In the article Big Data Analytics and the Evolution of the Supply Chain, the author gives an overview of how big data analytics can be beneficial to a supply chain. He delves into supply chain challenges and how big data analytics can help solve these challenges as well as the use of how big data analytics can revolutionize the supply chain. Big data is widely recognized as a way to better business operations, but its applications are just starting to make the impact everyone believes big data should have.
The use of big data can increase efficiencies in a supply chain by 10% or greater while also decreasing risk. This decrease in risk is due to the predictive power of looking at older big data and applying it to potential future problems. Big data analytics can increase traceability in the supply chain by reducing time need to access and manage product databases. Finally, big data analytics can make companies operations safer in volatile markets by making them five times more likely to report shortened order-to-delivery cycle times.
In overall operations, Big Data Analytics can optimize delivery networks using geoanalytics. It can allow companies to deepen their relationships with suppliers with more detailed vendor profiles. Finally, Big Data can have predictive powers. Using historical data on suppliers can lead to predictive lead times which eliminates guesswork. In summary, Big Data used correctly can lead to large efficiency gains in a supply chain.
How confident do you feel about the predictive power of Big Data?
Will there come a point when there is too much Data collected and the analyzation of such data could potentially hurt processes?
How close are we as an industrialized society to having to use Big Data in our supply chains to be competitive?