A computer-implemented method including accessing an order history that, for each of one or more past orders, indicates (i) one or more order details associated with the order, and (ii) a fulfillment outcome associated with the order, wherein the order fulfillment outcome is selected from among multiple pre-defined order fulfillment outcomes including one or more intended order fulfillment outcomes and one or more unintended order fulfillment outcomes, for each of one or more particular unintended order fulfillment outcomes, selecting one or more particular past orders that are associated with the particular unintended order fulfillment outcome, for each of the one or more particular unintended order fulfillment outcomes, generating, using the one or more order details associated with the one or more particular past orders that are associated with the particular unintended order fulfillment outcome as training data, a predictive model that is trained to estimate, based on one or more given order details associated with a given order, a likelihood that the given order will be associated with the particular unintended order fulfillment outcome, receiving one or more order details associated with a subsequently received order, for each of the predictive models, providing the one or more order details as input to the predictive model, in response to providing the one or more order details as input to the predictive model, receiving, from each of the predictive models, a likelihood that the one or more order details will be associated with the particular unintended order fulfillment outcome, determining, for each indication of the likelihood, whether the likelihood satisfies a threshold, for likelihoods that satisfy the threshold, determining a remedial action that, when implemented, adjusts the likelihood to not satisfy the threshold, wherein determining the remedial action includes selecting actions from a group of predetermined actions stored in an actions database, applying the selected actions to the one or more given order details associated with the subsequently received order to create revised order details, and providing the revised order details as input to the predictive model to determine whether the remedial action determined based on the revised order details, when implemented, will adjust the likelihood to not satisfy the threshold, providing, for output, data indicating the remedial action, and preventing an order associated with the one or more order details associated with the subsequently received order from processing until execution of the remedial action. -0> L4o 0 0) N0 cN a N 0 C,4 -7 >~Cl >~> _ >-0 (N ) 0 a) >a)CD N- nEF '( -I- LE5 0N CN mcn a) U0 > N- C U = CD 77 cu 2 CD 0 a~ a E a)C) LOL CDCDC .=a)- -0:a (D-. 0 = 73U ne I > 0~ nn Cl) coI U CU Nnn I U 00/))
PREDICTIVE MODELING FOR UNINTENDED OUTCOMES