| Using Statistical Process Control to Improve the Quality and Delivery of IT Services | |
| Nathan Shiffman Armin Roeseler, Townsend Analytics Mike Pecak | |
This session presents a framework for the delivery of IT services based on Continuous Quality Improvement (CQI). Starting with the Capability Maturity Model (CMM), we develop a process oriented approach based on Statistical Process Control (SPC). We apply the framework to the Change Management process of a large IT environment for a trading software firm, and show how failure-rates of the Change Management process were reduced dramatically. |
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Igor Trubin began his engineering career in 1979 as an IBM/370 systems engineer. He earned a Ph.D. in Robotics from St. Petersburg Technical University in 1986 and spent 12 years there as a professor teaching CAD/CAM and Robotics. He has published and presented more than 60 technical papers and conference presentations in robotics, artificial intelligence, IT performance, capacity management, anomaly detection, and FinOps. After moving to the U.S. in 1999, Igor worked at Capital One, IBM, and SunTrust Bank in senior engineering, architecture, and management roles. His 2002 CMG paper on exception detection received a Best Paper Award. He later developed Perfomalist.com, based on his original methods for anomaly, change-point, and trend detection, and created the online course “Performance Anomaly Detection.” At Capital One, he led development of cloud capacity-management and FinOps solutions, including the award-winning OptiCloud application. He has served on the CMG Board of Directors since 2015. Now semi-retired, Igor focuses on research, writing, and consulting. His current work expands his concept of the “Area of Normal Functioning” (ANF) from technical systems to human, orga