Week 4 Critical Thinking_Forecasting

Week 4 Critical Thinking: Forecasting

Insert name

Institutional affiliation

Week 4 Critical Thinking: Forecasting

Introduction

Highline Financial Services provides three types of services to its clients. Analysis of the three categories of services – A, B, and C – by the manager shows that in the past eight quarters the demand for the services has been oscillating. This assignment will present the demand of the three categories for the next three quarters using the data on the past eight quarters. This would help the management of the company in the development of financial and personnel hiring plans for the coming financial year.

Demand of the Three Categories of Services

The table below shows the demand for the three categories of services offered by Highline Financial Services. Analysis of the data shows that the demand for there is oscillating demand for the services. In the first quarter, the demand for each of the services starts with a high value before reducing in the second quarter. It then increases significantly in the third quarter before dropping again in the fourth quarter. Comparison of the data for Year 1 and Year 2 shows that there is a slight increase in the demand of each category of product in the second quarter. However, the oscillation of the demand is also present in the second quarter.

LINK Excel.Sheet.12 F:Ordersforecast.xlsx Sheet1!R2C2:R11C6 a f 5 h * MERGEFORMAT

Service

Year A B C

1 1 60 95 93

2 45 85 90

3 100 92 110

4 75 65 90

2 5 72 85 102

6 51 75 75

7 112 85 110

8 85 50 100

Table 1: Demand of the three categories of products offered by Highline Financial Services Company

Demand Forecasting

The first step in determining the demand for the products is determining the trend of the demand for the different categories of products offered by the company. Table 1 shown above may be used to indicate the trend of the demand for each category of product. Visual representation of the trend of demand for each category using a graph would clearly show the trend in the demand each of the product categories.

Figure 1: Graph of the demand of the three product categories

From the graph, it is evident that the demand for each product category oscillates from one quarter to another. This shows that there is seasonality in the demand for each of the products. The seasonality leads to variations in the demand of each product category, which is based on the time of the year. Based on this fact, one of the methods that can be used to generate the demand for the three products is the naïve method.

According to Stevenson (2018), the naïve method is a simple forecasting method that is used with a stable series, data with seasonal variations, or data with a trend. In a stable series, the last data point is used to determine the forecast for the next period. On the other hand, with seasonal variations, the forecast for the last season is used to determine the forecast for the next season.

Using the naïve method, the changes in demand for each corresponding quarter in a financial year can help in generating the forecasts for four quarters of the third financial year. The table below shows the changes in the demand for each corresponding quarters in the two financial years whose data is provided in the case study.

From the table the changes shown after year 2 are calculated by dividing the demand in Year 2 by the demand in the corresponding quarter in Year 1. For instance, the changes in the demand for product A in quarter 1 are calculated by dividing 72, which is the demand of product A during quarter 1 of year 2, by 60, which is the demand of product A during quarter 1 of year 1.

Therefore, 72/60 = 1.20. The changes shown in after year 2 show the ratio of change of demand in each corresponding quarter. This ratio can be used to generate the forecasts for the quarters in year 3 by simply multiplying this value by the corresponding demand in each quarter in year 2.

LINK Excel.Sheet.12 “F:Ordersforecast.xlsx” “Sheet3!R2C2:R15C6” a f 5 h * MERGEFORMAT

Service

Year A B C

1 1 60 95 93

2 45 85 90

3 100 92 110

4 75 65 90

2 5 72 85 102

6 51 75 75

7 112 85 110

8 85 50 100

3 9 86 76 112

10 58 66 63

11 125 79 110

12 96 38 111

Table 2: Ratio of change in demand

This ratio can be used to generate the forecasts for the quarters in year 3 by simply multiplying this value by the corresponding demand in each quarter in year 2. This is shown in the table below. It is vital to note that the figures generated have been rounded to nearest integer.

LINK Excel.Sheet.12 “F:Ordersforecast.xlsx” “Sheet3!R2C2:R15C6” a f 5 h * MERGEFORMAT

Service

Year A B C

1 1 60 95 93

2 45 85 90

3 100 92 110

4 75 65 90

2 5 72 85 102

6 51 75 75

7 112 85 110

8 85 50 100

3 9 86 76 112

10 58 66 63

11 125 79 110

12 96 38 111

Table 3: Demand forecast of each product category (indicated in bold in year 3)

The demand forecast for each product is shown in table above. The naïve method was chosen due to its simplicity. In addition, nothing would change in terms of the amount of money or strategy that the company would use in advertising or promotion and the competition would not change (Reid & Sanders, 2019). Therefore, the factors that led to the changes in the demand of each product category in the two financial years would remain the same. Therefore, assuming all things remain constant, the ratio of increase or decrease in demand in year 3 compared to year 2 would be the same as the ratio of increase or decrease of demand in year 2 compared to year 1. Therefore, the naïve method would yield the most accurate demand forecasts due to the simplicity of the forecasting method and the fact that that it assumes all things remain constant.

The same forecasting method was chosen for all product categories since their demand have similar features. All the product categories have seasonal variations in demand. However, the ratio of seasonal variation of demand for each category is different.

Benefits of Using a Formalized Approach to Forecasting

There are seasonal variations in the demand of each product category. The use of a formalized approach to forecasting would help in predicting the demand for each product category. This would enable the company plan ahead to avoid service delay or inconveniencing customers. For instance, it would help the company determine its future personnel needs. Having personnel hiring plans that is based on the demand forecasts would prevent the company from having a workforce shortage or employing too many employees, which would increase the operational costs of the company (van der Laan et al., 2016). Therefore, it is pertinent to claim that a formalized approach to forecasting helps in improving the efficiency of the operations of the company.

Conclusion

Demand forecasting is vital in the operations of any business. It is more important in businesses that have seasonal variations in demand such as Highline Financial Services. However, it is vital for a company to use the right demand forecasting method. The use of the naïve method would help Highline Financial Services demand the demand of each product category. This would help the company to develop accurate personnel hiring plans, which would ensure it has the right workforce to meet the demand for its services at different times of the year.

References

Reid, R. D., & Sanders, N. R. (2019). Operations management: an integrated approach. Hoboken, NJ: John Wiley & Sons.

Stevenson, W. (2018). Operations management (13th ed.). New York, NY: McGraw-Hill Irwin.

van der Laan, E., van Dalen, J., Rohrmoser, M., & Simpson, R. (2016). Demand forecasting and order planning for humanitarian logistics: An empirical assessment. Journal of Operations Management, 45, 114-122.