| Date: 16th March | | | | model and this model depict that an increase in the |
| To: Vice President, Myra Reid | | | | level of competitors budget by one unit will result into |
| From: The forecast department | | | | an increase in the companies advertisement budget by |
| Subject: Advertising, Sales and production forecast | | | | 0.8666 units, the correlation coefficient in this case is |
| This memo outlines the sales forecast for the next | | | | equal to 0.8838 meaning that there is a strong relation |
| one year in terms of sales and production, | | | | between the two variables, the coefficient of |
| Advertising in the company plays a major role in the | | | | determination is equal to 0.781 meaning that 78% of |
| organisation sales level and because competitors have | | | | deviations in advertising budget are explained by the |
| increased their advertising budget then there is a high | | | | competitors budget. |
| possibility that they may capture our market share if | | | | Having estimated the three model the next step I took |
| the company does not use a proper advertising | | | | is to choose the best model that could be used in |
| strategy. | | | | forecasting, the sales model is the best due to the |
| However previous data regarding advertisement | | | | strong relationship that exist between the two |
| budget by competitors, the company has spent less | | | | variables. The correlation matrix also shows that there |
| than its competitors and that advertisement budget | | | | is a strong correlation between sales and other |
| has increased over the past years and as a result | | | | variables. |
| there has been an increase in market share and sales. | | | | The expected market in the industry is 40 billion which |
| Therefore an increase in advertising budget will | | | | is 5 billion less, in year 11 the sales level was 2,454 |
| increase sales and at the same time increase market | | | | million and in year 12 sales level was 2,264 and |
| share. | | | | therefore we expect the sales level to increase and if |
| According to the sales model estimated an increase in | | | | sales level increase then the advertising budget will |
| one unit of sales will result into a 0.0676 in sales | | | | also increase. If we expect the sales level to increase |
| budget, this model has a 0.9131 coefficient of | | | | to 2,500 then the advertising budget will increase to 169 |
| determination and this means that 91% of deviations in | | | | million. An Increase in advertising expenditure will |
| the advertising budget are determined by sales holding | | | | increase promotional activity according to Tim. |
| other factors constant. The correlation coefficient for | | | | Market size has steadily increased over the years and |
| the data is 0.9555 and this means that there is a | | | | this means that there is a high possibility of increase in |
| strong positive relationship between sales and | | | | sales, in year 12 the sales level was 39,049 and this is |
| advertisement spending. | | | | expected to rise to over 40,000 in the next year, for |
| The retail coverage model depict that if there is an | | | | this reason therefore we choose the weighted moving |
| increase in retail coverage by one unit then the | | | | average based on 2 periods where year 11 has 0.1 |
| advertisement budget will increase by 1.9 units holding | | | | weight and year 12 has 0.9 weight. From this point we |
| all other factors constant, the coefficient of | | | | set the production level at 60 units with seasonal |
| determination is 0.5934 depicting that 59% deviations in | | | | variations of 12 units in the first quarter, 16 units in the |
| advertising budgets are explained by retail coverage. | | | | second quarter, 13 units in the third quarter and 20 units |
| The correlation coefficient is 0.7703 meaning that there | | | | in the forth quarter. |
| is a strong positive relationship between the two | | | | References: |
| variables. | | | | Bluman A. |
| This last model is the competitors advertising budget | | | | |