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What Today’s Modern BI Systems Do That Legacy Reporting Tools Can’t

Silvon Software

Analytics and business intelligence (BI) are no longer optionaltheyre essential. Thats why modern BI systems are quickly becoming the go-to solution for data-driven enterprises. They integrate, align, and activate data across the business to drive better, faster decisions unlike legacy reporting tools that can’t.

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Machine Learning in Demand Planning: How to Boost Forecasting

ToolsGroup

Beyond simply improving forecast accuracy, todays ML-powered demand forecasting software uncovers hidden supply trends, anticipates pricing fluctuations, and enables proactive supply chain planning decisions. According to McKinsey , organizations implementing AI-driven demand forecasting solutions can reduce forecast errors by 30% to 50%.

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Making Supply Chain Planning Agile With Modular Planning Technologies

Logistics Viewpoints

We need planning platforms to keep up with all the changes. This means we need more agile, flexible, and scalable planning platforms to process and consolidate new data sources, drive insights using advanced analytics such as AI/ML to drive autonomous decisions, and expand collaboration within and outside our organizations.

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The Future Of Retail: Technologies Enabling Q-Commerce Growth

Logistics Viewpoints

Millions of shoppers, like my Dad, are not going back to their old habits because there are now faster and more convenient ways for buying daily household needs. It excels on a union of E-Commerce mobile apps and last-mile delivery innovations. It also provides an excellent part-time employment opportunity with flexible shifts.

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Top Supply Chain Challenges for CPG companies in 2023

Logistics Viewpoints

End-to-end supply chain visibility, planning, and execution support software are critical in agile supply chain performance. The classical approach involves functional silos, sequential decisions, and Excel and people to render a plan executable. each with discrete plans generated typically in sequential batch runs.

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Pandemic Lessons For Supply Chain Leaders

Supply Chain Shaman

The systems–based on shipment and order data–were out of step with the market. With fixed models and hard-wired data feeds, teams could not adjust the planning systems to use consumption data or market indicators. Resist the temptation to place deeper analytics on top of existing data models. The reason? Next Steps.

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Driving Supply Chain Analytics User Adoption with Cross-Departmental Metrics

Logility

User adoption is a challenge that often arises during the rollout of supply chain analytics solutions. Users are accustomed to building everything in Excel and manipulating the data as needed for their own particular use, typically using static reports or spreadsheets that are siloed in specific departmental needs.