Impact of Data Science on Supply Chain Functions
Driving operational growth and boosting supply chain efficiency are among the top priorities of many organizations in today’s ever-changing business landscape. In order to grow in a fast-evolving marketplace, an organization must have the ability to use advanced data analytics and algorithms to catch the next wave of supply chain management.
With the plenteous data flowing in from different sources and access to advanced technologies to help harness the power of the data, organizations must form and implement effective strategies to organize data, analyze and ultimately garner actionable insights to improve their supply chain processes. Data Science helps you extract business value from your digital information through scientific processes, methods, analytics, machine learning, algorithms and systems.
Below are some of the ways that data science is impacting supply chain functions.
Better demand forecasting
Through predictive and prescriptive analytics, businesses can improve the accuracy of demand forecasting. As the demand behavior constantly changes due to several factors like new trends, product innovation, government laws, tariffs etc., the modern enterprises need to have a thorough understanding of the consumer demand for their goods and services. Improved demand forecasting accuracy powered by advanced analytics leads to improved production scheduling and inventory management.
Smart pricing
Advanced analytics is based on science. It helps you intelligently price your company’s product range by analyzing several information. It identifies different factors like the government policies, the current state and global economic situation and customers’ preferences. By analyzing these factors, data science helps you develop effective pricing strategies for your products and services.
Improved distribution mechanism
Thanks to advanced technologies that distribution centers now can collect huge amounts of structured and unstructured data, which can yield powerful business insights when analyzed accurately. Today, data science is enabling businesses to predict fluctuations in demand, optimize delivery routes and manage workforces with a higher level of efficiency.
Better support to customers
Artificial Intelligence and data science enable maximization of customer support to customers, sales force suppliers and wholesalers through technologies like voice-activated assistants and chatbots. These technologies help the support team (call center) provide more accurate information like expected delivery times more quickly. Technologies like Blockchain and AI also help the support team detect procurement fraud more effectively.
More efficient procurement
Analytics can be utilized by procurement organizations to define, predict and improve business performance. Procurement analytics enables data-driven decision making. Augmentation in this area will drive speed in product development cycles, improve responsiveness, lower costs, increase production efficiencies and quality and foster better relationships with suppliers.
Data Analytics is transforming the supply chain of businesses of every industry and will continue to do so. It’s most important contribution to the manufacturing industry is that it allows manufacturers to reduce their product life-cycle times that in turn helps them react to customer demand and market trends more quickly.
Data Science in supply chain management
Better demand forecasting
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