The New Digital Era Demands More
Almost all conventional S&OP solutions are big and heavy pieces of application that suffer from data and decision latency. Today’s supply chains need to be fast enough to receive and respond as well as predict events in an almost real-time manner. Prediction is critical because on many occasions there is no time to respond. Systems need to be able to provide accurate digital twins that can represent and act as the digital avatar of your supply chain. They need to provide reliable real-time ATP/CTP to incoming orders and deal with changes and disruptions by predicting them and responding accordingly. Current S&OP solutions are a dead end. Plans created by current S&OP solutions are not executable without user intervention and laborious adjustments by users. The answer for most of them is to add S&OE in order to get much better and executable plans. But his could have been avoided in the first place. Planning and execution are a continuum not separate processes and systems.
The future demands the ability to predict based on an accurate representation of the physical supply chain. Thus, allowing the digital driving the physical. Prediction of events is a science with the use of AI/ML technology. But the premise is to have the right data and an accurate model. The rough high-level model of the conventional S&OP solutions fails to provide adequate insight since they are too high level, cannot listen to all the signals that are constantly coming in and are too slow to act.
In a recent research, it was estimated that that for a $10 billion company with a well-performing supply chain, that can “listen” and respond to events, has the potential to raise earnings by up to two percent, boost sales by $150 million, and reduce costs by $50 million. Listening and the ability to respond seems to be the first step to not just survival but also growth.
The future supply chains require a distributed architecture that can constantly listen to all the relevant signals, i.e., sense, and act while learning and getting better. As human beings our ability is limited to only seven variables at any point in time. Systems are capable of several orders of magnitude more. Receiving alerts and notifications are good but not manageable when you have hundreds of events happening in your global supply chain, coming from suppliers, customers, transportation systems, new regulations, geopolitical and socioeconomic events.
At Adexa, we have created a distributed architecture that is scalable as the complexity of the supply chain grows and additional dimensions appear. The architecture comes in the form of distributed intelligent processes that are tasked to perform business functions by sensing, acting and learning. They can monitor and respond as well as predict anything from web traffic to weather issues, safety stock changes, cost fluctuations, carbon emissions etc. we refer to these intelligent processes as Adexa Genies©. They are intended to be the avatars of planners and other business functions. More importantly, the architecture allows a continuity of planning and execution. Unlike current S&OP solutions that deliver a rough plan to be manually adjusted and corrected, Adexa architecture forms a continuum of plans to execution based on granularity and frequency of available data and signals. As mentioned earlier, the ingredients are a true digital twin (ability to model the supply chain accurately), ability to listen to relevant signals and be fast enough in near real-time while learning from experiences and available data.
The digital era is here with that comes Industry 4.0. For those companies who have already implemented S&OP solutions, the challenge is having the capability to autonomously execute the plans. That may come through a disjointed S&OE solution that is far from optimal. Yet it is essential to start building S&OE solutions in order to build a true digital twin, the basis of the future supply chain planning capability. For those companies considering S&OP, ask yourselves a simple question: How do I execute the plan? Through laborious manual adjustments? Is that the best way as your supply chain gets to be more complex? Alternative is having a system that keeps improving as the data becomes available automating the execution while providing visibility and more importantly learning from its experiences.
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