It is the use of data and analytics techniques to improve the performance of the supply chain. This can involve analyzing data from various sources, such as sale data . production data, and transportation data, to gain insights into the performance of the industry.
Some potential applications of supply chain analytics include demand forecasting, inventory management, and network optimization. By analyzing data and identifying patterns and trends, organizations can make more informed decisions about how to manage their industry, leading to improved efficiency and cost savings.
It can also be used to improve the sustainability of it. By analyzing data on the environmental impact of different activities, organizations can identify opportunities to reduce their carbon footprint and improve their environmental performance.
Overall, the use of it can help organizations to better understand their operations and make data-driven decisions that drive performance improvements.
Descriptive Analytics
It can be seen as the baseline of the industry, which basically assesses past and current data for more meaningful insights and delivers it to the people to use their own intelligence and knowledge to make decisions.
Predictive Analytics
A slightly different version of it that analyzes historical data and identifies future events to synthesize information for actionable insights and ensure better decision-making with increased efficiency and lower cost
Prescriptive Analytics
Prescriptive Analytics builds on Predictive Analytics and dives deeper into predicting future insights on what next can be done. With the Sophisticated ML Model, deeper insights can be delivered to the managers to see how different scenarios align and what the results could be when going with one of them.
Cognitive Analytics
With the use of AI in the industry, answering complex questions and drawing out contextual conclusions on how humans would have interacted with the situation. It helps with more meaningful data and scale experience and knowledge with better decisions.
Diagnostics Analytics
Analyzing overall performance and figuring out why errors, mistakes, and delays occur. It lets the manager know the delays, breakdowns, and disruptions in the demand and supply processes and the reasons behind them.