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The DeAngelis Review

Exploring Symmetries in Life and Practice

Intelligent Automation and Business Continuity

The pandemic exposed flaws in traditional business continuity plans. The answer? Intelligent automation to keep processes flowing even during disruptions. This article explores how smart automation can be your secret weapon for business resilience.

Where Should Business Decisions Be Made?

Countless decisions are made every day in every business. It turns out that it matters where those decisions are made. Some decisions should be made on the front lines, while others should be made in decision centers or war rooms.

Looking Forward to the Autonomous Intelligent Enterprise

In a world that is moving towards autonomous vehicles, aircraft, and robots, many pundits predict autonomous digital enterprises are not far behind. According to analysts from Pegasystems, “The autonomous enterprise is an organization which comprehensively applies AI and automation to engagement, servicing, and operations across the organization to operationalize agility and create a business that can become self-optimizing.”

Leadership and Decision-making

Leaders need to understand what decisions are important, how quickly they must be made, and what the consequences of certain decisions could be. Nevertheless, it’s easy for leaders to be overwhelmed by decision overload. One way to overcome decision overload is to let intelligent systems make routine decisions using the embedded expertise of the company’s best experts.

Cognitive Computing, Decision-making, and the Supply Chain

This article explores how cognitive computing can help supply chain professionals manage information overload and complexity. Cognitive computing uses AI and machine learning to analyze data and make decisions, reducing workload for humans. It can automate routine decisions and free up professionals to make strategic choices.

Making Better Decisions with Decision Science

Although many experts insist that companies must be data-driven, they also point out that collecting data is of little value until it is analyzed for insights. The problem with most data is that it assumes the future will look like the past. That is not always true. The best analysis looks forward as well as backward. It takes current trends into account as well as past performance.