Believe the Hype: Gartner, Noodle.ai, and Decision Intelligence
What is Decision Intelligence?
At Noodle, decision intelligence is at the core of what we do, highlighted by the machine learning in our Vulcan Manufacturing and Athena Supply Chain product suites. We focus our data science expertise on machine learning because it is uniquely suited to analyze massive amounts of data, find patterns, and make predictions. When you consider the seemingly infinite amount of data that touches a supply chain or manufacturing process, it becomes clear that predicting outcomes – a key element to decision intelligence – across these innumerable moving parts is not a human-solvable problem. But, doing a better job predicting these outcomes is only part of the battle. Where we hang our hat, and what differentiates us in the marketplace, is how we go about determining what outcomes – and the decisions required to get those outcomes – matter the most.
Value at Risk: How much is that decision worth?
As the global economy has become more dynamic, the shortcomings of rules-based ERP and MES software are laid bare. Namely, that rules and volatility don’t get along. As a result, planners, operators, managers, and executives are stuck trying to make decisions with noisy data and limited forward visibility, where everything is critical and there’s no way to prioritize. That reality doesn’t exist with our Value at Risk metric. For example, instead of navigating through hundreds of rules-based exceptions that all look the same, an inventory planner will see a list of predicted business risks, prioritized by the dollar value each risk represents to the company. And for each of those risks, Noodle will recommend a specific set of actions to maximize value capture in mitigating those risks.
Our approach to decision intelligence – predicting business risks, tying each risk to a hard dollar value, and then recommending mitigative actions – is unique. Both because of our ability to tie machine learning to significant business outcomes, but also because we’re the only Enterprise AI® software provider that provides a direct and measurable ROI to every decision we help our customers make. As you can imagine, there’s a lot more under the hood; if you’re interested in learning more, please contact us.
If you’re interested in learning more about the data science behind our “decision intelligence”, please read these blogs:
- Deep Probabilistic Decision Machines (DPDM) for building a causally generative process model-based action control in Enterprise AI
- Will All The Good Data Scientists Please Stand Up?: The importance of advanced data science in getting the coronavirus recovery right
1. Gartner “Hype Cycle for Artificial Intelligence, 2020,” Svetlana Sicular, Shubhangi Vashisth, 27 July 2020
Gartner does not endorse any vendor, product or service depicted in our research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s Research and Advisory organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
- Progress is as Simple as a Bowl of Cereal: Joining Forces with Noodle.ai to Create Perfect Flow
- Deep Probabilistic Decision Learning Returns Perfect Flow to Operations
- Perfect Flow: Augmented Intelligence and the Elimination of Manufacturing Waste
- AWS Partner Network Blog: How CPGs Can Improve On-Time, In-Full (OTIF) Deliveries
- The Future of Quality Management in Modern Manufacturing: AI-Driven