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autonomous business process (ABP)

Contributor(s): Dennis Shiao

Autonomous business process (ABP) management is an approach to business process governance that seeks to optimize process workflow without human assistance. ABP intelligent software agents, also known as bots, are designed to independently discover and map business processes and use machine learning (ML) algorithms to improve process flow.

ABP is an area of business process automation that takes advantage of technologies such as radio frequency identification (RFID) and autonomic computingAlthough it is still an emerging technology, vendors are beginning to label robotic process automation (RPA) software "ABP"if the software can improve efficiency in the following areas:

  • Auto-generation of repeatable documents, such as contracts, invoices or loan documents.
  • Servicing customer support requests within an enterprise, including the routing of tickets to departments or contacts.
  • Planning the transportation of goods in supply chain and logistics applications.

The ultimate goal of ABP software is to be able to autonomously determine the role of people, technology and data in a particular business process and independently figure out how to optimize it. When fully realized, ABP is expected to create a sea change for process management, including discovery, business process modeling, analytics and optimization. 

Autonomous Process Discovery and Modeling

  • Automatically identify process flows in new systems ("process discovery").
  • Automatic process documentation.
  • Automatically discover explicit as well as implicit process flows by observing actual human, data, and system operation.
  • Automatically discover the entities with which a business interacts.

Autonomous Process Analytics and Management

  • Automatically identify actual key performance indicators (KPIs) and metrics that determine process efficiency.
  • Automatically use overall business goals to measure how discovered processes are actually performing.
  • Automatically identify people, data, and system bottlenecks.

Autonomous Process Optimization

  • Automatically anticipate and mitigate process flow exceptions.
  • Automatically understand system data and interface changes, and make dynamic process changes.
  • Autonomously find and fix missing or incorrect data.

This was last updated in December 2019

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