Summary
Blanket Sales Orders are orders from your customers over a long duration. From their perspective, it is a blanket PO, e.g. a commitment to buy quantity over a long period of time.
StockIQ can help you plan for this using the Blanket Sales Order feature.
Blanket Sales Orders can be provided from an interface with your ERP or entered manually through the System Configuration > Blanket Sales Orders screen GUI.
Column Description
- Item, Site - The item and site for which there is a blanket
- Customer Ship To - the specific customer that has sent the blanket order. All blanket sales orders must be associated with a customer.
- Blanket SO #, Line # - The number for the blanket. When data is coming from the ERP, the order number and line number should be provided. If you are entering them by hand, StockIQ can generate these for you.
- Quantity - The expected TOTAL quantity of the blanket (not the month-by-month or week-by-week value)
- Invoice Price - any special price that you are going to give the customer on this blanket. Not used for any calculations, just an FYI field.
- Start Date - start date for the blanket time period
- End Date - end date for the blanket time period. These date ranges are used to determine the average monthly or weekly quantity expected on the blanket.
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Begin Update After Days - Very often, the quantity the customer gives you is an estimate, rather than a firm quantity.
- If this is the case, then you can have StockIQ start to update the actual uplift quantity expected after a certain time has passed with the blanket being active. For example, if the customer says they were going to purchase 100 per month of this item, but 3 months have passed with only 30 units purchased, we would recalculate the expected volume to be 10 per month instead.
- If your quantities are indeed firm commitments from the customer, and they MUST buy the listed quantity, then leave this field empty. StockIQ will continually adjust the uplift events created for the blanket to represent the remaining quantity the customer must buy.
- Front Load Periods - Often when receiving a large blanket, you may need to purchase ahead somewhat to ensure you can meet initial demand. If you choose to front-load the demand by some amount, then the first month/week of uplift events created by StockIQ will be larger accordingly.
- Percent Confidence - You can enter an initial percent confidence in your customer's numbers to have StockIQ only create uplift for a portion of the expected quantity. For example, if they've created a blanket for 1000 units over 10 months, rather than 10 months of +100 events, if you put a 60% confidence, you will get 10 months of 60 unit uplift.
Troubleshooting
The benefit of knowing the Blanket Sales Order is twofold, first, for when the blanket is ongoing and in the future, and secondly, for when it is completely or partially in the past.
Future/Upcoming Periods
For periods in the future, StockIQ will create events to help you plan for the uplift. These events are initially created as such:
Event Period Quantity = (Blanket Quantity) / (Blanket # of Periods)
for example:
100 = (1000 units on blanket) / ((10/1/2020) - 1/1/2020))
100 = (1000 units on blanket) / (10 months)
100 units per month of event quantity
If you have a percent confidence, this per-period estimate is then adjusted by the blanket's percent confidence amount.
If you have set a non-null value for the "Begin Update After Days...", then after that number of days has passed since the blanket start date, StockIQ will evaluate what the customer has purchased of that item since the blanket started, and begin using that average purchase quantity and average purchase interval to predict their remaining purchases, rather than use the estimated values originally provided by the customer. Details of this will be shown in the Blanket Sales Order Detail Dialog.
Past Periods
While a product is on a blanket sales order, StockIQ assumes that any sale to that customer is against that blanket.
As these purchases move into the past, StockIQ will create events for these purchases against the blanket. This will keep the forecast algorithm from starting to artificially inflate forecasted demand due to purchases on the blanket order.
Further into the future, once the blanket is completely over, all quantities purchased by the customer will be "evented out" in this way, so if the blanket is one-time and non-repeating, your baseline forecasts will not be artificially inflated due to this blanket behavior, thus increasing forecast accuracy moving forward.