Uop Qrb/501 – Quantitative Reasoning for Business

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Inventory Proposal

QRB/501 – Quantitative Reasoning for Business
University of Phoenix
September 6, 2010
Mr. John Carroll

Inventory Proposal
This proposal is for a solution for an inventory problem within an organization. The details of the organization’s business operations are established and the problem identified so a potential solution may be formulated and proposed. The expected benefits to the organization are also examined as the motivation for implementation. Additionally, an inventory index is used to compare and contrast historical trends leading to the inventory problem and supporting evidence is presented through a histogram and slope-intercept calculations.

Organization
Vertical Entertainment (VE) is a fireworks wholesaler headquartered in Austin, Texas. VE has been in business since 2005 and provides fireworks products through business-to-business and business-to-consumer channels. The organization’s key segments are the small-box retailers and fireworks display companies. The small-box retailers account for increased volume during the summer months (e.g. 4th of July) whereas the fireworks display companies purchase goods year-round. In recent years VE has expanded to direct sales via the company website.

Inventory Problem
VE purchases all firework inventories directly from China and they arrive in roughly 12 weeks. Product backorder usually result in lost sales because most events are time specific. The main inventory issue for VE is reducing stale inventory. Although stale inventory affects several key areas, the main focus is the effect on the company’s cash flow. Purchasing too much inventory and relaxed return policies results in 5% of VE product inventory to be stale.

Expected Benefits
The goal of this proposal is to reduce stale inventory from 5% to 3% of the total inventory. This reduction will provide VE with much needed cash flow, increase the profit margin, and reduce seasonal temporary warehousing needs.

Use of Indices as Vehicle for Solution
Indices are used to analyze changes in data overtime and to predict what causes the fluctuations. Companies use this information to estimate periods of increased sales and inventory needs more accurately. The University of Phoenix Summer Historical Inventory Data provided does not describe what the data is measuring or what the indices expect to forecast. When analyzing data any period may be used; however the only way the data is meaningful is to fully understand what the historic data is trying to predict or analyze. For example, the Consumer Price Index (CPI) predicts the price of goods in relation to years past and measures inflation. In 2008 the CPI rose .1% and in 2009 the CPI rose 2.7%. 1982 is the base year used in calculating the indices for 2008 and 2009 (Thredgold, Jeff, 2010). This change shows a 2.6% increase in the price of goods in one year indicating the inflation rate. Information provided by the University of Phoenix does not state the units of measurement (e.g. inventory units or dollar amounts) necessary to analyze changes in the indices over time for the purpose of accurately forecasting future inventory. For forecasting purposes some assumptions must be made. The first assumption is that the data provided is total inventory value in dollars. The second assumption is relative supply cost of inventory does not change from Year 1 to Year 5. Given these assumptions the data can be converted to indices and a forecast for Year 5 can be made from the University of Phoenix Summer Historical Data listed in Table 1 (University of Phoenix, 2010). Table 1. Summer Historical Inventory Data.

Inventory Data| Year 1| Year 2| Year 3| Year 4| Year 5| Month 1| 18,000| 45,100| 59,800| 35,500| 31,536|
Month 2| 19,800| 46,530| 30,740| 51,250| 46,754|
Month 3| 15,700|...
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