Optimizing Economic Order Quantity (EOQ) Inventory models for calculating optimal order quantities and reorder points have been in existence long before the arrival of the computer. When the first Model T Fords were rolling off the assembly line, manufacturers were already reaping the financial benefits of inventory management by determining the most cost effective answers to the questions of When? and How much?. Yes long before JIT, TQM, TOC, and MRP, companies were using these same (then unnamed) concepts in managing their production and inventory. I recently read Purchasing and Storing, a textbook that was part of a Modern Business Course at the Alexander Hamilton Institute in New York. The textbook published in 1931 (thats right 1931) was essentially a how to book on inventory management in a manufacturing environment. If youre wondering why I would want to read a 70-year-old business text, my answer would be that the fundamental concepts of managing a business change very little with time, and reading about these concepts in a vintage text is a great way to reinforce the value of the fundamentals. The occasional reference to The War (referring to WWI) also keeps it interesting and the complete absence of acronyms is refreshing. As you may have guessed, this 70-year-old book contained a section on Minimum Cost Quantity, which is what we now refer to as Economic Order Quantity (EOQ). I can imagine that in the 1930s an accountant (or more likely a room full of accountants) would have calculated EOQ or other inventory related formulas one item at a time in a dimly lit office using the inventory books, a mechanical adding machine and a slide rule. Time consuming as this was, some manufacturers of the time recognized the financial benefits of taking a scientific approach to making these inventory decisions. So why is it that, in these days of advanced information technology, many companies are still not taking advantage of these fundamental inventory models? Part of the answer lies in poor results received due to inaccurate data inputs. Accurate product costs, activity costs, forecasts, history, and lead times are crucial in making inventory models work. Ironically, software advancements may also in part to blame. Many ERP packages come with built in calculations for EOQ which calculate automatically. Often the users do not understand how it is calculated and therefore do not understand the data inputs and system setup which controls the output. When the output appears to be "out of whack" it is simply ignored. This sometimes creates a situation in which the executives who had purchased the
Optimizing Economic Order Quantity (EOQ) Inventory models for calculating optimal order quantities and reorder points have been in existence long before the arrival of the computer. When the first Model T Fords were rolling off the assembly line, manufacturers were already reaping the financial benefits of inventory management by determining the most cost effective answers to the questions of When? and How much?. Yes long before JIT, TQM, TOC, and MRP, companies were using these same (then unnamed) concepts in managing their production and inventory. I recently read Purchasing and Storing, a textbook that was part of a Modern Business Course at the Alexander Hamilton Institute in New York. The textbook published in 1931 (thats right 1931) was essentially a how to book on inventory management in a manufacturing environment. If youre wondering why I would want to read a 70-year-old business text, my answer would be that the fundamental concepts of managing a business change very little with time, and reading about these concepts in a vintage text is a great way to reinforce the value of the fundamentals. The occasional reference to The War (referring to WWI) also keeps it interesting and the complete absence of acronyms is refreshing. As you may have guessed, this 70-year-old book contained a section on Minimum Cost Quantity, which is what we now refer to as Economic Order Quantity (EOQ). I can imagine that in the 1930s an accountant (or more likely a room full of accountants) would have calculated EOQ or other inventory related formulas one item at a time in a dimly lit office using the inventory books, a mechanical adding machine and a slide rule. Time consuming as this was, some manufacturers of the time recognized the financial benefits of taking a scientific approach to making these inventory decisions. So why is it that, in these days of advanced information technology, many companies are still not taking advantage of these fundamental inventory models? Part of the answer lies in poor results received due to inaccurate data inputs. Accurate product costs, activity costs, forecasts, history, and lead times are crucial in making inventory models work. Ironically, software advancements may also in part to blame. Many ERP packages come with built in calculations for EOQ which calculate automatically. Often the users do not understand how it is calculated and therefore do not understand the data inputs and system setup which controls the output. When the output appears to be "out of whack" it is simply ignored. This sometimes creates a situation in which the executives who had purchased the