Intelligent Resource Matcher

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has title::Intelligent Resource Matcher
status: ongoing
Student name: student name::Marloes Dost
Start start date:=2010/09/01
End end date:=2011/04/30
Supervisor: Mark Hoogendoorn
Company: has company::Logica
Poster: has poster::Media:Media:Posternaam.pdf

Signature supervisor



At Logica Netherlands Consulting and Professional Services (C&PS) aims at providing their Industry Sectors (IS) good and qualified personnel as much as possible. The nature of Consulting & Professional Services makes that employees need to be assigned to external projects. Resourcing and matching of employees with new projects is done by employees of Matching and Resourcing (M&R). Currently HR managers use “Logica Assignment Resourcing Application”, or LARA to provide information on employees and project applications. Employees of M&R deliberate with a certain practice on the most suitable candidate on a project. This candidate will be presented to the client. Disadvantage in the current matching process is not only the difficulty to find the right candidate on the job, but also the time it takes to find the right candidate.

To improve accuracy (the percentage of candidates invited by clients after presentation) and speed of the matching process an application should be developed which can provide a recommendation on the best candidate on the job. Based on characteristics of the application and characteristics of employees this recommendation should be made. Goal of this graduation project is to develop a proof of concept of such an application. As in the field of Artificial Intelligence already some research is done on selecting people for a job, and Multi-Agent Resource Allocation has a very natural resemblance to the matching process, the application will be based on a Multi-Agent system. Improved accuracy and speed of the matching process might result in a decrease in time consultants being idle. Also it might lead to moderation of the selection done by Matching and Resourcing, leaving time for more complicated tasks. Overall it can lead to increased efficiency.

By means of this project a proof of concept of an “intelligent resource matcher” based on a Multi-Agent system will be created and tested which can provide a recommendation on the best candidate on a job based on both characteristics of an application and characteristics of employees.