THE BUSINESS OF PRACTICE: STRATEGY IN ACTION Table 4. Inventory Cost Savings Over a 5-Month Period by Improving Forecast Accuracy


Demand Forecast at a PE of 16.7%


Demand forecast Quantity per order Purchase cost Holding cost Order cost


Total actual inventory cost (for the 5-mo period) Savings over the original 16.7% PE forecast


140 28


$28,196.00 $411.19 $50.00


$28,657.19


Demand Forecast at a PE of 8.3%


130 26


$26,182.00 $381.82 $50.00


$26,613.82 $2,043.37 (7.68%)


Demand Forecast at a PE of 8.3% Using EOQ


130


9.4 (as calculated by EOQ) $26,182.00 $138.17 $138.17


$26,458.34 $2,198.85 (8.31%)


Abbreviation: EOQ, economic order quantity. Actual sales  120 units; per unit cost with tax  $201.40; yearly holding rate  35%; per order cost  $10; ordered equal amount per month for 5 months except when using EOQ.


forecasting increases revenue by reducing shortage costs and decreases cost of goods sold by decreasing the holding costs associated with excess inventory. At the same time, the reduced inventory capital investment reduces working capital requirements, which reduces the practice’s cash flow toward inven- tory. More importantly, the increase in gross profit margin and decrease in working capital require- ments lead to an increase in profitability and share- holder value.


5. Translating Improved Forecasting Accuracy Into Cost Savings


As previously described by the author,1 the total actual inventory cost is comprised of the purchase cost, holding cost, and order cost. As defined by the formulas presented in the Appendix, the forecasted demand is a key component of the calculations. The example that follows in Table 4 presents a real- life situation where minimization of PE and MAPE led to a better demand forecast and, in turn, a re- duced cost of inventory. In addition, the example presents how going one step further within the pro- cess of lean inventory management through the cal- culation of the economic order quantity further enhanced the cost savings that was originally started by the improved demand forecast. The example in Table 4 clearly indicates how im- proving the forecasting accuracy led to a savings of 8.3% on just this one inventory item. The gener- ated savings go directly into increasing the bottom line by increasing gross profit margin and increasing profits net of taxes, a scenario that directly trans- lates into increased shareholder value.


6. Measuring the Efforts


The efforts toward not having too much inventory on hand can easily be measured through the observed change in inventory turnover (see Appendix); a re- duced amount of average inventory on hand (the formula’s denominator), thanks to better forecast- ing, resulting in an increase in inventory turns. Attention should be paid, however, to the concurrent efforts at reducing cost of goods sold (COGS)


540 2015  Vol. 61  AAEP PROCEEDINGS


(through the use of economic order quantity analysis or through better pricing attainment, for example) as the reduction in the formula’s numerator (COGS) will artificially reduce the calculated inventory turns; to the point that an equal percentage reduc- tion in COGS and in average inventory on hand will result in an unchanged calculation of inventory turns. For this reason, measurement of inventory turns should be made with knowledge of changes in COGS given that the costs of the inventory will affect not only the total cost of goods, but also the cost of the inventory on hand. A second method of measuring inventory turns that is only based on demand and order quantity takes away the effects created by unit cost on the previously described turnover calculation and gives a more precise eval- uation of inventory usage. Re-arrangement of this formula provides the useful measure of days of sup- ply, which will also allow the practitioner to monitor the results of improved forecasting. Efforts toward avoiding shortage costs associated


with too little inventory on hand cannot necessarily be measured through total revenues other than hav- ing personal knowledge of having lost a client’s busi- ness to a competitor. The effort to go lean through calculating the economic order quantity should be accompanied by the calculation of a reorder point (see Appendix), which will trigger an order and therefore avoid running out of inventory that allows the provision of service. Although measuring shortage costs cannot be done other than through gut feeling, implementation of a reorder point will prevent the shortage costs because the inventory will be reordered before running out.


7. Conclusion


To properly analyze forecasting accuracy, the veteri- nary practitioner must use simple statistics measure- ments that compare with a perfect forecast. PE and MAPE represent a percentage-based analysis of how far off the forecast was from the actual demand, and provide a continuous measurement to evaluate accu- racy of estimation over time. Changes in the fore- casting technique to reduce PE and MAPE will lead to


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