- A backorder is an order for a good or service that cannot be filled at the current time due to a lack of available supply. The item may not be held in the company's available inventory but could still be in production, or the company may need to still manufacture more of the product.
- The backorder is an indication that demand for a company's product outweighs its supply. They may also be known as the company's backlog. Also, company cannot overstock every product in their inventory to avoid such situation.
- If a company consistently sees items in backorder, this could be taken as a signal that the company's operations are far too lean. It may also mean the company is losing out on business by not providing the products demanded by its customers. If a customer sees products on backorder—and notices this frequently—they may decide to cancel orders, forcing the company to issue refunds and readjust their books.
- There has to be a way for the company to know for which products they can face this problem. So, the company has shared a data file with different input features for each product and it hopes to find a pattern inside this data which can give them some insight.
- The data file contains the historical data for some weeks prior to the week we are trying to predict.
The data has 23 columns including 22 features and one target column.
To model and predict the target, we’ll use the features columns, which are:
sku – Random ID for the product
national_inv – Current inventory level for the part
lead_time – Transit time for product (if available)
in_transit_qty – Amount of product in transit from source
forecast_3_month – Forecast sales for the next 3 months
forecast_6_month – Forecast sales for the next 6 months
forecast_9_month – Forecast sales for the next 9 months
sales_1_month – Sales quantity for the prior 1 month time period
sales_3_month– Sales quantity for the prior 3 month time period
sales_6_month – Sales quantity for the prior 6 month time period
sales_9_month – Sales quantity for the prior 9 month time period
min_bank – Minimum recommend amount to stock
potential_issue – Source issue for part identified
pieces_past_due – Parts overdue from source
perf_6_month_avg – Source performance for prior 6 month period
perf_12_month_avg – Source performance for prior 12 month period
local_bo_qty – Amount of stock orders overdue
deck_risk – Part risk flag
oe_constraint – Part risk flag
ppap_risk – Part risk flag
stop_auto_buy – Part risk flag
rev_stop – Part risk flag
went_on_backorder – Product actually went on backorder. This is the target value.