Time Series

Report:

Time series forecasting involves the use of various methods to estimate future production, sales or advertising expenses to ensure the proper growth of a business, Blue Inc has a 6% market share in the 40 billion industries; the first task is to select the most appropriate model to estimate the advertisement budget.

Advertisement is crucial to the growth a business; it ensures a growth in the market size and also helps a business to maintain its market share. We are provided with three regression model that predict the advertisement budget, we have the sales model, the retail coverage model and the competitor’s model.

In this case we choose the sales model and this is because it has the highest coefficient of determination which is 0.9131, this means that 91.31 % of deviations in advertisement budget are explained by the changes in sales level. The correlations coefficient of the two variables is

0.9555 which shows a very strong positive relationship between the two variables It has also the lowest estimation error which is 11.00 meaning that an estimate will deviate negative or positive 11 million from the actual results, this is the lowest compared to all the other variables, this model is stated as Y = 0.0676 X – 0.3592 which means that as sales increase then advertisement budget also increases.

Time Series

We now use the sales model to estimate the advertisement budget, given that the industry is 40 billion and that the market share of Blue Inc is 6 % we can determine the sales level which is 40 billion X 6% = 2,400 million, we therefore expect the sales level to be approximately 2,400, after setting this sales level we get an advertisement budget of 162 million.

Production:

The next task is to determine the production level for Blue Inc, we use the weighted average method to determine the production level, the sales level forecasted is 776.70 million for the industry, we use 2 periods to estimate the values due to the errors associated with the use of many periods, the 11th period will have a 0.1 weight while the 12 period will have 0.9 weight, as a result of this we estimate the production level to be 46 units.

Production for the four quarters:

From the trends of production and sales it is evident that there are deviations in the production in each quarter, we use the central moving average because we will only be determining the production for the four periods, it is also evident that the company ensures a 10% safety stock and that from the ales forecast the following are the sales levels predicted for the four quarters:

quarters

sales forecast

1

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10.24

2

12.72

3

11.5

4

18.12

Given the above sales forecasts we will be in a position to determine the production level, we will determine the production level taking into consideration the forecasted sales and also the 10

Time Series

% safety stocks for each period, for this reason therefore we set the production for each quarter as follows:

quarters

production

1

11

2

13

3

12

4

19

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From the above discussion therefore it is evident that we use different methods to forecast depending on the advantages associated with these methods, to estimate the advertisement budget we use the model with the highest correlation of determination and correlation coefficient and also the lowest estimation error. We then use the weighted mean method to estimate production and then the centered moving average method to estimate production for the quarters.

REFERENCE:

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Doane Steward (2007) applied statistics for business and economics, McGraw Hill publishers, N ew York