An unprecedented challenge laid in front of a multinational conglomerate – a growing, complicated supply chain network that was proving to be beyond human capacity to manage. A solution would come from a revolutionary AI engine.
For the past 3 years, supply chains have been the focus of dissatisfaction across the globe – from empty grocery shelves to a shortage of essential electronic parts to the lack of new vehicles on car dealership parking lots, it hasn’t been easy for supply chains to keep up with the rise of demand under their limited capacities.
For Ingress Corporation Berhad, that issue of managing demand is multiplied threefold. Ingress is a multinational conglomerate with operations spanning across several ASEAN countries with businesses in the automotive, energy, and telecommunications industry. They have a massive network of supply chains and like any manufacturer, relies on supply chain data it receives to figure out how much demand there is in the market which in turn helps them produce the right amount of products.
Traditional forecasting and inventory management tools arethe industry standard in understanding that data and determining supply. But as supply chains became more complex, the suitability of traditional tools depreciated.
That’s why the next advancement in supply chain management is with artificial intelligence (AI) and for Ingress, that meant a total transformation. There was no other technology fit to transform an organization as complex as Ingress except for Seeloz’ Supply Chain Automation Suite (SCAS). It plays a pivotal role in reimagining supply chains using AI; consisting of a game-changing Reinforcement Learning based planning engine that’s capable of autonomously driving supply chain functions with no forecasting-based execution and no need for traditional parameter and equation-driven inventory planning.
For Ingress, SCAS applies a customer adoption methodology called “Crawl, Walk, Run”. It’s a gradual transformation of an organization’s supply chain planning process where every step has a clear set of intended goals and milestones.
In the Crawl stage, Ingress goes through a retroactive comparative analysis in which SCAS is simulated to autonomously drive supply chain decisions (procurement, production & cross-warehouse movements) in a specific past period while receiving the same demand at the same receipt timings (e.g., exactly as the As-Is system received it). Throughout this process, all decisions taken by the As-Is system are hidden from SCAS, which runs periodically (at the same frequency at which the As-Is MRP/DRP engine runs). It’s during this stage SCAS uncovers areas of improvement and unlock potential benefits that helps Ingress manage their data far more accurately, allowing a more detailed view of their operations.
Next in the Walk stage, we integrate SCAS to be ready for the end-to-end supply chain life cycle. The goal is to successfully integrate and productionalize SCAS to replace Ingress’ traditional demand planning and operations research driven inventory planning with an Al engine that autonomously generates supply chain planning decisions. The engine manages procurements, production orders, & cross-warehouse movements at unprecedented levels of timeliness, accuracy, and profitability.
And finally, at the Run stage, SCAS takes the lead on autonomously driving planning workflows under full supervision of Ingress’ supply chain planners. At this stage, they are empowered through SCAS to confidently manage their entire operational workflow with ease and maximum efficiency.
Traditionally the planning and managing of supply chains have relied on human intuition and MS Excel-driven optimization. A process that has proven to be beyond human capacity and unreliable. With an increasingly interwoven supply chain network, Ingress sees and understands the benefit of SCAS and Seeloz AI can bring to transform and modernize its supply chain. The issue was never when to implement AI within their organization, but how. In a complex issue like supply chain planning, AI is a complicated tool to implement but what we have proven so far to Ingress is that Seeloz makes it incredibly easy to implement.
Our methodology of “Crawl, Walk, Run” seeks to help Ingress and any organization change into the company of tomorrow.
With the success of Ingress, Seeloz’ SCAS is proving to be the new global standard in supply chain automation. Our mission is to redefine supply chains with the power of AI and SCAS is here to help.