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Exploring the Benefits and Challenges of Decision Intelligence

Complex decision-making is becoming increasingly challenging as companies strive for operational excellence and productivity. Research shows that businesses make up to three billion decisions a year and a Gartner survey reported that 65% of decisions are more complex than two years ago. To bridge the gap between data and decisions, businesses must adopt decision intelligence (DI). DI is an evolving discipline which combines data, analysis, AI, automation, and experience to make better decisions. It helps an organization make informed decisions at every level, without relying on intuition and experience. Google's first Chief Decision Officer, Cassie Kozyrkov, even established a new decision-intelligence engineering discipline. DI applies to various decision-making problems, such as resource allocation, risk management, and marketing. Organizations leveraging DI gain a more potent competitive edge by evaluating, then acting on, faster complex decisions. Benefits include navigating complex decisions with more focused and comprehensive information, reducing risk and uncertainty, enhancing efficiency and productivity, and avoiding costly mistakes. However, DI isn't without challenges and limitations. Data availability, ethics/bias, and resistance to the new decision-making culture are all issues to consider. Leaders can overcome these by communicating how DI benefits their efforts and leads to better outcomes. Tips and factors to consider include choosing a focused decision, beginning with outcomes, mapping out decisions, not automating everything, providing authority to the decision, developing new decision-making habits, and avoiding narrow framing. Overall, decision intelligence is a crucial tool that can help organizations make better decisions. By combining data science, AI, and human expertise, DI can help reduce uncertainty and improve effectiveness. Nevertheless, risks and limitations must be taken into account.

Originally reported by Martech:
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