The Growing Need for Decision Intelligence: What We Learned at #GartnerSC Orlando 2023

This year’s Gartner Supply Chain Symposium/Xpo in Orlando, Fla. drew thousands of attendees, many of whom were eager to learn more about AI and Decision Intelligence. It’s not an exaggeration to say that Decision Intelligence was one of the most talked-about topics at this event.

From the conversations we had around the conference, to the number of demos and meetings the Aera team had at our booth, it’s clear that companies have recognized the critical importance of increasing the pace and accuracy of decision making.

Perhaps the biggest takeaway is that the acceleration of AI adoption in recent months, and the incredible excitement about tools like OpenAI’s ChatGPT and Google’s Bard, have fueled a stronger level of trust in decision making automation – along with a growing realization of the benefits AI and machine learning will have for companies' supply chains.

AI is Driving Supply Chain Innovation

What we saw at this year’s Gartner Supply Chain Symposium is evidence of the pivot that has taken place – from companies asking “What is it?” about AI and automation for decision making, to asking “Where do we start?” and “How long will it take to see the benefits?”

That pivot has been extraordinary. And we can attribute this high level of trust in AI for decision making to the experiences of companies like Proximo Spirits, who highlighted an over 90% level of trust in the recommendations that Aera is making for their users. There’s a massive willingness for teams to adopt Decision Intelligence in order to transform supply chain decision making and fuel innovation.

Aera Decision Cloud™ is helping companies like Proximo Spirits vastly improve decision agility – ingesting data and harmonizing it into a data model for decision making, then applying AI and ML to make data-driven recommendations in near-real-time.

With Aera, users can dig deeply into the data – down to the transaction level if needed – and fully understand the recommendation, accept it, or modify it as needed.

At the Gartner symposium in Orlando, we found that leaders have increasingly heard about this technology and understand its benefits. We had many discussions about potential use cases and applications for Decision Intelligence, eager to see how they can achieve similar results from an AI-powered platform.

Overcoming Decision-Making Silos

Another recurring theme on the Gartner expo floor was improving the decision-making challenges that occur at the intersections of business units and functions. These are critical areas that often suffer due to siloed processes and systems. Companies have begun to realize the capability a Decision Intelligence platform has to bridge those siloes, delivering end-to-end visibility with a data model that extends across the entire enterprise.

With this system of intelligence in place, companies can make intelligent decisions with a level of speed and accuracy that simply isn’t possible with disconnected solutions and processes. For example, if there’s a change in demand, an MRP will tell you that you need more of a particular material – but how do you know the best supplier from which to source it? And, if the preferred supplier doesn’t have the material or capacity, how can you pivot to keep your production plans in place?

Another problem area we heard time and again concerns warehouse capacity – in particular, the excess fees companies are facing for third-party warehousing. Companies are working to optimize inventory placement to avoid both unnecessary costs and the need to spread inventory across external warehouses (which compounds the problem by increasing lead times as well as costs).

We’re also hearing more and more conversations about how to apply Decision Intelligence across the enterprise, not only in supply chain but across procurement, marketing and media spending, and more – all focused on gaining agility and intelligence, while preparing for potential volatility in a fast-moving, digital world.

Taking the Next Steps

Many people we spoke to also expressed concerns about master data. One perceived challenge that can hold companies back from exploring Decision Intelligence is a fear that the point solutions and systems they rely on may not have the right information – preventing them from digitizing or automating decision making.

The good news is that Decision Intelligence and AI can avoid the problem of “bad data in, bad data out.” As our customers have realized, concerns about “bad data in” can be addressed with AI and automated machine learning (AutoML) capabilities. With a Decision Intelligence platform, your team can understand what data is missing or wrong, while AutoML and AI allow for 24/7 self-healing capabilities.

With more and more companies realizing the cost of the decisions they aren’t able to address today – gaps caused back a lack of time, visibility, or data analysis capabilities – the time has come for Decision Intelligence. Aera Decision Cloud™ combines end-to-end data with AI and machine learning capabilities, making it possible to identify risks and opportunities in real time.

We came away from the Gartner Supply Chain Symposium/Xpo with a sense that this is a turning point for adoption of Decision Intelligence. As more companies add these capabilities alongside their existing technologies for planning, manufacturing, logistics, and more, they’ll see the benefits of increased intelligence and agility. You can bet that next year’s event will see even more conversations not only about adopting Decision Intelligence, but the benefits companies have seen over the ensuing months.