Utilizing machine learning and predictive modeling to manage and determine a predicted success rate of new product development

A device, comprising:

• one or more memories;
• and
• one or more processors, communicatively coupled to the one or more memories, configured to:
• provide, to one or more client devices and server devices, one or more tools to enable development of a new product via the one or more client devices and server devices;
• receive, from the one or more tools, current project data identifying a current project for developing the new product;
• receive historical project data identifying historical projects for developing historical products;
• receive industry data associated with the new product;
• process the current project data, the historical project data, and the industry data, with a machine learning model, to identify one or more variables for a predictive model,
• wherein the machine learning model is trained based on:
• prior project data identifying a prior project for developing a prior product,
• the historical project data, and
• particular industry data associated with the prior product;
• process the one or more variables, with the predictive model, to predict a predicted success rate of the current project;
• and
• perform one or more actions based on the predicted success rate of the current project.

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

• one or more instructions that, when executed by one or more processors, cause the one or more processors to:
• provide, to one or more client devices and server devices, one or more tools to enable development of a new product via the one or more client devices and server devices;
• receive, from the one or more tools, current project data identifying a current project for developing the new product;
• receive historical project data identifying historical projects for developing historical products;
• receive industry data associated with the new product;
• process the current project data, the historical project data, and the industry data, with a machine learning model, to identify one or more variables for a predictive model;
• process the one or more variables, with the predictive model, to predict a predicted success rate of the current project;
• and
• perform one or more actions based on the predicted success rate of the current project.