This series explores the many supply chain-related use cases of AI, starting with pricing and promotion
Service Supply Chain
Supply chain to provide service, repair, maintenance, and implementation, including spare parts supply chain, repair equipment supply chain, technician/resource management, etc.
Agile Demand-Supply Alignment – Part 2E
A discussion of requirements for Agile Demand-Supply Alignment (ADSA) solutions for demand management (demand-side visibility, time-phased views, POS and channel data visibility, order pegging, demand sensing, retail planning capabilities), and analytic capabilities (e.g. supplier performance, carrier performance, lead-time analytics, total landed cost optimization.)
AI for Supply Chain: Debunking the Myths – Part Two:
We debunk myths about AI vs. human thinking, AI autonomy, the role of data, open source AI, the role of data scientists, and AI’s impact on jobs.
Supply Chain Orchestration: Part Two
One important way that Supply Chain Orchestrators manage multiple tiers is sourcing and buying on behalf of their suppliers. Learn how and why that is done.
Agile Demand-Supply Alignment – Part 2D
Here we look at what is needed for a platform to provide Agile Demand-Supply Alignment functionality in supplier-facing functionality (e.g. sourcing, production management), quality management, and logistics and global trade. These include areas such as production visibility, supply risk management, quality management (detection and resolution), and logistics capabilities.
Agile Demand-Supply Alignment – Part 2C
We cover required characteristics of a multi-enterprise network architecture, such as a shared single version of the truth, multi-enterprise master data management, security, process flows, and an integrated network of trading partners. We also delve into the differences between a ‘Visibility-only Control Tower’ vs. a ‘Supply Chain Application Network.’
AI for Supply Chain: Debunking the Myths – Part One
Previously intractable challenges that supply chain professionals have been grappling with for decades are now within reach using AI/ML. These include fixing new product introductions, stock-outs, optimizing inbound through outbound fulfillment, and improving profit margins.
Supply Chain Orchestration: Part One — Multi-tier Relationships
For some companies, managing only their immediate suppliers is not sufficient. Brand owners whose reputation and competitiveness is on the line for the performance and social compliance of the whole chain are increasingly taking on the role of Supply Chain Orchestrator, coordinating key activities across multiple tiers of their supply chain.
Agile Demand-Supply Alignment – Part 2B
A framework for understanding Agile Demand-Supply Alignment solutions. We present questions to ask solution providers about how they detect, contextualize, prioritize, predict, and prescribe solutions for demand-supply imbalances.
Seven Steps Toward an Autonomous Supply Chain
Systems and companies are evolving incrementally towards autonomous supply chain execution. Here we outline seven steps to autonomous supply chains.
Geospatial Intelligence – Part Nine: What to Look for in a Modern Supply Chain GIS System
Taking the longer view, companies can select a GIS platform that can serve as an enterprise-wide platform for many different applications. Here we discuss the characteristics to look for when selecting a platform.