Reference models and data repositories

  • Authors:
  • Leon F. McGinnis;George Thiers

  • Affiliations:
  • School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta, GA, USA. E-mail: leon.mcginnis@isye.gatech.edu;School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta, GA, USA. E-mail: leon.mcginnis@isye.gatech.edu

  • Venue:
  • Information-Knowledge-Systems Management - Enterprise Transformation: Manufacturing in a Global Enterprise
  • Year:
  • 2012

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Abstract

In transforming any large scale, complex, global supply network, a key challenge is knowledge management. There are many stakeholders, spread across a number of enterprise functions, whose decisions directly or indirectly impact the success of the transformation. Typically, each stakeholder has important, often tacit knowledge that in contemporary practice is difficult or impossible to share effectively with other stakeholders, yet can be critical to the success of the transformation. The intended "to be" state maybe defined abstractly, but the full intent may not be explicitly understood by all stakeholders. The lack of a complete coherent shared understanding of the to-be state can have major repercussions in transformation decision making. The challenge for global enterprises is to capture as much of the critical tacit or implicit knowledge as is practical, so it can be vetted, shared, re-used, and leveraged. This chapter introduces a methodology and a set of tools that can be used to effect some aspects of knowledge capture, sharing and re-use in the context of enterprise transformation, and illustrates their use with two examples.