Andrew Lencsak
Argano - Director of Delivery - East Region
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Based out of New England, Drew has been in Dynamics since 2008. He started as a Production planner, Lean specialist, and business analyst for a leading manufacturer of Photonics products. In 2013, he joined a Microsoft partner as a Functional consultant specializing in manufacturing. Since then he has worked on ~50 implementations of AX3.0, AX4.0, AX2009, AX2012 and D365FO across the globe as a Sr. consultant, Solution Architect, Delivery lead for Manufacturing and Supply Chain, and now Director of ERP Delivery.
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The New Demand Planning App Meets Copilot
Introduction to the new Demand planning app in D365, an overview of its features and integration with Copilot, as well as use cases and real world scenarios.
Demand Planning Unplugged
Learn all about the new Demand Planning app and its features highlighting collaboration, flexibility, and visibility from a Microsoft MVP in AI ERP and Azure AI Bot Service. Demand planning provides what-f analysis, full version history and control, customizable worksheets, aggregation and disaggregation, and native integration with D365 Supply Chain Management, Teams, and Copilot.
Order Delivery - 5 Forms in 5 Minutes Each
5 minutes on 5 forms to help serve order fulfillment in D365 Finance and Operations / SCM. 1) Available to Promise (ATP) Information, 2) Net requirements, 3) Supply Schedule, 4) Planned Orders, and 5) Explosion.
Making a Use Case for Multiple Master Plans
From projecting the impact of potential sales on your inventory levels and spend to creating level load build plans, multiple master plan setups enable companies to prepare for whatever their supply chain throws at them. Join us to see real examples of these scenarios.
Demand Forecasting in D365 F&O, Azure Machine Learning, and D365
Learn how to setup and use the Demand Forecasting functionality in D365 for Finance and SCM. We will talk through the algorithms available for forecasting and how you can tweak the settings and control the machine learning project. We will also discuss examples of how to extend the functionality and bring more life to your machine learning project. Learning Objectives: understand Time series models and algorithm parameters needed for statistical forecasting in D365; understand how to use Forecast models for forecast comparison and analysis; define how forecast models can be used to feed plans and fulfill an S&OP process.
Andrew Lencsak
Argano - Director of Delivery - East Region
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