Essay Doctorate 454 words

Forecasting Indices the Following Figure Is Taken

Last reviewed: March 11, 2013 ~3 min read
Abstract

Using forecasting idnices to predict and react to demand variation is critical in many marketing, operations and production-based professions. The intent of this analysis is to define how best to accomplish forecasting analysis using time series analysis in addition to exponential smoothing. The results show that this approach is the best for the data set given in the example.

Forecasting Indices

The following figure is taken from sales data of sporting goods, graphed over the last four years, showing worldwide demand for wave and ski boards combined. Each line on the graphic shows combined sales of wave and ski boards. The significant ramp in sales throughout March and April are attributable to the launch of each seasons' new wave boards. The spoke in sales in October are attributable to ski board sales ramping on a seasonal basis. In aggregate the market continues to grow for these products, generating a compound annual growth rate (CAGR) for the four years of 4.76%. Using averaging based on four periods generates the Averaging line shown in the following graphic.

Forecasting Analysis

A relatively simplistic approach to defining year 5's inventory doesn't necessarily capture the variation in forecasts over the four previous years. As can be seen from the graphic on the previous page, simple averaging only amplifies the variation in the data series, it does not explain which factors are causing the variation overall (Ziegel, 2006).

What's needed to better understand the variation in the data is a forecasting technique that takes into account periodic fluctuations in value. The following analysis was completed using the Moving Average feature of the Data Analysis Pack installed in Microsoft Excel 2010. The orange line shows the relative goodness of fit for the data overall, showing May to be the month with the highest demand and therefore the most difficult to forecast. December's low inventory levels show how wave and ski boards are popular gifts during the holiday season.

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References
3 sources cited in this paper
  • Goodwin, P., & Wright, G. (1993). Improving judgmental time series forecasting: A review of the guidance provided by research. International Journal of Forecasting, 9(2), 147-147.
  • Snyder, D. (1982). Current approaches to time series forecasting. Business Forum, 7(2), 24-24.
  • Ziegel, E. R. (2006). Computational intelligence in time series forecasting. Technometrics, 48(3), 451-451.
Cite This Paper
PaperDue. (2013). Forecasting Indices the Following Figure Is Taken. PaperDue. https://www.paperdue.com/essay/forecasting-indices-the-following-figure-86603

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