Supply Chain Management Algorithms and their application in planning software

Software-based supply chain management through big data, self-learning artificial intelligence (AI) and advanced analytics

Supply chain management algorithms – such as heuristics, mathematical solver-based optimization methods and (advanced) analytics – describe a wide range of analysis methods that are used in supply chain management. Advanced analytics is no longer limited to analysing historical data through descriptive analytics (the question of "what happened?"), but focuses on predictive ("what will happen?") and prescriptive analytics ("how can I achieve it?"). By using analytics with regard to the future, planning scenarios can be mapped and – based on predefined and/or prioritized/ranked goals such as maximum customer service level, customer segmentation, margin-optimised production programme, etc. – automatically executed.

With the application of supply chain management algorithms, a primary goal is formulated: (Data) modelling of complex end-to-end planning scenarios in Supply Chain Management, Sales & Operations Planning and  Advanced Planning & Scheduling.

Supply chain management algorithms and AI-empowered applications as integral planning tools in supply chain management:

  • Application of Artificial Neural Networks (ANN) in demand planning and sales forecasting
  • AI-aided controlling of the trade-off between delivery reliability and tie-up capital in inventory management
  • Autonomous Planning and Scheduling: Turning the MRP-run into an agile real-time AI-process
  • Holistic Energy Management as an Integral Part of Production Planning
  • Reactive scheduling as AI-supported agile process that remains open up to the last minute
  • (Partially) automated and self-learning AI-assisted decision-making processes including alert functionalities.

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A Milestone on the Way Toward Planning 4.0: The Application of Big Data Along End-To-End Supply Chain Management

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Big Data, Artificial Intelligence (AI) And Autonomization in Supply Chain Management
Multiple Options Become Available – Already Today and in the Very Near Future

 

Big Data, Artificial Intelligence (KI) und Advanced Analytics might help to capture and process complex information and data structures during the planning run. With their support, a solid basis of decision-making can be issued and thus be prioritised on (pre)defined criteria in order to meet certain objectives. Thanks to their ability to act independently, it can relieve employees of routine tasks. Long-term data generated by AI and ML can hence provide valuable criteria for strategic decisions.