decision-data-model 
Supply Chain Shaman
NOVEMBER 15, 2023
When deploying enterprise decision support applications, there are many implementations and lots of hype but few clear and consistent definitions. The lack of interoperability between decision support platforms is a problem for companies attempting to improve decisions from the channel to supplier bi-directionally through technology.
Logility
MARCH 21, 2024
Leveraging AI for Faster, Strategic Decision Making There is a lot of information out there around generative AI, and it’s difficult to separate fact from fiction. Myth 2: Generative AI is unable to keep your data private One of our top concerns is that clients have complete confidence that their data is safe and secure.
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Supply Chain Shaman
APRIL 16, 2024
Let’s start with definitions: Self Service Planning: Decision support technologies designed for business leaders to use analytic techniques on a collaborative platform to improve business planning. Outside-in Planning: Modeling based on channel and supply network signals. This is how we should jump. The dance goes like this.
Logistics Viewpoints
APRIL 22, 2024
Causal AI can serve as a valuable agent to help in their decision-making processes.” It analyzes new and historical order data, customer preferences, and transactions. GP describes Causal AI as a mixture of Knowledge AI and Data AI. Causal AI utilizes sophisticated causal models to make decisions on multiple levels.
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Just by embedding analytics, application owners can charge 24% more for their product. How much value could you add? This framework explains how application enhancements can extend your product offerings. Brought to you by Logi Analytics.
Supply Chain Shaman
JULY 23, 2023
Why is there a discontinuous line on the model?” This model reminds me of a snail. In each phase, companies refine the models until they find that the future is discontinuous. The evolution of planning moves from a focus on the enterprise to an adaptive platform that senses and responds based on market data.
Supply Chain Shaman
APRIL 19, 2024
The supply network–shipments and production of trading partners–represents over 70% of the environmental impact of supply chain decisions. Here I share insights on the sharing of supply data. In Figure 1, I share the importance, trust and perceived accuracy of different forms of supply data. Most is silo’d.
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Why do some embedded analytics projects succeed while others fail? We surveyed 500+ application teams embedding analytics to find out which analytics features actually move the needle. Read the 6th annual State of Embedded Analytics Report to discover new best practices. Brought to you by Logi Analytics.
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Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.
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“Supply chain analytics creates new insights that help improve supply chain decision making from the improvement of front-line operations to strategic choices, such as the selection of the right supply chain operating models.” – McKinsey & Company. Inconsistent data on safety stock levels.
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For decades, operations research professionals have been applying mathematical optimization to address challenges in the field of supply chain planning, manufacturing, energy modeling, and logistics. Learn all about this AI technique and how it can help your organization.
Speaker: Dr. Ken Fordyce, Solutions Director, Supply Chain and Advanced Analytics at Arkieva
Creating a successful plan demands a thoughtful combination of data science and computational models to anticipate structural weak points. How to avoid data-driven disasters. What structural data quality is and why it limits rapid intelligent response (RIR).
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