The first revolution in supply chain planning technology happened in the late 1990s with the first generation of advanced planning and scheduling software. Those early solutions for forecasting and demand planning were game-changers, especially in a world with relatively low supply chain complexity and variability of supply and demand.
Yet even without supply chain disruptions, the volume of decisions that must be made has grown beyond the ability of traditional planning approaches and legacy technologies to keep up. Today’s businesses need more robust tools to close the gap between planning and execution.
Companies have become very good at defining mid- to long-term plans leveraging the capabilities of the APS, and at executing on those plans with ERP and other enterprise systems. The clear gap is in the S&OE horizon – wherein the volume of decisions is highest and speed is most critical, but everything is still managed manually.
Creating a New Approach to Supply Chain Planning
To begin with, supply chains should be designed to support agility, transparency, resilience, and sustainability. You need a solution that will support the definition of an optimal supply chain operating model.
In our recent Future Now series webinar, now available to watch on-demand, we discuss the steps in creating this outcome – including choices for your technology stack and how companies can identify risks in real time, quantify them, and respond more quickly. This quick response is key to avoiding lost revenues or increased costs incurred by not closing the gap between planning and execution.
Real-time, data-driven decision making demands a solution that flags decisions for rapid human execution – one that can even act on those recommendations autonomously when desired. Decision Intelligence is built on intelligent technologies such as artificial intelligence (AI) and machine learning (ML). It is the process of digitizing, augmenting, and automating decision-making processes and has been called the “killer use case” for AI.
For example, consider the workflow for materials planners. Traditionally, they would have used advanced planning software to set and protect the plan during their previous monthly/weekly cadences. They would then start every week by reviewing the stockout alerts generated due to changes in demand or supply. Next, they manually gather data and evaluate options to reallocate deliveries or rebalance, followed by aligning those changes with logistics and suppliers. (In many cases, however, these processes leave no record of the decision that was made or its context.) Lastly, teams create stock transport orders (STOs) and adjust purchase orders (POs) manually.
With Decision Intelligence, materials planners need only to review allocation and rebalancing recommendations that are always on, delivered in real time, with 100% SKU coverage and the capability for automated decision making and execution.
Improving Efficiency Across the Enterprise
Aera Decision Cloud™ helped a global fast-moving consumer goods (FMCG) company implement Decision Intelligence. This company needed a solution to address the acceleration of consumer segmentation, the demand for hyper-personalization, and the “anytime” demands of customers who wanted more options and faster order fulfillment.
After implementing Aera’s Decision Intelligence platform, this company saw the amount of time planners spent looking for information reduced from 60 to 70% of their workday to less than 20% of their day. As a result, those planners were able to spend more time looking for new solutions to strategic challenges.
With Aera Decision Cloud driving faster and more accurate decision making, companies make decisions more quickly, enabling them to stay competitive and capture greater market share.
Watch our on-demand webinar, "How Decision Intelligence Connects Planning and Execution to Manage Disruption," and learn how Aera Decision Cloud complements, enhances, and extends planning capabilities – making companies more agile in the face of disruption.