Inventory_Systems

University of Phoenix Inventory Systems Summary Summer and Winter Data Comparison MGT/521 03/21/2012 Summer and Winter Data Overview The way in which an organization manages its inventory levels has a significant impact on that organization’s profitability. If an organization is unable to anticipate product demand they could find themselves with inadequate product to meet customers’ needs or in a different regard too much product that remains unsold in the warehouse. Effectively anticipating demand and adjusting inventory levels appropriately will help to ensure product flows to the customer when it’s needed and revenue and profitably are maximized. An important method in gauging proper inventory levels is through analyzing prior years’ demand data looking for trends and anomalies. Certain products will have seasonal demand and therefore warrant inventory management models that account for these seasonal sales cycles. In the data provided, the University of Phoenix provided two inventory models a summer and a winter. The two models provide data for the number of units in a time frame of four years for each seasonal time frame. Summer Data Data from the summer inventory model shows that over 56% of all unit demand occurs in April through August. On a monthly basis the most substantial year over year growth for that same four year period occurred in the months of February, which saw 158.84%, March at 119.11%, and September at 103.90% in unit demand growth. However, the months of May, June, and November saw negative demand over the same four-year period at (-18.15%), (-16.19%), and (-21.50%) demand growth from year one to year four, respectively. The data indicates that over a four-year period demand improved 20.42% from 457,350 units in year one to 550,750 in year four. Year two saw the single highest year over year growth reaching double digit gains at 10.39% from 487,030 units in year two to 537,620 in year three. These consistent gains show a positive trend in unit demand for the entire four year period indicating a favorable forecast into years five and onward. Winter Data Conversely, when the same organization’s inventory is looked at from different seasonal perspective unique outcomes transpire. When viewed from a winter seasonal model one immediately finds that 56.1% of all demand takes place in the five months between October and February. An immediate concern with this type of model is the ability to provide inventory. To meet a winter demand the organization must concern themselves with winter weather patterns. Inaccessibility of distribution routes can cause delays in product deliver to customers. When one analyzes the winter data more closely several trends emerge. Over the four-year period the most significant growth occurred in the months of March, August, and September with 103.90%, 158.84%, and 119.11% total growth respectively. This could be indicative of a change in demand trends for the products as during the same four years those months, which combined had the highest demand in total units (Oct-Feb), saw growth of only 11.6% compared to 20.42% for all combined months. From overall analysis of the winter demand may indicate a long term change in demand patterns, which will see a moving away from a winter buying model to that of a later fall model. This trend should be looked at closely to determine if leadership should make changes in inventory management to support the demand trend of its customers. Summer and Winter Data Comparison Both the summer and winter historical inventory data shows a few different trends and some similarities over the past four years. Both data sets show the demand increased from the first year during February and March. During year three, the demand had decreased for both summer and winter inventory during the months of February and August. The higher demand months for summer inventory are April with a total of 183,240 and May with a total of 174,300. The winter highest demand months over the four-year data are October and November. However, the summer data shows the demand to be the lowest over the four-year period during the months of November with a total of 87,890 and December with a total of 60,300. During the time period between years one through year four, the data shows a decrease during May at -18.15%, June at -16.19%, and November at -21.50% for the summer historical data. However, the summer demand was relatively lower during the months of April through July the second year, and July through September of the third year. The winter demand was up for May, July through September during the second year and July, September through December during the third year. Both inventory data shows demand increase during the month of September and both show a decrease during the second year in December. The winter data shows a decrease during the second year of 37,200. However, during the next two years demand increased during both months of November and December from year one to a combined total of 332,400. Overall, both inventories appear to change seasonally and show a large amount of growth in the past four years. During the time peak seasonal time periods for the winter demand, the summer demand is showing the opposite or slight decrease. There could be several factors, which could cause a dramatic change in the demand curve. The data could easily be manipulated by variables, such as the cost of the product, location, vendor availability, and market or competition. If there were a need or high-demand for the product, each one of these factors would either cause the inventory to remain high or too low. It is critical for the company to review analyze and study the trends over a certain period and compare it to the industry as whole. This action would allow the company to provide a better forecast when trying to meet customer needs and expectations. The company would need to strategically plan production and in accordance with the data analysis of the industry. After reviewing all data and thoroughly considering all aspects and possible variations of impact with the seasonal demand for both winter and summer, the company should be in a position to properly plan or forecast over the next few years based on a certain amount of historical data. Advantages There are several advantages of these two historical data systems. The company can review and evaluate the history in demand trends, whereas maintaining a certain level among the inventory. It also serves as a guide for ordering product throughout the year based on the year before. Developing the knowledge of what the prior year inventory sales or demand results were can help minimize the risk of having too much stock or too little. New inventory systems today come in a variety of packages which appear basic and other companies may have the software customizable. The inventory system can provide an understanding on were the inventory levels and sales should be at during each month. Disadvantages Although there are several advantages, there are also some disadvantages as well. For example, if the company has inventory scheduled for production toward the end of the year based on the data provided, for some unknown reason in year four, the company may find it hard to get rid of the inventory if an unexpected event should happened. For instance, there could be a major economic change or horrible weather conditions which may cause an impact on the level of inventory and demand forecast in year five. Conclusion. In conclusion, the report from both summer and winter inventory data shows an increase in demand over a four-year time frame. The trend would therefore suggest an increase in the future forecast for the next year. An increase in demand primarily would increase financial return and profitability. With the history showing primarily an increase in the demand curve during certain seasonal time periods and a decrease during other time frames, the University of Phoenix would be able to analyze the various variables provided by the data material. This would help the company forecast accordingly for the next four years, while making adjustments as necessary during economic changes. For many companies, it is important to make sure the data is correct and that the variables used are consistent with each year. It is also important to make sure the proper inventory system is chosen to meet the company’s needs as well as their customer’s needs. There are a variety of inventory systems companies can use, so it is critical to seek and research the best application that meets the requirements. This would require the company to review the advantages and disadvantages of each inventory system. References University of Phoenix. (Version 3). Summer Historical Inventory Data. Retrieved March 18, 2012, from University of Phoenix, QRB/501 website. University of Phoenix. (Version 3). Winter Historical Inventory Data. Retrieved March 18, 2012 from University of Phoenix, QRB/501 website.