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Operational Excellence (OE) is the systematic implementation of principles and tools designed to enhance organizational performance, and create a culture focused on continuous improvement. It is intended to enable employees to identify, deliver, and enhance the flow of value to customers.
A given Work Center is scheduled to run for an 8-hour (480-minute) shift with a 30-minute scheduled break. Operating Time = 450 Min Scheduled – 60 Min Unscheduled Downtime = 390 Minutes The Standard Rate for the part being produced is 40 Units/Hour or 1.5 Minutes/Unit The Work Center produces 242 Total Units during the shift.
An explanation of the difference between efficiency and (total factor) productivity is found in "An Introduction to Efficiency and Productivity Analysis". [1] To complicate the meaning, operational excellence , which is about continuous improvement, not limited to efficiency, is occasionally used when meaning operational efficiency.
Organizational engineering (OE) is a form of organizational development. It was created by Gary Salton of Professional Communications, Inc. It has been developing continuously since 1994 on both theoretical and applied levels. The core premise of OE is that humans are information-processing organisms.
Creating an actual logic model is particularly important because it helps clarify for all stakeholders: the definition of the problem, the overarching goals, and the capacity and outputs of the program. [15] Rossi, Lipsey & Freeman (2004) suggest four approaches and procedures that can be used to assess the program theory. [8]
T=Sales less TVC and NP=T less OE. Throughput (T) is the rate at which the system produces "goal units". When the goal units are money [8] (in for-profit businesses), throughput is net sales (S) less totally variable cost (TVC), generally the cost of the raw materials (T = S – TVC). Note that T only exists when there is a sale of the product ...
Data may be used as variables in a computational process. [1] [2] Data may represent abstract ideas or concrete measurements. [3] Data are commonly used in scientific research, economics, and virtually every other form of human organizational activity.
The use of a sequence of experiments, where the design of each may depend on the results of previous experiments, including the possible decision to stop experimenting, is within the scope of sequential analysis, a field that was pioneered [12] by Abraham Wald in the context of sequential tests of statistical hypotheses. [13]