Adexa’s technology is now deployed for Seagate’s purchasing, production, and distribution planning, across operations expanding over five continents.
According to Gartner, there can be no effective sales and operations planning (S&OP) process without an S&OE—Sales and Operations Execution, process. In other words, why make a plan if cannot be executed accurately or cannot be translated into execution?
Adexa solutions deploy attributes to define the characteristics of machines, processes customers and suppliers, in order to mold the solution to a particular environment.
In recent years AI and machine learning have had a major impact on how we run our businesses. They have also influenced the way we make decisions in supply chain planning. As a result we are now in a position to have a supply chain planning system that may have enough intelligence to grow and change with the organization on its own!
Adexa’s Machine Learning Predictor, GENIE©, is designed to predict inefficiencies in the supply chain as well as identifying the main causes of late orders. In its analysis, GENIE© examines not only the internal data but also exogenous data such as weather, season, supplier or customer locations and many others.
Most supply chain professionals and planners think of finished goods when they hear attributes. But attributes are present in every part of the supply chain from suppliers to raw materials, to machinery, products and distribution centers.
Many companies say that they want to Optimize Inventory, but they often have different things in mind when they say it.
Why do we need Attribute Based Planning? Attributes are properties specific to an object. In a supply chain, like anything else, everything that you deal with has attributes.
What sets planning and execution apart is really the horizon and timing between the time a decision is made and when it is realized. In general, we plan for responsiveness and execute for reliability.