The Period End (PE) Event is a way to alert buyers to products that did not perform the way they were expected to. K3S-Replenish® is constantly working to create the 'smartest' suggested orders for your company, but every month there will be a percentage that do not behave exactly as the system had predicted. Instead of a buyer having to constantly monitor every product they have to see which ones perform abnormally, K3S-Replenish® alerts the buyers to those products that need review. We call this the PE Event. 

After the completion of a period the Night Job will run the PE report. It will pop up when a buyer first signs onto K3S-Replenish® the following day (the screen is called Selected Products Review). The buyer should expect that 10% of all his products will produce a PE Check each month. A PE Check is a triggered flag to help identify what type of behavior a product is showing. K3S-Replenish® has a strict set of tolerances that if a product behaves even slightly abnormally will trigger one of these PE Checks. A buyer will go through his/her list and review each PE Check. Even though a product may produce a PE Check, a buyer should only expect to adjust 10% of the products flagged each time (or 1% total of all products). 

There are 5 basic groups that a product could be put into when a PE Check is triggered. These 5 groups are known as PE batches and are labeled in the system as PE1, PE2, PE3, PE4, and PE5. Note that products will only be classified into one group even though it may meet the criteria for others as well.

PE1 - Products that sold more than expected last period: A product is placed into this group because in the last period it sold significantly more than the average. Most of the time the product's spike is nothing more than a one time occurrence and no adjustment will need to be made. This is also known in the system as a Demand filter high check.

PE2 - Products that sold less than expected last period: A product is placed into this group because in the last period it sold significantly less than the average. Most of the time the product's dip is nothing more than a one time occurrence and no adjustment will need to be made. This is also known in the system as a Demand filter low check.

PE3 - Products that are starting to sell more over time:  A product is placed into this group because over time the product's demand has been increasing. Unlike a product spike (PE1) this product's inventory has shown strong substantial growth. A buyer would want to inspect the product to make sure the system is responding to the growth and make adjustments if needed. A product is likely to end up in a PE3 batch when you gain a customer because of the added demand. In the system, a PE3 check is also described as Tracking signal trending up.

PE4 - Products that are starting to sell less over time: A product is placed into this group because over time the product's demand has been decreasing. Unlike a product dip (PE2) this product's inventory has shown a steady substantial decrease. A buyer would want to inspect the product to make sure the system is responding to the decrease and make adjustments if needed. A product is likely to end up in a PE4 batch when you lose a customer because of the decrease in demand. In the system, a PE4 check is also described as Tracking signal trending down.

PE5 - Service level requirements not met: A product is placed into this group because the service level target was not met. This product might not be reaching the service target because the Average is too high, too low, or a seasonal profile needs to be put on or changed. 

When you are looking at a product within a PE batch, check the Average and the most recently completed period of history.  Compare those two values first, and then start looking at the other periods of history.  You may also need to check if the item has a Seasonal profile on it. 

Remember, this product has been put into a PE batch because the current Average and the most recently completed period of history do not ‘match’.  Your job is to do some investigating and decide why they don’t match. You may have to tweak some components of each product, for example: increase the Average, decrease the Average, use F21=History to re-average, put on a seasonal profile, take off a seasonal profile, or change the seasonal profile.  However, chances are you will not need to adjust anything at all!