- Orchestration Starts with Information
- Modeling the Real-World Supply Chain Ecosystem
- Orchestrating for Sustainability
- Achieving a Balanced Digital Ecosystem
Once upon a time, back when decision cycles were longer, supply chain designs could be linear and relatively uncomplicated. But today’s supply chains should not be thought of as linear. They are better conceived of as connected ecosystems that link people, places, activities, information, and resources over time and across all layers of a far-reaching, often global, ecosystem.
Everyone in the supply chain ecosystem has a common goal: create and/or move products from suppliers to customers in the most effective and efficient way achievable. As global supply chains become more interconnected, the focus moves beyond simple operational efficiency toward end-to-end orchestration of the ecosystem.
All participants, be they customers, suppliers, manufacturers, or trading partners have their own role-based needs. Decision makers succeed or fail based on having accurate, up-to-date information to trigger the right actions. Partners need access to timely data and relevant functions so they can deliver the right inventory to the right place at the right time. Supply chain orchestration aims to keep stakeholders across the end-to-end value chain in sync and aligned with near-perfect operational visibility, updated information, and efficient collaboration. For instance, if port congestion delays cargo, this fact should immediately trigger the search for alternative transportation sources, while incorporating factors such as container sizes and truck load capacities in negotiating new freight rates spontaneously.
Orchestrating the planning effort across the ecosystem creates the unified ability—and agility—to handle changes in consumer behaviors and expectations, supply chain shocks and disruptions. Too often supply chain decisions are based on stale and static data. The right supply chain planning technology allows a company to take advantage of increasing volumes and types of data in real time and make decisions with greater efficiency and responsiveness. Supply chain ecosystems enabled with machine learning are able to increase visibility and drive profound insights based on inputs from a vast spectrum of IoT sensors, instrument telemetry, point of sale information, weather conditions, market monitors, and more.
Any community of people, objects, the environment they occupy, and the interactions among them—is dynamic. Any ecosystem is hit with periodic disturbances; its ability to react and reorganize to remain close to its equilibrium state is called its resilience.
A key to building resilience for a supply chain ecosystem is the ability to model the real-world using a digital twin. A digital supply chain twin is a virtual replica that duplicates the behavior of the physical supply chain end-to-end, including its responses to real-world changes. When kept in synch with the entire ecosystem, a digital twin dynamically reproduces the relationships between supply chain entities. It provides a laboratory for experimenting with business scenarios and what-if analyses. Simulations performed on the digital twin can compare what is happening in the supply chain today against historical data and potential plans related to capacity, demand, or inventory. This creates powerful prescriptive insights and drives confident predictions that anticipate consequences.
The digital twin is a testing ground for strategic, operational, and tactical plans based on a common data model and “one version of the truth” that incorporates real-world parameters such as leads times, set-up times, bill of materials, and more.
Companies are being called on by investors, consumers, and regulators to reduce, reuse, and recycle. Sustainability initiatives are ubiquitous, focusing on a range of issues such as how to cut harmful emissions related to supply chain operations. Orchestrating the digital ecosystem through a unifying planning platform promotes better network design can align components based on sustainability KPIs. Again, better visibility into the end-to-end supply chain allows planners to identify, focus on sustainability efforts that yield the greatest benefits.
In a global climate rife with volatility, supply chain shocks, and shifts in revenue, supply chain planning must remove silos, synchronize stakeholders, maximize resources, and link planning to execution for greatest efficiency. When an advanced planning platform can break down function silos and unify all stakeholders around one version of the truth, the door to orchestration opens wide. The multi-enterprise ecosystem becomes transparent and supports seamless collaboration both internally and with 3rd party providers. End-to-end supply chain visibility enables orchestration around the full lifespan of a customer order, from demand and supply planning to manufacturing, warehousing, and delivery. All elements in the ecosystem work intelligently in concert to automate and optimize order flows while taking into account key supply chain constraints such as inventory, costs, time horizons and capacity.
John Galt Solutions offers the Atlas Planning Platform, an advanced supply chain planning technology platform that has helped hundreds of companies master the interconnectedness of their multi-enterprise supply chain ecosystems. Let’s take a look at how your business goals can be realized through intelligent orchestration.