Linear management is the application of reductionism to management problems, often relying on the ability to predict, engineer and control outcomes by manipulating the component parts of a business (organization, operation, policy, process and so on). Business process reengineering (BPR) is a popular example of linear management at work. The key defining characteristic of linear management is that order is imposed – usually from above.

However, many[who?] argue that such an approach – treating organizations as machines to be engineered in this way – simply doesn't work. Businesses are too complex and too unpredictable. The results of many BPR projects in the 1990s suggests that this argument might be correct.

Nonlinear management (NLM) is a superset of management techniques and strategies that allows order to emerge by giving organizations the space to self-organize, evolve and adapt, encompassing Agile, "evolutionary" and "lean" approaches, flextime, time banking, as well as many others. Key aspects of NLM, including holism, evolutionary design or delivery, and self-organization are diametrically opposite to linear management thinking.

Examples of nonlinear management at work:

Agile software development is an approach to software development under which requirements and solutions evolve through the collaborative effort of self-organizing and cross-functional teams and their customer(s)/end user(s).[1] It advocates adaptive planning, evolutionary development, early delivery, and continual improvement, and it encourages rapid and flexible response to change.[2][further explanation needed]

The term agile (sometimes written Agile) was popularized, in this context, by the Manifesto for Agile Software Development. The values and principles espoused in this manifesto were derived from and underpin a broad range of software development frameworks, including Scrum and Kanban.

There is significant anecdotal evidence that adopting agile practices and values improves the agility of software professionals, teams and organizations; however, some empirical studies have found no scientific evidence.

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