Integrate data to create a dynamic supply chain that meets fast-changing needs
Conveyor_Belt Supply chain logistics

Integrate data to create a dynamic supply chain that meets fast-changing needs

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Today’s supply chains must overcome continuous and rapid change

Pervasive digitalization. Multiple delivery channels. New entrants to the market that have retrained consumers to expect on-demand access. A pandemic accelerating trends. All of these factors are coming together to create challenges for supply chains.

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Get the blueprint for dynamic supply chains

Explore how to create accurate and reliable forecasts and demand plans, and optimize analytics, for supply chains. This detailed architectural blueprint shows how organizations with Teradata can:

  • Meet and exceed customer expectations
  • Maintain cost excellence
  • Improve a company’s sustainability footprint
  • Optimize omnichannel inventory
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Customers want instant gratification

Customers expect to buy the latest products on-demand, through their preferred delivery channel. This challenges supply chains to have the right product in the right place at the right time, and at a competitive price.

Solving this challenge requires retailers, consumer packaged goods (CPGs), and other industries to bridge the gap between lead times and consumer expectations.

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Still using seasonal trends and legacy buying habits to predict consumer needs?

Customer behaviors are constantly changing. Making buying predictions based on simple drivers such as seasonality and previous purchasing habits alone are too slow moving to meet the needs of modern companies.

Today’s complex environment requires a shift from basic forecasts and demand plans to a dynamic, agile supply chain that’s continuously optimized based on real-time data insights.

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Inventory

Create the supply chain of the future

Organizations can modernize their supply chain by moving to:

    • Forecasts that refresh at or near real time
    • Integration of all data, including new data
    • Better predictability using clear signals
    • Multi-layered models that identify changes as they occur

Forecasting and demand planning accuracy is one aspect of an efficient and predictive supply chain. This enables a dynamic supply chain that strategically balances customer expectations for high service levels with cost, quality, sustainability, resilience, and agility.

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Case studies

High-impact results for retailers

A European general merchandise retailer saw a 2.2% increase in sales after leveraging a multi-layer model that integrated new data and improved forecasting accuracy from 66% to 77%.

A grocery retailer increased sales of baked goods 12% by using real-time sales feeds to forecast and deliver demand plans directly to stores.

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