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How Big Data Analytics Is Reshaping Supply Chain

Srikanth by Srikanth
November 15, 2020
in Big Data
Reading Time: 3 mins read
How big data analytics is reshaping supply chain
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Big data analytics has literally penetrated even the darkest corners of the digital world, where no one ever bothers to look. With Big Data analytics everything is simple and easy, though the acquisition of the data sets is not easy. Most of the companies are trying to build every marketing strategy around the Big Data analytics. After all it has done to the world of customized marketing, we can safely say that it is reshaping the supply chain.

Quantzig, a global analytics solution provider has stated that the c-level executives of many companies are trying to incorporate Big Data Analytics into the supply chain and logistics sector of their businesses. When Big Data can truly enhance the customer experience by just carefully observing what their previous purchases are and help them take better decisions, it can most definitely help the business in Supply and Logistics sector.

Here are some highlights from the article published by Quantzig in their official blog

Supply chain traceability

Won’t it be helpful to see where exactly the product is at any moment in the supply chain? Yes, it would be of tremendous help to the businesses. The benefit of tracking the products is to prevent them from spoiling or misplacing. Today’s supply chain managers do have tools to pinpoint where the products are in the supply chain but what if they can have insights into where the products are exactly wasting time just sitting there instead they could be anywhere but there. Or, because the manager does not know how long he can store the products in the shelf – most of the products are damaged. Wouldn’t it be helpful to know how many products are sitting where for how long? After the products are scanned the data acquired from that can be used to build analytic models to survey the change using Big Data methods.

Optimized warehousing

Sometimes we just don’t know where to install a new warehouse or how big in capacity it should be. However, using the Big Data Analytics models (BDAM) we can track the previous utility of that place and design a model which can predict the needed capacity and location.

Manufacturing the right number of products

Yes, this can be difficult and sometimes it may seem impossible because managing to pull this off is extremely tedious and hard. So, instead we can leave the work to Big Data Analytics and Machine Learning. These two technologies are very effective when used together. Also, it is impossible not use the both them together. Based on your customer demand and your manufacturing capabilities, developers can build models to estimate the right number of products to be manufactured. This eliminates the problem of stock wastage!

Overall Efficiency of the supply chain

When most of the process is optimized the total efficiency will be high. That is what happens when Big Data models are precisely used. They give optimized solutions to most of the problems you may face in any part of your business and BDAM in supply chain and logistics network is not an overkill.

In conclusion, the companies who still did not adopt Big Data models will be at loss because the world is moving on and in a few years every business including supply chain and logistics network will be optimized with Big Data Analytics. Changing your ways when everyone has already adopted a technology and when they have practising the same for a few years would put you at disadvantage. The best way is to adjust your business model when you can and can spare the time and effort.

Tags: Businesslogistic Startup
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