Inventory Systems

Using the University of Phoenix (2011a) winter historical data an inventory management problem has been formulated to fulfill the assignment criterion. First, an organization is described and the inventory problem it faces is explained. Second, the expected benefits that are motivating to the organization to implement a solution are shown. Next, using the seasonal indices to analyze the inventory data the slope intercept formula is used to determine the annual increase in inventory, while providing monthly seasonal indices for the given data and simultaneously identifying the busies and the slowest months of the year. Furthermore, a histogram of the inventory was depicted and constructed as well as the forecast of the inventory costs using time value of money concepts were completed using Microsoft Excel.

Organizational Description

Current economic conditions and un-clarity within the world's markets causes managers to question business needs as well as provides a reason for businesses to use forecasting as an essential part of remaining in competitive. Whether it is a startup company or well established corporations in business for many years, managers use the experience of past performance to determine future success if not it is possible to make fatal mistakes that will cause any business to fail. Within this report, a four-year history of the Winter Historical Inventory Data (University of Phoenix, 2010b) is examined to create an index to forecast for the upcoming years inventory and sales.

Time Series Data

Time series data are particular types of data with seasonal and cyclical effects that need to be identified in order to the relationship one is trying to bring forthright. Time series data helps identify profits, budgets, sales forecasting, and yield projections. Thus, with the right information businessmen can identify trends as well as make educated predictions of upcoming changes to their market economies. The University of Phoenix Winter Historical Index Data was converted and used for the purpose of this assignment (See Appendix A) (University of Phoenix, 2011b).

Inventory Data Analysis

The seasonal indices were used to analyze the inventory data (See Appendix A-D). The annual increase for the inventory was determined to be y = 2673.3x +35874 (See Appendix C). The monthly seasonal indices for the given data are given in Appendix's A - D. The busy months of the year were identified as the months of October, November, and December (See Appendix D). While on the other hand the slow months identified were May, June, and July (See Appendix D). In addition, the histogram was constructed using Microsoft Excel and is depicted on Appendix A (See Appendix A). Inventory costs using the time value of money concept was estimated at 220,000 using Microsoft Excel.

Conclusion