Mex is a marketing technology leader, architect and strategist who talks about martech and AI. Decision intelligence (DI) is how people make business decisions, regardless of their role or industry. The key factor in decision intelligence is its focus on outcomes, emphasizing results, which gives both commercial decision makers and technical teams a space to address actual business issues. What decision intelligence is not is removing humans from the decision-making process completely. It's about empowering humans with AI and creating a more holistic, convenient view of all of your business' data to allow them to make the best decision possible.

Today, companies are faced with two enormous challenges: complexity coupled with an ever-increasing speed of change. Technology like artificial intelligence (AI) can help to overcome those challenges. These technological advancements are automating, augmenting and combining human intelligence and the power of decision intelligence to enable smarter and more efficient decision-making processes. Ronald van Loon is a paretos partner and has used the decision intelligence platform to support key business decisions. Businesses must maintain a heightened awareness of ever-changing circumstances and real-world scenarios, analyze these perspectives and information, and act with timing.

As Artificial Intelligence moves from the world of academia to commercial applications, we see the technology sector fragment into categories. Decision Intelligence (DI) is the application of AI to the decision-making process. It is industry- and department-agnostic – decisions are the one thing every function in every business has in common. Gartner predicts that over a third of large organizations will be using DI by 2023, and pioneers like Peak are firmly of the opinion that this is the route by which most businesses will adopt AI. But what is meant by Decision Intelligence?

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! In a digital world fueled by a steady influx of data, achieving organizational excellence depends on giving everyone immediate access to accurate, up-to-date information. Organizational-wide communication and collaboration are vital. Mission-critical decisions, in particular, depend on the timely sharing of lessons learned and insights from all departments.

Hear from top leaders discuss topics surrounding AL/ML technology, conversational AI, IVA, NLP, Edge, and more. In a digital world fueled by a steady influx of data, achieving organizational excellence depends on giving everyone immediate access to accurate, up-to-date information. Organizational-wide communication and collaboration are vital. Mission-critical decisions, in particular, depend on the timely sharing of lessons learned and insights from all departments. With new technology based on artificial intelligence (AI) and machine learning (ML), it's easier than ever to share data effectively and consistently.

Digital experiences are constantly being pushed to new limits by new technology and market shifts. Businesses can't just set up data analytics once and forget about them. They must be adaptable and rely on real-time data and insights to keep up. Startups, SMEs, and large corporations are increasingly turning to data analytics to cut costs, improve customer experience, optimize existing processes, and achieve better-targeted marketing. Besides these, many businesses are interested in Big Data because of its ability to enhance data security.

Decision intelligence is one of those terms that sound vaguely familiar, even if you've never come across it before. Like many category-defining terms, it can mean different things to different people. This is a feature category-defining terms either have by design, or acquire through extensive use. Gartner defines decision intelligence as "a practical domain framing a wide range of decision-making techniques bringing multiple traditional and advanced disciplines together to design, model, align, execute, monitor and tune decision models and processes. Those disciplines include decision management (including advanced nondeterministic techniques such as agent-based systems) and decision support as well as techniques such as descriptive, diagnostics and predictive analytics". Erick Brethenoux, a distinguished VP analyst on artificial intelligence (AI) data science and decision intelligence (DI) at Gartner, frames DI as, "a practical discipline used to improve decision-making by explicitly understanding and engineering how decisions are made, outcomes evaluated, managed and improved by feedback".

Many companies manage by exception, but that is only one part of decision intelligence, explains Henry Hwong, vice president of product marketing for Aera Technology. Hwong told FreightWaves that decision intelligence is still an evolving field that includes simple decisions such as shifting a load to another carrier because the lane price has exceeded a preset threshold, to more complex decisions such as moving production when a factory shuts down. "We are transforming from an era of people making decisions guided by machines to an era of machines making decisions guided by people," explained Fred Laluyaux, president and CEO of Aera Technology, during a presentation of the company's product on Monday at the Gartner Supply Chain Symposium/XPO 2022 conference at Walt Disney World's Dolphin Resort. Hwong detailed the company's new product, which is designed to automate decision-making across organizations, although he noted that humans are and will always be part of the process. Gartner has predicted that by 2025, 95% of decisions that use data will be at least partially automated.

Maintenance now plays a central role in the management of complex machines and systems. In modern plants, it is in fact increasingly important to guarantee pre-established levels of productivity and availability also in consideration of the fact that these are often parameters included in the contractual terms. In addition to these aspects, it is also essential to be able to control the overall management costs of the plants since, in an enlarged economic scenario, competition is fierce and globalization leads to a direct confrontation with Emerging Countries that have labour at lower costs. The issues related to effectiveness, measurable in terms of availability and productivity, and efficiency, which instead can be assessed on the basis of specific management costs, are increasingly interconnected and their control opens the scenario to multiple trade-offs that, especially in the case of complex systems in which the operating variables are many, it is not possible to fully govern with traditional methods. Industry 4.0 and Artificial Intelligence are making a truly significant contribution to the evolution of maintenance, which has gone from a purely reactive operation to a preventive, predictive and finally prescriptive operation.

Pascal Bornet is an expert in AI and Automation, best-selling author, keynote speaker, and CDO at Aera Technology. Decision intelligence is a new field that helps support, augment and automate business decisions by linking data with decisions and outcomes. It uses a combination of methods (e.g., decision mapping and decision theories) and technologies (e.g., machine learning and automation) to improve the way decisions are made in companies. Decision intelligence includes continually evaluating decision outcomes and optimizing them through a feedback system. The term "decision intelligence" was popularized in Lorien Pratt's 2019 book, Link: How Decision Intelligence Connects Data, Actions, and Outcomes for a Better World, after Google launched its decision intelligence department in 2018.