A visualization solution for the analysis and identification of workforce expertise

  • Authors:
  • Cheryl Kieliszewski;Jie Cui;Amit Behal;Ana Lelescu;Takeisha Hubbard

  • Affiliations:
  • IBM Almaden Research Center, San Jose, California;IBM China Research Lab, Beijing, China;IBM Almaden Research Center, San Jose, California;IBM Almaden Research Center, San Jose, California;Texas A & M University, College Station, TX

  • Venue:
  • Proceedings of the 2007 conference on Human interface: Part I
  • Year:
  • 2007

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Abstract

Keeping sight of the enterprise's workforce strengthens the entire business by helping to avoid poor decision-making and lowering the risk of failure in problem-solving. It is critical for large-scale, global enterprises to have capabilities to quickly identify subject matter experts (SMEs) to staff teams or to resolve domain-specific problems. This requires timely understanding of the kinds of experience and expertise of the people in the firm for any given set of skills. Fortunately, a large portion of the information that is needed to identify SMEs and knowledge communities is embedded in many structured and unstructured data sources. Mining and understanding this information requires non-linear processes to interact with automated tools; along with visualizations of different interrelated data to enable exploration and discovery. This paper describes a visualization solution coupled with an interactive information analytics technique to facilitate the discovery and identification of workforce experience and knowledge community capacity.