Exceutive management presentation

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The importance of management

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  • Just-In-Time (JIT) is an inventory system used by Gilbarco. With Just –In-Time production and the purchase of materials do not begin until a customer places an order for a product.. This allows Gilbarco to shrink their inventories to lower quantities or not having any on hand all. JTI has had many direct effects on the following inventories: raw material, work in process, finished goods. Old inventory systems would require the companies to have large quantities of resources to avoid any production problems. JIT allows enough materials to be purchased in order to cover the needs daily.
  • Gilbarco uses forecasting methods to predict current and future trends. Gilbarco uses the information to determine if the company will break even and if the company does not do well they can decide if the company will be able to maintain production the next year. The index is a point of reference concerning numbers with common points. Indices are used to observe historical and short-term comparisons with percentages change and commonly used. The chart above is example raw data that Gilbarco uses to help forecast the next five years.
  • The normal distribution is important because it describes the statistical behavior of Gilbarco inventory. The shape of the normal distribution is completely described by the mean and the standard deviation . Normal distribution curve is a statistical function that describes how data behaves around any given mean. Also known as a Gaussian distribution or bell curve, a normal distribution curve allows statisticians to analyze data and make predictions
  • The measure of dispersion that most accurately depicts inventory data is standard deviation. When you look at measuring dispersion you are looking to see how the entire spread of data actually measures to each other. Standard deviation presents how much the data will deviate from the normal number.
  • Data Source: University of Phoenix The table above shows the Frequency and Normal Distribution Data during the Winter Season. This was created to show the different results of Mean, Median, Mode, Range, and Standard Deviation.
  • Exceutive management presentation

    1. 1. KAREN FAITH ADAMS, KAREN JONESQRB/501 – QUANTITATIVE REASONING FOR BUSINESS MARCH 26, 2012 ARI RAHMAN
    2. 2. Introduction Inventory management systems are a vital part of businesses Observing inventory levels is necessary for creating revenue and profits. Mangers need to develop , analyze frequency distributions, locate the mean, median and mode and show a normal distribution of raw data collect
    3. 3. Just-In-Time Inventory System Production and the purchase of materials do not begin until a customer places an order for a product. Eliminates waste and makes the company efficient Companies are able to do away with their warehouses Funds that were tied up in inventories can be used elsewhere Defect rates are reduced, resulting in less waste and greater customer satisfaction
    4. 4. Typical Seasonal Demand for Winter Highs Actual Demands (in units)Month Year 1 Year 2 Year 3 Year 4 1 55,200 39,800 32,180 62,300 2 57,350 64,100 38,600 66,500 3 15,400 47,600 25,020 31,400 4 27,700 43,050 51,300 36,500 5 21,400 39,300 31,790 16,800 6 17,100 10,300 31,100 18,900 7 18,000 45,100 59,800 35,500 8 19,800 46,530 30,740 51,250 9 15,700 22,100 47,800 34,400 10 53,600 41,350 73,890 68,000 11 83,200 46,000 60,200 68,100 12 72,900 41,800 55,200 61,100Avg.
    5. 5. Measure of Dispersion
    6. 6. Winter Historical Inventory Data Frequency/Normal Distribution Month Year 1 Year 2 Year 3 Year 4 1 15,400 10,300 25,020 16,800 2 15,700 22,100 30,740 18,900 3 17,100 39,300 31,100 31,400 4 18,000 39,800 31,790 34,400 5 19,800 41,350 32,180 35,500 6 21,400 41,800 38,600 36,500 7 27,700 43,050 47,800 51,250 8 53,600 45,100 51,300 61,100 9 55,200 46,000 55,200 62,300 10 57,350 46,530 59,800 66,500 11 72,900 47,600 60,200 68,000 12 83,200 64,100 73,890 68,100 MEAN 38,113 40,586 44,802 45,896MEDIAN 24,550 42,425 43,200 43,875 MODE Non-Modal Non-Modal Non-Modal Non-ModalSTDEV 24739.13099 13336.54409 15407.74471 19185.84301RANGE 67,800 53,800 48,870 51,300
    7. 7. Conclusion Forecast accuracy is a critical component of Gilbarco’s success in today’s markets, particularly when competing on a global scale. Inventory is Gilbarco’s largest asset Forecasting techniques are quantitative. Quantitative techniques of forecasting are best used when changes are infrequent.
    8. 8. • Accounting For Management. (2011). Retrieved fromhttp://www.accountingformanagement.com/just_in_time.htm• University of Phoenix. (2012). Winter Historical InventoryData, University of Phoenix Material.. Retrieved from University ofPhoenix

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