Workflow

Workflow describes the steps in a business work process, through which a piece of work passes from initiation to completion; and how these steps can be executed and automated according to a set of procedural rules.

Organizations use workflow to coordinate tasks, with the aim of improving organizational efficiency, responsiveness and profitability. Workflow may either be sequential, with each step contingent upon completion of the previous one, or parallel, with multiple steps occurring simultaneously.

The concept of workflow was important to the study of the rational organization of work and optimizing manufacturing or informational processes – to avoid bottlenecks. After WW2, a number of workflow improvement theories were developed by the quality movement, which embraced more qualitative notions of business process re-engineering. These philosophies could be applied to car assembly lines, a loan application by a bank, or the production of a newspaper.

Six Sigma and Total quality management (TQM), are two process improvement philosophies that have been embraced by organizations around the world. TQM is a structured approach to overall organizational management where internal guidelines and process standards reduce errors. The goal of Six Sigma is to reduce defects through quality control.

Workflow technologies and management systems are being used today in industries as wide ranging as finance, healthcare, marketing and higher education. They have been fundamental to the development of artificial intelligence and machine learning systems, that are having a big impact on corporate workflows in every industry, thanks to their ability to process and extract value from big data.

By gathering and sharing data across an organization, and embedding analytics, enterprise data management systems are being used to eliminate information silos and optimize business processes and automate data processing. And this is helping to connect previously disconnected sectors and industries.

Finance is being transformed by big data, which is being used for both trading and compliance. Investors are tapping into the flood of real time data produced by global digitalization and social media, and experimenting with enhanced data analytics and AI to generate investment ideas – free of cognitive bias — and manage risk.