Measuring information alignment in production organizations
Abstract
All organizations are interested in meeting or exceeding organization performance metrics. Resource allocation, risk management, and process improvement techniques (i.e. Six Sigma, Lean Manufacturing, etc.) are common approaches to improve organization performance. Although the operations aspect of an organization is visible and quantifiable, the operations aspect is not the only aspect of an organization that improves organization performance. Information flow has been consistently identified as an organization aspect that can improve organization performance and ease of operations. To improve information flow involves the alignment of the information shared between various entities. Unfortunately, the alignment of information has only been identified as a factor affecting organization performance. The effect of information alignment has not yet been quantified in the literature. This dissertation outlined a methodology to collect and analyze data to quantify information alignment. This dissertation collected data from a production facility and a refurbishment facility. The model created from the operations aspect of the organizations proved to be significant for both organizations. The information alignment model included some of the operations aspect model factors, which was determined by a backward regression analysis. The hypothesis of this dissertation was that the information alignment model was significantly better than the operations aspect model in predicting organization performance. The model significance and R-Square value improved using the information alignment model for each organization. However, the information alignment model was only statistically significantly better for one organization. The results from the other organization provided vital insight into experiment design and lessons learned for future research. The results from the analyses determined that there was a relationship between information and organization performance.
Degree
Ph.D.
Advisors
Caldwell, Purdue University.
Subject Area
Industrial engineering
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