Noodle.ai’s Gartner 2021 Trifecta: Our Third Mention this Year, Now in Market Guide for Data Analytics and Intelligence Platforms in Supply Chain
Just released: We’re excited to see that Gartner positioned us as a Representative Vendor in the 2021 Gartner® Market Guide for Data Analytics and Intelligence Platforms in Supply Chain. This first-time Market Guide provides initial coverage of the market and focuses on the market definition, rationale for the market, and market dynamics.
Let’s unpack what Gartner said in its September 20th, 2021, Market Guide by Noha Tohamy and Christian Titze and what it means for modern supply chain leaders.
TLDR: It means “get busy” implementing resilient planning/A.I. right now. What follows are the highlights of the Market Guide from our P.O.V.
A Prerequisite for Success
“Many supply chain organizations recognize that platforms leveraging advanced analytics and intelligence are a prerequisite to have a more flexible approach to dealing with the data deluge,” says the Gartner report.
A.I. will be table stakes for supply chain applications by 2025:
“By 2025, more than 80% of newly created supply chain applications will leverage artificial intelligence and data science resulting in additional insightful information, predictions, and suggestions.”
“This market spans capabilities that provide descriptive, diagnostic, predictive, and prescriptive analytics. Many of these offerings have been enhanced with artificial intelligence (A.I.) and data science (D.S.) capabilities to support supply chain decision-making. A platform consists of existing and emerging technologies (such as AI/ML), built next to a digital supply chain twin foundation, and combined with near-real-time data from the business ecosystem.”
The two other mentions for Noodle.ai by Gartner in 2021 also speak to the transformative nature of our technology, telling a broader audience what we’ve always known:
- The 2021 Supply Chain Technology Themes (available to Gartner subscribers)
- 2021 Hype Cycle for Supply Chain Strategy (available to Gartner subscribers)
“The growing interest in A.I. will continue to drive new and existing vendors to aggressively position their solutions as AI-enabled data intelligence. This will generate a high level of confusion for buyers, potentially resulting in dissatisfied customers and failed projects.”
YES! We’ve seen a lot of misinformation in the market, with A.I. vendors and consultants presenting science experiments and non-productized offerings being presented as products. Noodle.ai products are proven in production. Read evidence provided by customers Kellogg, Reckitt, and Estee Lauder, from this Noodle.ai Fireside Chat, Creating Perfect Flow in Supply Chains from March 2021.
Building Blocks and Use Cases
Some core elements of this technology are fundamental to the value proposition of the Noodle.ai FlowOps product suite. Of the five building blocks mentioned, three are worth calling out as they closely align with our products:
“1. Integration — Allows process integration/orchestration and partner collaboration, an engine that drives workflows and integration across functional silos and distributed systems, basically expanding from insights into actions (respond planning).
2. Algorithms (algorithm and model library)— Offer a library of best-in-class algorithms and prebuilt models to be leveraged for supply-chain-specific AI-driven simulation and optimization use cases (including AI/ML algorithms for what-if simulations, predictions, suggestions, and optimization), allowing to publish customer-specific apps.
3. Digital supply chain twin— Creates a digital representation of the physical supply chain, modeling the near-real, networked world (the digital supply chain twin including relationships, attributes, and parameters, as source for feeding simulation and optimization engines). ”
We are happy to see that this new category follows the “Plan, Source, Make, Deliver, Service, Cross” model because it encompasses Noodle.ai’s complete product offering in two stages, Plan and Make:
- Plan: Automated replenishment, integrated planning, resource planning and scheduling, demand forecasting (Noodle.ai’s Inventory Flow, Production Flow, Demand Flow)
- Make: Production schedule optimization, predictive asset maintenance, asset failures, and downtime, yield prediction and optimization, equipment maintenance, shop-floor flow optimization, capacity optimization (Noodle.ai’s Asset Flow, Quality Flow)
Finally, How to Get Started
We talk to supply chain and manufacturing leaders actively driving digital transformation every day. What does Gartner (and what do we) recommend leaders seeking a modern supply chain do?
- “Outline a roadmap for adopting advanced analytics and intelligence and other enabling technology
- Maximize future connected supply chain data success by carefully choosing a buy, build or partner model, based on organizational maturity and data analytics and intelligence resource availability. (note: we’d say buy. Why not leverage the learnings we already have after $110M of investment in building A.I. products?)
- Start increasing R.O.I. of analytics and intelligence by leveraging existing applications with embedded capabilities next to investing in dedicated data analytics and intelligence platforms. Capture the R.O.I. by improving current usage levels and addressing adoption challenges.” (our users LOVE using our products, and user adoption is HIGH!)
Read the entire report here and reach out to schedule a demo and get started on the path that Gartner sees as essential, inevitable, and transformational.
Gartner does not endorse any vendor, product, or service depicted in its 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 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
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