Applying Time Series MethodologiesApplying Time Series MethodologiesThe purpose of this memo is to provide the business decisions that were made concerning the sales production plan for all the upcoming quarters. First our team decided to use the centering moving average model with the selected data range of 6 years for the calculations. The reason our team chose this was to obtain the best possible accurate results. Our team did not want to go too far in the past as past trends may no longer applicable. As for the production of the product our team decided to fix production levels at 11 million units for the first quarter, 14 million units for the second quarter, 12 million for the third quarter and 20 million for the fourth quarter. The reason for these production levels was to coincide the sales figure forecast.
Date: September 26, 2012
Time: 5:00 AM Eastern: 9:00 PM Western: 10:59 PM
Where: Seattle, WA,
We would like you to have your input and feedback regarding the results of this experiment.
We think this is very interesting data for the future. We know for sure that when new products arrive the sales volumes and margins become more and more difficult for users, with some products even getting in the way of sales.
Now we know the data we wanted and the data we are looking for, so we are going to get back to you with the first results in this one
As you may know, we worked with this data and found that the sales growth in the US was so slow that the majority of our customers had been affected.
If you have a lot of questions for us and to see these results in action, please call us at: +1-206-903-5895, +1-206-903-5739, e-mail: [email protected] or on Google+.
We also plan ahead, to be quite frank right next time and right after that.
While we still have quite a few additional data sets to analyze, we’re confident that we know enough to start implementing new trends as well as doing a greater number of comparisons. As such, we’d appreciate your feedback and feedback as we continue work with our analytics team to create better ways of doing this.
We would like to thank you for your input and feedback. For more information, please see our full product line and our FAQ.
If you think it’s a good idea, please send us an e-mail at [email protected] that we will try to answer back.
Our team would also like to add to the decisions that were made concerning the advertising budget. The first decision made for the advertising strategy was to use sales as a variable for regression analysis. Based on our findings the correlation coefficient of sales with the advertising budget is 0.96. This correlation indicates that the sales have a strong positive relationship with the advertising budget. Using the regression equation our team found the value of the advertising budget would be at $2,400 million, which would make our advertising budget at $162 million. The budget was decided at $162 million since Blues, Inc. shares 6% of the $40 billion dollar denim industry. This budget would help with maintaining our competitive abilities.
The next decision that was made was to study the fluctuations in the market size to reach the destination of our sales forecast. Our team decided to use a 2-period