Utilizing machine learning models to generate and monitor progress of a strategic plan

A device, comprising:

• one or more memories;
• and
• one or more processors, coupled to the one or more memories, configured to:
• receive entity data identifying an entity associated with generating and implementing a strategic plan;
• identify harvested templates, contract profiles, and commitment accuracy scores associated with strategic plans, based on the entity data;
• process the harvested templates, the contract profiles, and the commitment accuracy scores, with a first machine learning model, to generate a first plurality of templates;
• process the harvested templates, the contract profiles, and the commitment accuracy scores, with a second machine learning model, to generate a second plurality of templates;
• process the first plurality of templates and the second plurality of templates, with a third machine learning model, to generate a final plurality of templates and final rankings for the final plurality of templates;
• select a template from the final plurality of templates based on the final rankings;
• process the template, with a fourth machine learning model, to identify deliverables associated with the template;
• generate a strategic plan based on the template and the deliverables;
• cause the strategic plan to be implemented;
• and
• track a progress of implementation of the strategic plan.

A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising:

• one or more instructions that, when executed by one or more processors of a device, cause the device to:
• receive entity data identifying an entity associated with generating and implementing a strategic plan;
• identify harvested templates, contract profiles, and commitment accuracy scores associated with strategic plans, based on the entity data;
• process the harvested templates, the contract profiles, and the commitment accuracy scores, with a first machine learning model, to generate a first plurality of templates;
• process the harvested templates, the contract profiles, and the commitment accuracy scores, with a second machine learning model, to generate a second plurality of templates;
• process the first plurality of templates and the second plurality of templates, with a third machine learning model, to generate a final plurality of templates and final rankings for the final plurality of templates;
• select a template from the final plurality of templates based on the final rankings;
• process the template, with a fourth machine learning model, to identify deliverables associated with the template;
• generate a strategic plan based on the template and the deliverables;
• cause the strategic plan to be implemented;
• utilize a fifth machine learning model, with the strategic plan and progress data identifying progress of implementation of the strategic plan, to identify milestone delays;
• utilize a sixth machine learning model, with the milestone delays, to generate one or more recommendations to mitigate the milestone delays;
• and
• cause the one or more recommendations to be implemented.