Skills gap management platform

A device, comprising:

• one or more memories;
• and
• one or more processors, communicatively coupled to the one or more memories, configured to:
• receive a set of role skills data that identifies one or more role skills associated with a role;
• receive a set of worker skills data that identifies one or more worker skills associated with a worker;
• receive a set of skill proximity data that identifies one or more proximity values, wherein a proximity value of the one or more proximity values quantifies a relationship between a first skill of the one or more role skills or the one or more worker skills and a second skill of the one or more role skills or the one or more worker skills;
• generate a weighted directed graph, comprising a network of a plurality of nodes and a plurality of edges, based at least in part on the set of role skills data, the set of worker skills data, and the set of skill proximity data;
• determine a plurality of edge utilities corresponding to the plurality of edges in the weighted directed graph;
• determine, based at least in part on the plurality of edge utilities, a maximum network flow by optimizing a flow on the network from a source node to a target node, wherein the source node represents the role and the target node represents the worker;
• determine a fitness of the worker for the role based at least in part on performing a comparison of the maximum network flow with a threshold;
• and
• perform an action based at least in part on determining the fitness of the worker for the role.

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 a set of role skills data that identifies one or more role skills associated with a role;
• receive a set of worker skills data that identifies one or more worker skills associated with a worker;
• receive a set of skill proximity data that identifies one or more proximity values, wherein a proximity value of the one or more proximity values quantifies a relationship between a first skill of the one or more role skills or the one or more worker skills and a second skill of the one or more role skills or the one or more worker skills;
• generate a weighted directed graph, comprising a network of a plurality of nodes and a plurality of edges, based at least in part on the set of role skills data, the set of worker skills data, and the set of skill proximity data;
• determine a plurality of edge utilities corresponding to the plurality of edges in the weighted directed graph;
• determine, based at least in part on the plurality of edge utilities, a maximum network flow by optimizing a flow on the network from a source node to a target node, wherein the source node represents the role and the target node represents the worker;
• determine a fitness of the worker for the role based at least in part on performing a comparison of the maximum network flow with a threshold;
• and
• perform an action based at least in part on determining the fitness of the worker for the role.