Select an inventory management problem that applies to your work or personal life.
Prepare a project proposal in which you:
•Describe the organization, the inventory problem it faces, and the expected benefits that are motivating the organization to implement a solution.
•Convert time series data collected in Week Two to seasonal indices. You may choose to use the University of Phoenix Material: Summer Historical inventory data or University of Phoenix Material: Winter Historical Inventory Data if the data you collected is insufficient.
•Use seasonal indices to analyze the inventory data.
oUse the slope-intercept formula to determine the annual increase in inventory.
oProvide monthly seasonal indices for the given data.
oIdentify the busy months of year.
oIdentify the slow months of year.
•Construct a histogram of the inventory data using Microsoft® Excel®.
•Forecast the future inventory costs using time value of money concepts.
University of Phoenix Summer Historical Inventory Data
The University of Phoenix Summer Historical Inventory Data is the source for developing Team B’s inventory management proposal. Annual trend lines were plotted in Microsoft Excel © to display the inventory amounts for each year. The trend line in this case is positive, which indicates that the likelihood of inventory levels in the subsequent years will continue to rise without considering any additional factors that may influence the business. Factors to support the observation include economic instability from stock market volatility, a decline in consumer confidence, severe weather, and acts of terrorism. Table 1 shows the existing data and includes the fifth year projections. Figure 1 displays the trend line.
The Term Paper on Sales and Inventory Monitoring system
Introduction The used of manual processes in business has decline since the rise of computerized and automated systems. And in fact, nowadays, the use of computer-based business system has become prevalent all throughout the developed and developing countries around the world due to the increased productivity and efficiency of data processing A collection of components that work together to ...
