479971 Big Data Vs. Little's Law: A Systems-Based Framework Changing the Risk-Reward of Large Scale Facilities

Monday, March 27, 2017: 1:35 PM
211 (Henry B. Gonzalez Convention Center)
John Carrier, System Dynamics Group, MIT Sloan School of Management, Cambridge, MA

The current rush to adopt Big Data ignores the fact that the data is not the system. Ignoring system dynamics in the interpretation of thedata often produces the opposite of the intended result. Fortunately, Little’s Law (L = λW) provides a framework to properly interpret the dynamic nature of data and diagnose the true underlying systemic problems. Little’s Law is especially useful in identifying and eliminating hidden factories in the system that erase profits, increase systemic risk, and erode morale and culture. Dr. Carrier will explore examples from high-risk environments that have saved hundreds of millions of dollars per year while improving safety. In addition, the amount of data required to make and implement informed decisions is dramatically decreased through the use of Little's Law. The approach will be demonstrated with several examples in Oil and Gas, Refining, and Fine Chemicals worked on by the author. The methodology will also be demonstrated for use in maintenance management and the radical improvement of a mid-sized refinery's MoC (management of change process). Finally, the role of culture in actively the dynamic response of our systems will be discussed.

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See more of this Session: Big Data Analytics and Process Safety Joint Plenary II
See more of this Group/Topical: Topical A: 3rd Big Data Analytics