Ex-Ante PLM Misfit Analysis Methodology: A Cognitive Fit Approach

Commercial off-the-shelf (COTS) Product Lifecycle Management (PLM) systems have been introduced by companies to facilitate their new product development process to shorten the product time to market, reduce the product development cost, and meet the dynamic demands of customers. However, PLM implementation is not an easy job and some of the attempted projects failed. A common problem encountered in adopting PLM packages has been the issue of misfits, i.e., the gaps between the specifications offered by a PLM package and those required by the adopting organization, which easily causes the project to fail. Current approaches for the ex-ante analysis of PLM misfits are extremely limited. This paper develops a methodology grounded in the extended cognitive fit theory for the misfit analysis. This approach can assist in identifying and representing consistent set of information for functions and workflow processes across business requirements and the PLM package. Particularly, Petri nets that are of graphical representations and easy to understand are employed to model the function-embedded workflow process. A case study is presented to examine the feasibility of this approach. We conclude that with our methodology, PLM analysts or adopting organizations can systematically identify potential misfits and the degree of misfit between the business requirements and PLM packages in an ex-ante analysis to mitigate the risks in PLM implementations.