Supply Chain Management is one domain which the general masses amongst the young engineers don't seem to know a lot about and also, don't seem to see it as a hot domain to go into. However, it is the industrial leaders which understand how important Supply Chain Management is and how significantly it effects any organization's growth and development. In an article of Forbes, Industrial leader claim that "Automation in plants, fulfillment centers, and areas like procurement, production planning and maintenance is eliminating jobs. And yet overall hiring continues to rise and senior leaders say that finding and hiring the right talent is harder than ever." The question then looms above all our heads. Is this a paradox? How is it possible that when the industry is crying out and moving towards decrements of hiring, there is still a segment which has less supply as compared to demand when it comes to good talent. In today's industry, Supply Chain Management encompasses to major technologies which are relatively young in the industry and are on a steep rise. Automation and machine learning has led to a steep rise in competition and gap between the first and subsequent positions of the market leaders in supply chain management. However, the importance of supply chain management in organizations of all shapes and sizes remains highly paramount and important leading to an increase in requirement of good talent which can not only implement good Supply Chain Management practices through dedicated tools and technologies but also integrate advanced computational technologies such Machine Learning and Automation to accomplish the task. Consequentially it has become important that either the organization's hire new talent with the requisite skill set, or train their existing workforce in the skill sets which are lacking and required to compete with their competitions which are employing advanced technologies and tools to do the same job. The following are the technology domains which are required in the current industry to ensure the effective deployment of successful supply chain management models.
Several software applications and tools such as SAP APO, SAP BIW, SAP PP, etc. provide high levels of sophistication when it comes to supply chain management. The tools let the organizations decide and manage their inventories, track orders, maintain ready stock, maintain a track of orders and fulfillment, maintain track of procurement and much more. Advanced technologies may come later, but it is essential that the professionals are trained in the core technology tools which manage the supply chain.
At the root of the entire supply chain management lie optimization and approximation techniques which provide the basis of all computations required to ensure an effective supply chain management model. The professionals dealing with supply chain management must essentially also have an understanding of approximation and optimization techniques so that they have a better hold on what is happening on the background enabling them to troubleshoot issues in a better manner.
To ensure a feedback model which is self correcting, it is important that performance measurement models and tools are employed which constantly check for the increased and decrease in the performance of the supply chain management model to ensure that the work is on the right track. The better performance should be interpolated and the bad performance should be mitigated and corrected.
Possibly the biggest need of the hour is to train the workforce in advanced computational and predictive technologies such as Machine Learning, Data science, Automation, etc. These technologies are bringing to table never before known capabilities to achieve optimization and efficiency in the supply chain models. Such technologies make use of the immense computing powers on the existing data to improve the supply chain model effectively with the best possible predictions.
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