RELEX Solutions delivers a unified platform for retail, manufacturing, and supply chain planning, enabled by proven AI technology. We help retailers, manufacturers, and consumer goods companies optimize demand forecasting, replenishment, merchandising, pricing and promotions, supply chain operations, and production planning across the end-to-end value chain. Companies like ADUSA, AutoZone, Coles, Circle K, Dollar Tree and Family Dollar, M&S Food, PetSmart, Rituals, The Home Depot, and Systemair trust RELEX to increase product availability, boost sales, deliver actionable insights, improve sustainability, and drive profitable growth. Learn more at: www.relexsolutions.com/customers/
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RELEX Solutions
Every conversation about what's next for enterprise AI eventually returns to the same place. Forget the flashy models and agentic capabilities. In the end, it's all about data.
In this excerpt from Episode 3 of Decision Loop, host Christine Babington asks Richard Davis, CEO and co-founder of Inference Group, what lies ahead for enterprise AI in the next few years. His response moves the discussion from the speculative to the present day issues that could block the potential in the future.
All forms of AI, from machine learning to large language models to generative tools, depend on a foundation of data. Without it, none of it works as expected or produces meaningful value. The model isn't the differentiator. The quality, structure, lineage, and governance of the data feeding it are.
This is what the organizations that are moving fast understand. They have figured out what to cleanse, what to verify, what's confidential and what can be used for classification purposes. They've put in the work, investing in data quality and metadata discipline before the race to deploy arrives. That's why they'll be the ones flying with AI.
In the next one to two years, data readiness will be the dividing line.
1 day ago | [YT] | 0
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RELEX Solutions
While most organizations realize they need a business case for AI, few have created a framework to ensure it keeps having a net-positive impact across the full lifetime of its deployment.
Richard Davis , CEO and co-founder of Inference Group, walks through how to evaluate an AI investment properly, laying out the benefit against strategic OKRs, costing out build, buy, and blended approaches, and accounting for the maintenance burden that's often overlooked by initial calculations.
The key insight is that underlying systems change every two to three years, so custom builds require a full rebuild on that cycle. A bought solution passes that responsibility onto the license fee. A blended approach changes the equation again. Understanding that difference is what separates a business case that just gets you to launch from one that endures over time.
Catch the full Decision Loop podcast episode on the RELEX Solutions YouTube channel.
2 weeks ago (edited) | [YT] | 0
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RELEX Solutions
Process mapping can sound like a months-long undertaking. It does not have to be.
In this clip from Decision Loop, Ron Crabtree, CEO of MetaOps Inc., shares the approach he has used across automotive, aerospace, and healthcare to help organizations get started without feeling overwhelmed.
The answer is not to map everything. It is to pick one meaningful process, walk it end to end, and capture what is actually happening, including what Ron calls the hidden factory: all the unplanned steps, workarounds, and delays that eat time and money when things do not go as expected.
Get the right people in the room. Ask the right questions. You will be surprised how quickly a clear picture emerges.
If your organization is trying to build the process foundation for AI or automation and does not know where to start, this is the most practical three minutes you will spend today.
1 month ago (edited) | [YT] | 0
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RELEX Solutions
Lowering the barrier to entry for AI sounds like good news. And it is. But only if your organization’s foundation is ready for it.
In this excerpt from episode 1 of Decision Loop, Christine Babington and Madhav Durbha tackle one of the most common enterprise mistakes: launching agentic AI from legacy infrastructure. Think siloed data, 20 different ERP systems, planning still happening in Excel, and expecting results.
It's not going to happen. Not without the right technological foundation.
Madhav walks through why specialized AI must come first in manufacturing, how it opens the door for fully functional agentic capabilities, and why enterprise adoption is harder than the headlines suggest.
He also confronts misdirected fear head-on, arguing that jobs won't disappear because of AI, but the work will change. Organizations that bring their people in as active participants in that change will move faster and further.
1 month ago | [YT] | 0
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RELEX Solutions
What do you see as the most important aspect of supply chain planning that can improve collaboration between suppliers and retailers?
3 years ago | [YT] | 0
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