Supply Chain and Data Analytics- Things to Know

Manufacturers, suppliers, and retailers are showing interest in using artificial intelligence to bring changes and modify their supply chain in an attempt to reduce the production and delivery cycle and also improve customer satisfaction. 

In fact, a study has shown that the top retailers are using data analytics to study customer preferences and are establishing new outlets based on predictive insights. Data science and analytics when paired with supply chain management can give a business a range of insights, predictions, and forecasts that can help streamline the entire supply chain, optimize the use of resources, and maximize the returns.

Small, medium, and large scale enterprises can use data science to revamp their business and get the much-required business makeover to fight the competitors in the market. If a business has to survive in today’s market, it needs to do more than use traditional processes and operations. Artificial intelligence, data science, and data analytics come as reliable support, especially when enterprises take the assistance of the Best Data And Analytics Companies in the industry. Nothing like having an expert help and support a business, isn’t it? 

The following are the four different types of data analytics usually used in logistics and supply chain management. 

· Descriptive Analysis: The report describes the past trends, patterns, and decisions of the business in an easy manner for the management to understand without too much effort.

· Predictive Analysis: As the name says, it uses real-time data and historical data to provide a comprehensive report predicting future trends. 

· Advanced Analysis: This is a process in which data is processed and transformed into insights that help with better decision making. 

· Prescriptive Analysis: This type uses the results of predictive analysis to provide suggestions to avoid potholes or make the most of a certain situation in the market. 

But how does data science actually help supply chain and logistics? What are the areas where the insights are used? 

ü Planning Inventory 

Automated systems combine the forecast for demand for the product and the existing stock to provide a detailed report to the business. This will prevent overstocking or understocking, both of which are not good for the business. It will also help optimize the use of resources and reduce the investment in warehousing. 

ü Warehousing 

Whether the business stores the products in its warehouse or hires the services of a third-party provider, it is important to use keep track of the inflow and outflow of products. The efficiency of warehouse management will directly impact the delivery cycle, which will indirectly affect customer satisfaction. 

ü Distribution 

The products move from the warehouse to different distributors and retailers in most instances. Be it choosing the right distributor for the right market or deciding the volume of products that need to be sent to each distributor, the decisions are made based on analyzing the real-time data of how the stock is moving in the market. 

ü Delivery 

Supply Chain Data Science uses real-time information from search engines, social media, weather, news, and important events so that the delivery will not be delayed and will reach the customer on time. Customers do not like to wait for long and even expect the deliveries to reach them before the estimated date. From that to happen, businesses should know how the external affecting factors would be and how these can be prevented from disrupting their delivery cycle. 

Businesses and retailers can get numerous advantages if they use the appropriate analytical methods to derive insights from the vast amount of data they have. The ultimate result will depend on how well the data and technology have been used by businesses. 

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Created on Oct 5th 2020 07:45. Viewed 260 times.

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