A supply chain is the end-to-end system that creates products and services like a theme park, distributes them to customers, fulfills them like a retail store or solar installation company, and gets raw materials, ingredients, components and finished goods back into storage, distribution or the manufacturing process. It requires the management of complex inventory, purchasing, transportation, client service, invention scheduling, vendor relatives, and warehousing processes and technology.
Many traditional planning processes take place within functional silos that lack the ability to synchronize schedules and share data, leading to high risk, waste and latency. Concurrent planning eliminates these silos, enabling planners from different areas to have access to the latest information and make better decisions in less time.
As such, concurrent planning is a key part of a network-centric approach to supply chain planning that supports improved cost, accuracy, visibility and resilience, as well as greater agility. However, to succeed, a network-centric approach must be supported by the right technologies, including advanced analytics capabilities.
These tools include advanced forecasting, predictive and prescriptive analytics. They enable a broad range of applications, such as what-if scenarios, digital twins, AutoML, demand sensing, and much more. Generally, these are built into a scalable, flexible and powerful supply chain execution and planning platform designed to support fast, connected and collaborative business operations that align people, processes and data. The best solutions leverage cloud services, always-on algorithms, in-memory databases with direct memory references and efficient versioning engines to drive capabilities like these.
