Forecasting nventory - Speech or Presentation Example

Topic:  Forecasting Inventory Forecasting is an important part of decision making. The research focuses on using SPSS and Excel to arrive at the trend line generated from the 2007 to 2010. The research focuses on estimating the projected inventory for the four months after the end of 2010. Forecasting inventory aids in making better inventory –related management decisions. Ronald Nowczyk (1988) emphasized the inventory system is based on physical count. The warehouse clerk counts and records the actual number of inventory for two months.

The inventory shows that inventory count fluctuates seasonally. There are months where the inventory is highest. There are months when the inventory counts indicate low numbers. The inventory fluctuation is needed in order to prepare for the months where there is a strong demand for the products. The above time series graph shows that the inventory fluctuates from during the six inventory counts during the year. The graph shows that the inventory count drops as the year ends and the new year begins.

The graph indicates that the inventory count at the end of each year is higher than the inventory count of the prior year’s inventory count. In the same manner, the inventory count of the months of March and April in one year is usually higher than the inventory count of the inventory count for the year. Likewise, the inventory count of the months of August and September in one year is usually higher than the inventory count of the inventory count for the year. In addition, the data gathered is converted to an index for each year.

The computations for the four years are shown below as follows, based on the time series data from the index table. Inventory year   Inventory year Jan-Feb 2007 6,500. Jan-Feb 2008 7500 Mar-Apri 2007 7,000. Mar-Apri 2008 9000 May-Jun-2007 8,000. May-Jun-2008 10000 Jul-Aug 2007 8,500. Jul-Aug 2008 12000 Sep-Oct 2007 10,000. Sep-Oct 2008 13400 Nov-Dec 2007 20,000. Nov-Dec 2008 25009 Index 10,000 Index 12818 The above computation shows the index for the year 2007 amounting to 7,883 units.

The index for the year 2008 shows an index of 12,818 for the entire year. Year Inventory Year Inventory Jan-Feb 2009 8,200 Jan-Feb 2010 10000 Mar-Apri 2009 10,200 Mar-Apri 2010 14000 May-Jun-2009 12,000 May-Jun-2010 15000 Jul-Aug 2009 14,000 Jul-Aug 2010 15500 Sep-Oct 2009 17,200 Sep-Oct 2010 20200 Nov-Dec 2009 28,000 Nov-Dec 2010 32000 Index 14,933 Index 17873 The above computation shows the index for the year 2009 amounting to 15,933 units.

The index for the year 2010 shows an index of 18,617 for the entire year. Slope of the line = 590 computed using excel formula. In addition, the regression coefficient is shown below as follows: Model Summary(b) Model R R Square Adjusted R Square 1 .607(a) .368 .340 The above data shows that the R square is .368 and the Adjusted R square is .340. The constant predictor is the year factor. The dependent variable is the inventory count. Residuals Statistics(a) Minimum Maximum Mean Std. Deviation N Predicted Value 7145.

7534 20621.6641 13883.7083 4143.00319 24 Std. Predicted Value -1.626 1.626 .000 1.000 24 Standard Error of Predicted Value 1135.468 2196.033 1563.188 356.262 24 Adjusted Predicted Value 7265.7153 20009.5625 13852.2047 4113.60106 24 The above SPSS computation shows that the predicted value of the trend for future inventory for the first 4 mounts of the year 2011 will have minimum value of 7146 items. The dependent variable is inventory count. In addition, the above SPSS computation shows that the maximum amount of inventory will be 20,522 items for the first four months of the year 2011.

The SPSS computation above indicates that the mean of the projected inventory is 13,884 units. The above table also shows that the standard deviation is 4,143 units of inventory. Based on the above discussion, Forecasting is a very significant part of management’s decision making activities. The research shows that SPSS and Excel can hasten and improve management’s decision making activities by presenting more reliable historical inventory trend analysis. The historical analysis is based on actual inventory data generated from the 2007 to 2010.

The research indicates the projected inventory for the four months after the end of 2010 can be easily forecasted with the use of SPSS, excel software and past historical inventory data. Indeed, inventory forecasting enhances management’s inventory –related decisions. Reference: Nowaczyk, R. (1988), Introductory Statistics for Behavioral Research, N.Y., London, Sydney, Hot, Rinehart & Winston Press