Analytics is a relatively new term, but it has already become an indispensable part of our lives. This can be seen in the rise to the prominence of data scientists responsible for gathering & analyzing vast amounts of data from various sources. Data scientists have been instrumental in shaping how companies do business and creating tools that help them explore their data.
Analytics and Supply Chain Management: The Conjunction
Analytics and Supply Chain Management are two areas that have seen a significant transformation in the last few years. Analytics is now being used to improve customer experience, which has become one of the most important goals for businesses.
Supply Chain Management training is being used to increase efficiency throughout the entire supply chain, from production to delivery.
The role these two departments play in business cannot be understated- it’s more evident than ever that they are shaping new-age careers!
How has analytics become an integral part of supply chain management?
Supply chain analytics is the process used by organizations to gain insight & extract data associated with procurement, processing, and distribution. Supply chain analytics is an essential part of SCM.
The mathematical models, data infrastructure, & applications supporting analytics have evolved significantly. This improvement came from better statistical techniques, predictive modeling & machine learning.
Data infrastructure has changed with cloud infrastructure, complex event processing & IoT. Applications now provide insights across traditional application silos such as ERP, warehouse management, logistics & enterprise asset management.
Features of Supply Chain Analytics:
Data visualization: The ability to derive and reciprocate data to have better insights.
Stream processing: Deriving insights from wide data streams
generated by IoT, applications, weather reports & third-party data.
Social Media integration: Using data from social feeds to improve planning.
Natural Language Processing: Extracting & organizing unstructured data in documents, news sources & data feeds.
Location intelligence: Extracting insights from data to understand and optimize distribution.
A digital twin of the supply chain: Organizing data into a comprehensive model of a supply chain can aid in improving predictive & prescriptive analytics.
Supply Chain Analytics Uses
- Identifying and improving risks & predicting future threats based on patterns & trends throughout the supply chain.
- Boost planning accuracy by analyzing customer data to identify factors that increase or decrease demand.
- Improve order management by consolidating data sources to assess inventory levels, predict demand & identify fulfillment issues.
- Streamline procurement by organizing & analyzing cash flow across departments to improve negotiations & identify opportunities for discounts or alternative sources.
- Increase working capital by refining models to determine inventory levels needed to ensure service goals with minimum means.
Learn and Grow with Imarticus Learning:
If you are looking for a career that has both excellent prospects and flexibility, then, IIT Supply chain Management course offered by Imarticus Learning is perfect for you.
Supply Chain Analytics enables management to make data-driven decisions at strategic, operational, and tactical levels. With this course, you can explore employment opportunities in job roles like Demand Planner, Data Scientist, Supply Planner, and Supply and Operations Planner. Master your SCM skills with analytics through this cutting-edge curriculum that helps you get more data-centric & improve the decision-making of a Supply Chain by leveraging the power of Python.