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Extract from article by James Wilson, Allan Alter, and Prashant Shukla

Powerful machine-learning algorithms that adapt through experience and evolve in intelligence with exposure to data are driving changes in businesses that would have been impossible to imagine just five years ago. The PCs and databases introduced during the reengineering of the 90s have grown up: the rules-based codes written by engineers are giving way to learning algorithms driven by the machines themselves. As a result, business processes are being machine-reengineered.

Algorithms aim to redesign business processes just like humans did during the original reengineering movement. Then, reengineering was limited by the speed of humans. Managers noted historical trends and revised processes, and engineers developed code that was then baked into computing systems. Every update or response to the market required multiple steps; it cost time and performance. Sometimes, by the time changes were in place, the market had already moved. With machine-reengineering, process changes are constant and driven not just by history but also by the predictive capabilities of machine-learning algorithms.

 

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