by Jon Schreibfeder | Aug 5, 2019 | Best Practices, Consulting, Forecasting, Order Cycles, Purchasing, Replenishment Parameters, Replenishment Source, Stocking Decisions
Using Residual Inventory Analysis in Fine Tuning Your Safety Stock Quantities 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...
by Jon Schreibfeder | Jul 10, 2019 | Analysis, Best Practices, Forecasting, Order Cycles, Purchasing, Replenishment Parameters, Stocking Decisions
Protecting Customer Service – Part 2 Last month we began a discussion of safety stock. That is, “insurance inventory” to protect against unusually high demand or delays in receiving a replenishment shipment from the supplier of an item. Though we found...
by Jon Schreibfeder | Jun 10, 2019 | Best Practices, Forecasting, Order Cycles, Replenishment Parameters, Replenishment Source, Stocking Decisions
Protecting Customer Service – Part 1 Over the last several months, we have been discussing when to order products in order to meet your customers’ expectations of product availability. We have explored various methods for calculating accurate forecasts and...
by Jon Schreibfeder | May 17, 2017 | Forecasting
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...
by Jon Schreibfeder | Apr 15, 2017 | Forecasting, Stocking Decisions
What Affects Forecasts Other Than Past Usage Most computers systems calculate forecasts of future demand based on past sales or usage. The theory is that what you sold or used in the past is a good indication of what you will sell or use in the future. But there are...
by Jon Schreibfeder | Mar 15, 2017 | Forecasting
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...
