eliminating redundant processes and inefficiencies in the supply chain to improve overall performance.

Enhancing Visibility: Sharing information across the supply chain to better align supply and demand, reduce lead times, and lower costs.

Focusing on reducing setup times (A) is an internal process improvement. Implementing a firewall (B) is a security measure, and working with key suppliers to reduce costs and lead times (C) is part of the broader strategy but does not address the holistic approach of reducing channel redundancies.

References

"Supply Chain Integration: Challenges and Solutions" by Douglas M. Lambert.

APICS Dictionary, 16th edition.

The Supply-Chain Operations Reference-model (SCOR) is a process reference model that provides a comprehensive framework for evaluating and improving supply chain performance. It includes best practices for various supply chain processes such as plan, source, make, deliver, return, and enable. In this context, the production and engineering departments using SCOR best practices to design a new "make" process flow is a correct application of the model. The "make" process in SCOR focuses on production activities, and leveraging SCOR's best practices helps in designing efficient and effective production processes.

References

Supply Chain Council. (2012). Supply Chain Operations Reference Model (SCOR) Version 11.0. Supply Chain Council, Inc.

Bolstorff, P., & Rosenbaum, R. (2007). Supply Chain Excellence: A Handbook for Dramatic Improvement Using the SCOR Model. AMACOM.