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Planning for supply chain optimization

Are advanced planning and scheduling systems (APS) transforming supply chains today? Explore how artificial intelligence (AI)-driven decision-making can reshape your planning process. This first article in our series dives into achieving the right balance between human expertise and AI collaboration.

Rethinking the value of planners

The past five years have been a period of significant learning for organizations navigating through changing consumer trends and global supply chain disruptions. Organizations that have a clear understanding of the value creation and loss areas of their business have a distinct advantage in these volatile market conditions. At the heart of it, all business value is created or destroyed in two ways:

  1. By the quality of the decisions you make
  2. By the quality of your execution

Traditionally, planners have been caught in the minutiae of data processing, firefighting and using heuristics to “get the job done.” As planning is a wholly decision-centric process, the ability to provide automation and decision support tools allows planners to focus on optimizing their value-creating decisions. An APS solution is a key enabler that provides the potential platform for planners to have all the right information required to make decisions that drive value for the business when they are designed and implemented well.

Understanding the nature of different decision types

The implementation of an APS represents the opportunity to automate much of the low-level decision-making, allowing planners to focus their effort where it delivers the most value. As you can’t—and shouldn’t—systematize every aspect of an organization, there will always be a need for human-driven insights and decisions. We categorize decisions in terms of the human and machine boundaries:

Decisions that are wholly contained within the planning system. There’s a high confidence level that the engine will make the right decision.

Decisions made by the APS engine that require validation and acceptance by planners, based on a review of factors external to the system. There’s a medium confidence level that engine will make the right decision.

Decisions that are supported by APS outputs but are not wholly included within the planning system. There’s a low level of confidence in the engine to make the right decision, due mostly to not having the required information/data at the right level of quality.

A more holistic approach

Instead of focusing on technology capabilities only, our decision-based approach shifts the focus to decisions, whether fully contained in a planning tool or not. This approach catalogs your key business decisions, identifies those that deliver the highest value based on your supply chain and business nuances, and then shapes the APS design and implementation to sequence for early value and maximize the return on your investment.

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