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As production manager last unit in the Kibby and Strand simulation you gained insights into how raw materials were turned into finished goods

As production manager last unit in the Kibby and Strand simulation you gained insights into how raw materials were turned into finished goods

Unit 2: Discussion

Introduction

As production manager last unit in the Kibby and Strand simulation you gained insights into how raw materials were turned into finished goods. This unit you will learn more about the front end of the operational process employed by the company. Specifically, you will learn how to manage suppliers who provide the raw materials used in the production of the company’s textile products. Some challenges you will face are: 1) which suppliers provide the best quality raw materials; 2) which suppliers are the most reliable; and 3) which suppliers have the most competitive prices.

The simulation scenario will pose many opportunities for decision making and forecasting, and if you make a poor decision regarding suppliers it will impact the ability of Kibby and Strand to meet its contractual obligations, leading to dissatisfied customers. Since customer satisfaction weighs heavily on future contracts, you can’t simply make the best decision for the moment, but rather the best decision for the long haul. This scenario provides a realistic illustration of the issues textile companies face across the U.S. It’s extremely important that operations professionals have an above average comfortable level when it comes to establishing grounded assumptions and conducting and interpreting financial and operational forecasts. In its simplest form, forecasting is a process that represents an “educated guess”. In business, we use time series methods, the indicator approach, or regression analyses to forecast the nature of a situation or future values. The data we observe when forecasting fall into one of four types: trended patterns, seasonal patterns, cyclical patterns, or irregular patterns (Kros & Brown, 2013). Forecasting models are used to predict consumer demand, which, in turn, aids management in forecasting staffing requirements. In addition, to demand forecasts, management routinely engages in financial forecasting, which includes, but is not limited to: sales growth, economic predictions, and forecast future cash flows. In order to perform forecasts, it’s important that the management team signoff on the underlying assumptions used to complete these analyses, such as population growth and technology development. The following represents the typical steps one undertakes when preparing for and conducting a forecast (Investopedia, n.d.):

1. A problem or data point is chosen. This can be something like “will people buy a high-end coffee maker?” or “what will our sales be in March next year?”

2. Theoretical variables and an ideal data set are chosen. This is where the forecaster identifies the relevant variables that need to be considered and decides how to collect the data.

3. Assumption time. To cut down the time and data needed to make a forecast, the forecaster makes some explicit assumptions to simplify the process.

4. A model is chosen. The forecaster picks the model that fits the data set, selected variables and assumptions.

5. Analysis. Using the model, the data is analyzed and a forecast made from the analysis.

6. Verification. The forecaster compares the forecast to what actually happens to tweak the process, identify problems or in the rare case of an absolutely accurate forecast, pat himself on the back.

Sources:

Kros, J. F., & Brown, E. (2013). Health Care Operations and Supply Chain Management.  San Francisco, CA: John Wiley & Sons.

http://www.investopedia.com/articles/financial-theory/11/basics-business-forcasting.asp (Links to an external site.)

Unit Learning Outcomes

1. Develop a plan for forecasting impacts to an organization’s bottom line. (CLO 1, 2, 4, and 7)

2. Demonstrate how to perform forecasting using data and statistics. (CLO 4 and 5)

3. Identify trends and patterns in data as they apply to forecasting. (CLO 1, 3, 5, and 7)

4. Develop a data collection plan that will permit the creation of an accurate and reliable forecasting model. (CLO 3, 4, and 5)

Directions

Accessing McGraw-Hill Connect

Follow these steps to view the scenario.

Initial Posting

Go to McGraw-Hill Practice Operations to view the scenario.

1. Click the “McGraw-Hill Connect” tab in the course navigation menu.

2. Click the McGraw-Hill Practice Operations link.

Students are to complete Module 3, Forecasting and Contracts (Scenario) in Practice Operations. Based on their observations in this scenario, and upon a careful review of the available literature, the student is to consider him or herself to be the Production Manager of Kibby and Strand, the company in the scenario.

Create a forecasting plan to forecast production output for Kibby and Strand.  The plan should include forecasting objectives, the data to be used in forecasting, and the quantitative methods the staff is to use in creating the production output forecast.

Instruction Guidance: It would be prudent to consider content covered in chapter 3 of the textbook; however, there are many other useful resources available on the Internet and in the literature to support the construction of your action plan.

This forecasting plan should be prepared as a single Microsoft Word document, and then attached to the unit discussion thread. There is no minimum or maximum in terms of the word count; however, the response should explicitly address all required components of this discussion assignment. The document should be prepared consistent with the APA writing style and reflect higher level cognitive processing (analysis, synthesis and or evaluation).


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