Machine learning is something that feels like it is taken from a science fiction film, but in reality, it is the next wave of skills expected to be found in all computers in the immediate future. Machine learning is an application of artificial intelligence that allows computers learn from experience while undertaking tasks without having to be programmed to change patterns and behaviors in order to improve their performance. Machine learning, in general, relies on the ability these machines will have to change when exposed to new information.
Ok, but what does this have to do with analytics and supply chain management? Well, if you think about it could have a lot to do with it in the near future. Supply chains must always focus on finding ways to lower their prices while accomplishing faster deliveries, deal with things like the volatility of demand in the market and the staggering amount of products available while at the same time meeting the expectations of customers that continue to grow higher in quality and complexity every passing day.
Something that we all agree on, is that successful companies in the area of logistics like Amazon and Netflix, rely heavily on machine learning to take care of the business processes and offer customers some of the best service available. Artificial intelligence is no longer a vague term far removed from the public but instead, it is a force that is impacting the way business is conducted and how companies plan their strategies to remain relevant and to keep up with the pace of competitors in the world of logistics.
There are many factors that impact the supply chain and customer demand, and a system that wants to apply machine learning into the development of their own strategies must consider things like trends, innovative new products arriving in the market, the effect of media events, statistical forecasts, patterns, market intelligence and internet indicators just to name a few. Machines that learn must start from a baseline that provides them with the most accurate picture of the current market and then a way to create rules based on an expected behavior so it can create more accurate forecasts.
When we talk about things like this, we cannot pretend that “Big Data” is simply a buzzword that gets thrown around to seem hip and must start paying attention to its implications inside the supply chain. Big data provides information on real-time about an assortment of variables that allow us to capture more information than just the usual demographics of customers paired with superficial facts like date of purchase and method of payment. We actually want to go beyond that and gather information that will allows to get to know the customer in such way that we will be able to anticipate what they want before they even know it themselves. This information can be gathered by truly getting to understand the customer’s transactional behavior beyond the items that are directly relevant to the products and services we offer.
The Internet of Things is the way that physical objects can communicate amongst each other by using the Internet to transmit information that is relevant to the cohesion of the supply chain. Learning machines will also analyze all of this information in order to ultimately optimize processes in ways that we can only imagine. The input from operators will be reduced for mere supervision and routine checks while these powerful devices can run on their own and reduce mistakes and time wasted to a minimum. There are still many challenges associated with the use of the IoT to run operations and most of these challenges have to do with security and the vulnerability these systems can have and how they are affected by the human factor.
The cloud-based computer is another aspect to consider when it comes to establishing parameters for the way that machine learning operates. Clouds allow us to decentralize data so it can be used in the best way possible by the right people and the proper moment. This enhanced visibility and transparency allow the supply chain to work smoothly and to enjoy a type of collaboration that can be defined as seamless. Organizations can enjoy a flexibility and efficiency that was unheard of before as they will be able to react to eventualities quicker and with a wide arsenal of solutions right at their fingertips. Machines are better than humans at optimizing the way repetitive tasks are done and can make the best decisions based only on the data available. That type of detachment and analytical insight is what will revolutionize the supply chain of tomorrow and that is why we must start paying attention to these trends today, so we can be ahead of the curve and make the right decision for our businesses.
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