Published: 04 June 2024
Organizations struggle with mastering the intricacies of optimization techniques used in supply chain planning. To make informed choices during automation blueprinting and technology implementation, supply chain planning leaders need to learn the language, optimization options and a decision model.
Supply chain planning leaders and their teams often lack the language and understanding of prescriptive analytics, leading to misaligned value expectations.
Getting business requirements translated into algorithmic specifications is challenging due to a lack of clarity on driving factors. As a consequence, a wrong or incomplete list of algorithms gets shortlisted during the implementation blueprint.
Nonprioritized selection of optimization techniques leads to the underdelivery of expected automation benefits.
Establish a common language for discussing optimization options by learning the four types of prescriptive analytics used in supply chain planning.
Shortlist prescriptive algorithm options for optimized planning by identifying the relevant
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