Abstract: Systems and methods for measuring, reporting, controlling, and improving enterprise performance are described. A system receives objective statements for an enterprise, which can be an IEE value chain of the enterprise, and enterprise-specific measurable metrics through an interactive user interface with their associated processes. The system collects historical data and real-time data (e.g., daily) associated with enterprise-specific measurable metrics from a plurality of infield resources and analyses the historical data and the real-time data using a statistical model to provide information that teams can use to determine the strengths and shortcomings of the enterprise. Based on the determined strength and shortcomings, the system provides, using a knowledge database, information so that leadership and teams can determine where to focus process-output metric improvement efforts via process improvement efforts so that the enterprise-as-a-whole financially benefits.

Abstract: Systems and methods for measuring, reporting, controlling, and improving enterprise performance are described. A system receives objective statements for an enterprise, which can be an IEE value chain of the enterprise, and enterprise-specific measurable metrics through an interactive user interface with their associated processes. The system collects historical data and real-time data (e.g., daily) associated with enterprise-specific measurable metrics from a plurality of infield resources and analyses the historical data and the real-time data using a statistical model to provide information that teams can use to determine the strengths and shortcomings of the enterprise. Based on the determined strength and shortcomings, the system provides, using a knowledge database, information so that leadership and teams can determine where to focus process-output metric improvement efforts via process improvement efforts so that the enterprise-as-a-whole financially benefits.

Abstract: Systems, apparatus, and methods for improving the monitoring of processes. These systems comprise processors co-located with the (physical) processes and which accept certain metrics regarding the processes. These systems also include processors which are located remotely from the processes, but, which are in communication with the co-located processors. The remote processors receive the metrics from the co-located processors and transform these metrics to corresponding probability metrics. Based on the probability metrics, the remote processors determine whether the processes are predictable. They also output the predictability determinations regarding the processes. The processes can be associated with petrochemical wells, food/beverage processes, etc. Additionally, or in the alternative, some systems further comprise memories which store flowchart representations of the processes. In various embodiments, the remote processors associate the metrics with the operations represented in the flowcharts.