Optimizing supply chains

A computer-implemented method comprising:

• obtaining sales data from over a time span, the sales data pertaining to an inventory associated with a product or service;
• determining, from the sales data, a number of stock-out events in the inventory and the corresponding timing of the stock-out events, each of the stock-out events being an event in which the inventory fails to satisfy a threshold condition;
• determining a probability distribution representing a distribution of the stock-out events;
• estimating adjusted time locations of the stock-out events based on the probability distribution, the adjusted time locations accounting for one or more censoring effects of the sales data;
• generating, based on the adjusted time locations of the stock-out events, a model that accounts for one or more censoring effects of the sales data;
• and
• determining, based on the model, one or more parameters representing the one or more censoring effects of the sales data.

A system comprising one or more computers and one or more storage devices on which are stored instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising:

• obtaining inventory data associated with a product or service;
• generating, using the inventory data, a monotonically increasing function indicative of cumulative demand;
• predicting future inventory events using the monotonically increasing function and a machine learning model that includes survival curve analysis;
• in response to predicting future inventory events using the monotonically increasing function of data and survival curve analysis, generating an instruction configured to procure one or more items of inventory;
• and
• transmitting the instruction to an inventory system.