complete cycle indicating an increase in our knowledge of the system under study. This approach is based on the belief that our knowledge and skills are limited, but improving. Especially at the start of a project, key information may not be known; the PDCA—scientific method—provides feedback to justify guesses (hypotheses) and increase knowledge. Rather than enter "analysis paralysis" to get it perfect the first time, it is better to be approximately right than exactly wrong. With improved knowledge, one may choose to refine or alter the goal (ideal state). The aim of the PDCA cycle is to bring its users closer to whatever goal they choose. When PDCA is used for complex projects or products with a certain controversy, checking with external stakeholders should happen before the Do stage, since changes to projects and products that are already in detailed design can be costly; this is also seen as Plan-Check-Do-Act. The rate of change, that is, the rate of improvement, is a key competitive factor in today's world. PDCA allows for major "jumps" in performance ("breakthroughs" often desired in a Western approach), as well as kaizen (frequent small improvements). In the United States a PDCA approach is usually associated with a sizable project involving numerous people's time, and thus managers want to see large "breakthrough" improvements to justify the effort expended. However, the scientific method and PDCA apply to all sorts of projects and improvement activities. See also COBIT Decision cycle DMAIC Intelligence cycle Kolb's experiential learning Lean manufacturing Learning cycle Lesson study OODA loop Performance management Quality storyboard Robert S. Kaplan (closed loop management system) Six Sigma Software development process Theory of constraints Total security management References Further reading Reprint. Originally published: Quality Management Journal 2(1) (1994): 9–24. 50th anniversary commemorative reissue. Originally published: New York: Van Nostrand, 1931. American inventions