Average vs Anticipated Lead Times

Published on: May 17, 2017

Maintaining a high level of customer service is primarily dependent on when you reorder a product.  For example, let’s say you sell two pieces of a product per day, and the item has a seven-day lead time.  That is, it takes seven days to receive a product once it has been ordered from your supplier.  […]

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What Your Buyers Should be Doing – Part V

Published on: March 15, 2017

Determine the Best Forecast Formula Last month, we discussed the fact that a single forecast formula will not accurately predict future usage for all your stocked products.  But how do you determine the best forecast formula to use for each item? We have found that the best way to predict future demand of an item […]

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What Your Buyers Should be Doing – Part IV

Published on: February 15, 2017

Understanding the Elements of a Forecast A demand forecast is a prediction of the quantity of a specific product that will be sold or used in an upcoming time period (usually a month).  The accuracy of your forecast is a determining factor in whether or not you will achieve effective inventory management. Most organizations base […]

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What Your Buyers Should be Doing – Part III

Published on: January 20, 2017

Monitoring Your Forecast Accuracy Replenishment capabilities in most computer software packages answer two vital questions:   When a stocked item needs to be reordered to avoid a stockout? How much of the product should be ordered?   A critical factor in answering these questions is an accurate prediction of what will be sold, transferred or […]

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What Your Buyers Should be Doing – Part II

Published on: December 15, 2016

Most organizations are continually buying new products.  Unfortunately, part of the quantity of many of these items is “D.O.A.” or dead on arrival.  That is, you do not sell the entire initial purchase quantity.  For example, you might buy a case of 48 pieces of an item.  You sell a total of 20 pieces. And […]

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Collaborative Forecasting – Part II

Published on: August 15, 2016

Often the best sources of this information are your customers.  Indeed, the term “collaborative forecast” refers to a cooperative effort between you and your customers to derive an accurate demand forecast.  But, we have found that collaborative information from many customers tends to be far greater than subsequent sales or usage.  Why?   If they […]

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Collaborative Forecasting, Part I

Published on: July 15, 2016

Most computer systems forecast future demand of products based on past usage history.  These systems assume that what you sold or used in the past is a good indication of what you will sell or use in the future.  But this isn’t always true.  For example:   Products may increase or decrease in popularity over […]

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How Often Should You Order from a Vendor?

Published on: April 15, 2016

This month we will begin to examine the last of the parameters used to determine when to reorder a product, the order cycle (also known as the review cycle). The order cycle is the normal time between issuing replenishment orders with a supplier that meet that vendor’s target order requirement. The target order requirement is […]

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Use Residual Inventory Analysis to Fine Tune Safety Stock Quantities

Published on: March 16, 2016

Over the last several months, we have been discussing various ways of calculating safety stock quantities. If safety stock quantities are too low, they will not provide adequate insurance to prevent stockouts in case of unusually high demand or delays in receiving a replenishment shipment. If safety stock quantities are too high, part of your […]

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How Do You Know if Your Computer Is Set Up Correctly Part IV (A Better Way to Calculate Safety Stock)

Published on: February 15, 2016

Last month we began our discussion of safety stock. Safety stock is “insurance” inventory you maintain for a product to prevent stockouts due to unexpected demand or delays in receiving a replenishment shipment. Most systems calculate safety stock quantities based on a number of day’s supply or a percentage of anticipated lead time usage. These […]

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