The corporation may wish to find out the growth of output, employment, sales revenue, profits, and many other aspects that relate to the well-being of the firm in the future. For the case of Speciality Packaging Corporation, Julie should use time series analysis. Time series analysis is qualitative in nature and measures data over time to show trends.
The data of various aspects of the corporation record interval is weekly, monthly or even yearly depending on the needs of the company. Seasonal, trend, cyclical and irregular components make up the time series. Trend part may refer to increasing or decreasing sales depending on the computed figures. Cyclical components lie below or above the trend line and repeat for a year or longer.
Seasonal trends are like cyclical trends but occurs only in one year periods. The components of data used in time series analysis are subjective, rely on judgement and opinion of consumers and are more useful when data is not available.
The corporation can fully benefit from its forecasting mechanisms by use of time series analysis. It shows the trend in which various components like sales and revenue are following over time and thus the company may show where it shall be in the future (Makridakis, 1989).
Forecasting methods comes with a lot of errors due to uncertainties about the future business trends. In most cases, there are so many errors committed in the estimation of sales revenue and costs of production.
Julie, when using the time-series forecasting method meets errors in which the estimates(parameters) and actual results(statistics) are going to differ on the kind of data included in the analysis, data collection process, where the data is from, induced changes, the mathematical modelling techniques and computer models interpretation and analysis.
Julie, therefore, should pay a lot of attention to choice of data sources, collection methods, computation methods and the ultimate analysis to give her a clear picture which shall depict the outlook for the firm (Makridakis, 1989).
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