1. A computer implemented method for automated skill forecast and fulfilment,
comprising:
receiving, by an Artificial Intelligence (AI) engine, a skill demand
5 information from a skill cluster repository and a skill supply information from a
skill inventory;
parsing, by the AI engine, the received skill demand information and the
skill supply information;
generating, by the AI engine, a bill of materials using the parsed skill
10 demand information;
mapping, by the AI engine, the generated bill of materials with the skill
supply information based on pre-defined rules; and
generating, by the AI engine, one or more stock keeping units based on the
mapping, further causing deployment of the generated one or more stock keeping
15 units at client network, wherein the one or more stock keeping units comprise list
of resources mapped to the skill demand information.
2. The method of claim 1, further comprising, updating the skill demand information
stored in the skill cluster repository and the skill supply information stored in the
skill inventory, based on the deployment of the generated one or more stock
20 keeping units.
3. The method of claim 1, wherein each of the one or more stock keeping units is a
combination of technological skill, role definitions, domain skill and location
information.
4. The method of claim 1, wherein the skill demand information comprises at least
25 one or combination of technological services, skill clusters, role definitions,
functional skills, demand unit definitions and domain skills.
5. The method of claim 1, wherein the skill supply information comprises at least
one or combination of role definitions, technical skills, domain skills, proficiency
levels, and location preferences.
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6. The method of claim 1, wherein the pre-defined rules are updated by the AI engine
based on the generated one or more stock keeping units.
7. A system for automated skill forecast and fulfilment, comprising:
at least one processor;
5 at least one memory unit operatively coupled to the at least one processor having
stored instructions; and
an Artificial Intelligence (AI) engine hosted on a cloud computing environment,
wherein execution of the instruction stored on the at least one memory unit by the
at least one processor causes the AI engine to:
10 receive, a skill demand information from a skill cluster repository and a
skill supply information from a skill inventory;
parse, the received skill demand information and the skill supply
information;
generate, a bill of materials using the parsed skill demand information;
15 map, the generated bill of materials with the skill supply information based
on pre-defined rules; and
generate, one or more stock keeping units based on the mapping, further
causing deployment of the generated one or more stock keeping units at client
network, wherein the one or more stock keeping units comprise list of resources
20 mapped to the skill demand information.
8. The system of claim 7, wherein the at least one processor further causes the AI
engine to update the skill demand information stored in the skill cluster repository
and the skill supply information stored in the skill inventory, based on the
deployment of the generated one or more stock keeping units.
25 9. The system of claim 7, wherein each of the one or more stock keeping units is a
combination of technological skill, role definitions, domain skill and location
information.
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10. The system of claim 7, wherein the skill demand information comprises at least
one or combination of technological services, skill clusters, role definitions,
functional skills, demand unit definitions and domain skills.
11. The system of claim 7, wherein the skill supply information comprises at least one
5 or combination of role definitions, technical skills, domain skills, proficiency
levels and location preferences.
12. The system of claim 7, wherein the pre-defined rules are updated by the AI engine
based on the generated one or more stock keeping units.