Training and deploying models using global resource levels

A system comprising:

• at least one data processor;
• and
• memory storing computer executable instructions which, when executed by the at least one data processor causes the at least one data processor to perform operations comprising:
• receiving data characterizing a first output generated by one or more models of a first set of models associated with a first sub-organization of an organization, wherein the one or more of the first set of models is trained on a first dataset and a first set of resourcing levels corresponding to a first ratio of value per action or cost per action associated with the first set of models, and wherein the first set of resourcing levels defines an allocation of one or more resources to the first sub-organization;
• training one or more models of a second set of models associated with a second sub-organization of the organization based on a second dataset, one or more global constraints of the organization, and the first output generated by the first set of models;
• determining, by the one or more models of the second set of models, a second output indicative of performance under the first set of resourcing levels;
• assessing, based on the determined second output of the one or more of the second set of models, performance of the one or more models of the second set of models, wherein the assessed performance indicates an effectiveness of the allocated organizational resources relative to the first ratio of value per action or cost per action;
• and
• retraining the first set of models or a subset thereof based on the assessed performance.

A system comprising:

• at least one data processor;
• and
• memory storing instructions which, when executed by the at least one data processor, causes the at least one data processor to perform operations comprising:
• training a first model associated with a first sub-organization of an organization based on a first dataset, the first model including a first plurality of submodels trained at differing resource levels corresponding to a first ratio of value per action or cost per action associated with the first plurality of submodels, wherein the differing resource levels define an allocation of one or more resources related to the organization that are available to the first sub-organization;
• training a second model associated with a second sub-organization of the organization based on a second dataset, the second model including a second plurality of submodels trained at the differing resource levels based on global constraints of the organization;
• determining a resource allocation between the first organization and the second organization such that a first level of resource is provided to the first organization and a second level of resource is provided to the second organization based on an assessed performance indicating an effectiveness of the allocated organizational resources;
• selecting a first subgroup from the first model that corresponds to the first resource level;
• and
• selecting a second subgroup from the second model that corresponds to the second resource level.