By Topic

Statistical methods for automated generation of service engagement staffing plans

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Hu, J. ; IBM Research Division, Thomas J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598, USA ; Ray, B.K. ; Singh, M.

In order to successfully deliver a labor-based professional service, the right people with the right skills must be available to deliver the service when it is needed. Meeting this objective requires a systematic, repeatable approach for determining the staffing requirements that enable informed staffing management decisions. We present a methodology developed for the Global Business Services (GBS) organization of IBM to enable automated generation of staffing plans involving specific job roles, skill sets, and employee experience levels. The staffing plan generation is based on key characteristics of the expected project as well as selection of a project type from a project taxonomy that maps to staffing requirements. The taxonomy is developed using statistical clustering techniques applied to labor records from a large number of historical GBS projects. We describe the steps necessary to process the labor records so that they are in a form suitable for analysis, as well as the clustering methods used for analysis, and the algorithm developed to dynamically generate a staffing plan based on a selected group. We also present results of applying the clustering and staffing plan generation methodologies to a variety of GBS projects.

Note: The Institute of Electrical and Electronics Engineers, Incorporated is distributing this Article with permission of the International Business Machines Corporation (IBM) who is the exclusive owner. The recipient of this Article may not assign, sublicense, lease, rent or otherwise transfer, reproduce, prepare derivative works, publicly display or perform, or distribute the Article.  

Published in:

IBM Journal of Research and Development  (Volume:51 ,  Issue: 3.4 )