Demand Forecasting Techniques for Lean Manufacturing Supply Chains Discussion

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Forecasting (100 points)

Read through the Case Study entitled “Highline Financial Services, Ltd.” in Chapter 3 of your textbook. Examine the historical trends this company has experienced for the three products (A, B, C) discussed over the 2 years shown. Address the following requirements: Prepare demand forecasts for the next four quarters for all three products, describe the forecasting method you chose and explain why that forecasting method is best suited to the scenario. Explain why you did, or did not, choose the same forecasting method for each product. What are the benefits of using a formalized approach to forecasting these products?


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Running head: DEMAND FORECASTING Demand Forecasting Afnan J AL Mutiri Dr. Victoria Figiel MGT-530 - 13738 Oct, 5, 2019 1 DEMAND FORECASTING 2 The task ahead involves conducting a forecast on the demand levels for Highline financial services for the next four quarters. The company offers various financial services A, B, and C form the core products that Highline has. The three are the primary sources of income for the company. One of the Managing Partners, Freddie Mack, has sort for business forecasting services concerning the three products. The forecast will assist Mr. Mack in making critical decisions and plans for the future. There have been periods of uncertainty in the financial markets; thus, Mr. Mack is uncertain of the future (Mishra, 2018). Based on the forecast given, the company will take several actions to help the company withstand the storm of anxiety about the future. This forecast shall, therefore, form a basis for Mr. Mack to make decisions, and shall be subject to thorough scrutiny by the company's top management (Bower, 2018). The forecast shall also influence other factors such as business strategies, rebranding of products, increasing shift of labor, technology adoption, and even a costprofit ratio. Highline does not have stock inventory since it offers real-time services; thus, the demand estimates should be as accurate as possible. Forecasting the Three Products The data given about these products is not enough to make seasonal relations, but then it is possible to make reasonably excellent and intuitive estimates for the next four quarters (Bower, 2018). Therefore, the demand data from the last two years were tabulated in an excel sheet and a graphical representation of the trend drawn. Using the graphical representation, it is easy to intuitively and naively make out a particular trend followed by the demand quantities (Rivera- DEMAND FORECASTING 3 Castro et al., 2019). The best approach to use while estimating the demand for products A, B and C are moving average technique forecasting. Product Quarters A B C 1 60 95 93 2 45 85 90 3 100 92 110 4 75 65 90 5 72 85 102 6 51 75 75 7 112 85 110 8 85 60 100 9 82.6667 70 95 10 93.2222 68.3333 101.667 11 86.963 62.7778 98.8889 12 87.6173 67.037 98.5185 The figures above represent the forecasted demands for financial products A, B, and C. The data presented above indicates that with the maximum likelihood, the following demands will be witnessed for the next four quarters. The output suggests that for the products A, B, and C, the company will most likely experience the following demands for financial products A, B, and C during the next four quarters, respectively: DEMAND FORECASTING 4 Product A Quarter Forecasted moving average demand 9 82.67 10 93.22 11 86.96 12 87.62 (Rounded –off to the nearest two decimal places) Product B Quarter Forecasted moving average demand 9 70.00 10 68.33 11 62.78 12 67.03 (Rounded –off to the nearest two decimal places) Product C Quarter Forecasted moving average demand 9 95.00 10 101.66 DEMAND FORECASTING 5 11 98.89 12 98.52 (Rounded –off to the nearest two decimal places) Why I Chose Moving Average Method Moving average is advantageous since it can be used to measure the trend of any series of data, whether linear or non-linear(Rivera-Castro et al., 2019). The method gives room for smoothing that chances of varying datasets are significantly decreased. The data provided was not enough to form a seasonal relationship of the data, thus to make an intuitive forecast, the moving average is the choice to make. Using moving average at periods of three quarters, data was easily examined; thus, a trend, flow, and cycle followed by the data were established. Additionally, the moving average is also easy in both the application and interpretation of results. Therefore, every person, including Mr. Mack, can understand the outcomes of the forecast without a problem. Moving average also makes use of the immediate last data sets (Quarters 6 to 8). Therefore, there is a high probability that the forecasted values will be almost close to actual values(Rivera-Castro et al., 2019). The values established from the forecast are just assumptions, and therefore the actual values may either exceed or go less. The forecast values will, however, explain the trend followed by future values. Disadvantages of Using Moving Average Moving average is majorly used for a data set with many data values to enhance accuracy. However, the data values given above were not enough to make a more accurate forecast(RiveraCastro et al., 2019). This, however, does not negate the intuition involved in the forecast above. Another weakness is the assumption that all the data values have equal effort in affecting and DEMAND FORECASTING 6 altering the future values. Ideally, it is the immediate last values that affect the forecasted value the most. Considerations while Using Moving Average Precision is of utmost attention while using a moving average. The averaging formula should be accurately tabulated and then subjected to the same conditions throughout(Bicer&Lücker, 2018). Forecast values from moving average techniques are always precise in representing the nature of the actual value. Moving average is also favorable in demand forecasting since it is easy to use and interpret results. The simplicity also makes it convenient to use for any data series, whether linear or not. Lastly, moving average allows for smooth, thus possible, to eliminate data values that have some variations(Rivera-Castro et al., 2019). The line graphs of products A, B, and C is consistent hence possible to locate a particular trend, as shown below: Product A 120.00 100.00 80.00 60.00 A 40.00 20.00 0.00 Q1Y Q2Y Q3Y Q4Y Q1Y Q2Y Q3Y Q4Y Q1Y Q2Y Q3Y Q3Y 1 1 1 1 2 2 2 2 3 3 3 4 A 60.0 45.0 100. 75.0 72.0 51.0 112. 85.0 82.6 93.2 86.9 87.6 DEMAND FORECASTING 7 Product B 100.00 80.00 60.00 40.00 B 20.00 0.00 Q1Y1 Q2Y1 Q3Y1 Q4Y1 Q1Y2 Q2Y2 Q3Y2 Q4Y2 Q1Y3 Q2Y3 Q3Y3 Q3Y4 B 95.00 85.00 92.00 65.00 85.00 75.00 85.00 60.00 70.00 68.33 62.78 67.04 Product C 120.00 100.00 80.00 60.00 C 40.00 20.00 0.00 Q1Y1 Q2Y1 Q3Y1 Q4Y1 Q1Y2 Q2Y2 Q3Y2 Q4Y2 Q1Y3 Q2Y3 Q3Y3 Q3Y4 C 93.00 90.00 110.0 90.00 102.0 75.00 110.0 100.0 95.00 101.6 98.89 98.52 Overall Results and Recommendations The values from the moving average formula show the eventual outcome of demand for the next four quarters. The values no doubt primarily stand within the expected needs. The graph DEMAND FORECASTING 8 below represents the expected trend for the demands of products A, B, and C. 120.00 Graph showing forecasted demands 100.00 80.00 60.00 Product A 40.00 Product B 20.00 0.00 Product C First Quarter Second Quarter Third Quarter Fourth Quarter Product A 82.67 93.22 86.96 87.62 Product B 70.00 68.33 62.78 67.04 Product C 95.00 101.67 98.89 98.52 The use of the same methods of forecasting for all three products ensures consistency of the forecasts. The process of interpreting the likely results of the forecast should be as simplified and straight forward (Rivera-Castro et al., 2019). Employing different approaches for the methods may lead to inconsistent outcomes. It is also practical to use the same forecasting technique to deal with the same products. Catering to different forecasting methods for each product can be costly for the company in terms of time, energy, and resources. It is thus advisable to use a single forecasting technique for the three products. Benefits of Formalized Approach in Forecasting Accuracy and precision should be significantly considered when dealing with business forecasting. It is impossible to achieve accuracy using pure guessing or naïve prediction, thus the need for using formalized statistical approaches to make accurate forecasts(Bower, 2018). Companies rely on various methods while making both quantitative and qualitative forecasts on multiple factors, such as demand, price, and revenues (Bicer&Lücker, 2018). Thus, relying solely on intuition and guesses without using formalized techniques would result in erroneous judgments. DEMAND FORECASTING 9 Formalized forecasting methods are also simple to use and interpret results(Bicer&Lücker, 2018). The only requirement is for the correct formula to be applied. For instance, using MS Excel requires the input of the formula only once, and then the formula can be used for as long as needed (Bower, 2018). It is also possible to store the data for future references and referrals. A formalized approach also puts into consideration all possible outcomes before arriving at a final result. Lastly, it is economical to use formalized procedures since it saves on time, energy, and money used in forecasting. References DEMAND FORECASTING 10 Bicer, I., &Lücker, F. (2018).Inventory Dispersion in a Sequential Inventory System with Demand Forecast Evolution. Available at SSRN 3275499. Bower, P. (2018).S&OP, Demand Control, and Quick Response Forecasting. Journal of Business Forecasting, 37(2). Mishra, S. (2018).Financial management and forecasting using business intelligence and big data analytics tools. International Journal of Financial Engineering, 5(02), 1850011. Rivera-Castro, R., Nazarov, I., Xiang, Y., Pletneev, A., Maksimov, I., &Burnaev, E. (2019, July). Demand forecasting techniques for build-to-order lean manufacturing supply chains. In International Symposium on Neural Networks (pp. 213-222).Springer, Cham. Retrieved from https://link.springer.com/chapter/10.1007/978-3-030-22796-8_23 CASE HIGHLINE FINANCIAL SERVICES, LTD. or promotion, and competition doesn't change, predict demand for the services the company offers for the next four quarters. Note that there are not enough data to develop seasonal rela- tives. Nonetheless, you should be able to make reasonably good, approximate intuitive estimates of demand. What general obser- vations can you make regarding demand? Should Freddie have any concerns? Explain. B Highline Financial Services provides three categories of service to its clients. Managing partner Freddie Mack is getting ready to pre- pare financial and personnel hiring (or layoff) plans for the coming year. He is a bit perplexed by the following printout he obtained which seems to show oscillating demand for the three categories of services over the past eight quarters: Service Year Quarter А с 1 60 95 93 2 90 3 100 92 110 75 65 90 Examine the demand that this company has experienced for the three categories of service it offers over the preceding two years. Assuming nothing changes in terms of advertising 1 Year A C 45 85 2 Quarter 1 2 72 51 Service B 85 75 85 50 102 75 110 3 112 85 4 100 SELECTED BIBLIOGRAPHY AND FURTHER READINGS Acar, Yavuc, and Everette S. Gardner, Jr. "Forecasting Hanke, John, and Dean Wichern. Business Forecast- Method Selection in a Global Supply Chain." Inter ing. 9th ed. Upper Saddle River, NJ: Pearson, 2009. national Journal of Forecasting 28, no. 4 (October- Hopp, Wallace J., and Mark 1. Spearman. Factory December 2012), 842-48. Physics, 3rd ed. New York: McGraw-Hill, 2008. Bonomo, Charles. “Forecasting from the Center of the Wilson, J. Holton, Barry Keating, and John Galt Solu- Supply Chain." Journal of Business Forecasting tions. Business Forecasting with ForecasiX, 6th ed. Methods and Systems 22, no. 1 (Spring 2003), p. 3. New York: McGraw-Hill, 2009. Byrne, Robert F. "Forecasting Performance for North American Consumer Products." Journal of Business Forecasting 31, no. 3 (Fall 2012), p. 12.
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Running head: DEMAND FORECASTING

Demand Forecasting
Student’s Name
Institution

1

DEMAND FORECASTING

2
Demand Forecasting
Historical Trends of the Company

Highline Financial Services has three main product lines, including service A, B and C.
The managing partner, Freddie Mack, relies on these three service categories in formulating
financial plans for the company. However, there is considerable level of uncertainties in the
market as characterized by the fluctuating demand in all of the company’s sources of income.
Demand forecasting constitutes a useful tool that can enable the managing partner to predict the
future demand of these product categories.
As a critical component of an organization’s supply chain, demand forecasting estimates
future demands. Furthermore, the methodology sets the level of preparedness of the supply side
to meet the anticipated demands. Accurate forecasting is, therefore, the priority of many financial
managers as they seek to balance the company’s supply capacity with available demand in the
market (Nimai et al., 2019). Similarly, Freddie Mack has a critical role to play in developing
reasonable forecasts of future service demand. The performance of these products in the
preceding two years provides the background for estimating demand levels in the third financial
year.
During the first year, all the three products experienced a slight drop between the first and
second quarter. A significant increase was then realized in the third quarter before plummeting
again in the fourth quarter. Similar trends were observed in the second financial year with
services A, B and C showcasing mere drops towards the second and fourth quarters. It would
seem that the company realizes increased demand during the third quarters of its financial years.

DEMAND FORECASTING

3

On this note, these trends offer valuable insight on making intuitive forecasts for the next four
quarters in the third financial year.
Demand Forecasts for the Next Four Quarters
As aforementioned, the data on the two financial years are crucial in the estimation of
future demands. Ideally, the first step towards this process would entail tabulating the
information in an excel spread sheet and then performing a graphical analysis to showcase future
trends. Furthermore, graphs contain patterns that are easily identifiable, which will further
contribute to the understanding of future demand trends. Consistent with these procedures, the
below table illustrates the demand for the services for all the quarters in the three years. As a
result, the figures from the ninth entry to the twelfth line illustrate the demand forecasts.
Financial Quarter

Product A

Product B

Product C

1.

60

95

93

2.

45

85

90

3.

100

92

110

4.

75

65

90

5.

72

85

102

6.

51

75

75

7.

112

85

110

8.

85

60

100

9.

83

70

95

10.

93

68

102

11.

87

63

99

DEMAND FORECASTING
12.

4

88

Year 3 Quarter

67

98

Service A

Service B

Service C

1

83

70

95

2

93

68

102...


Anonymous
Excellent resource! Really helped me get the gist of things.

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