Supply chain analytics course: Reimagine organizational operations by fusing design thinking with cutting-edge technologies
Supply chain analytics is vital for corporate success because it directly influences a company’s capacity to provide a pleasant customer experience while accounting for many expenses that impact overall profitability. The supply chain is a network that connects suppliers, businesses, and end-users, and it includes everything from acquiring raw materials to delivering products to customers.
Companies can collect, analyze, and act on data created by their supply chains using supply chain analytics. It enables them to make immediate adjustments and long-term strategic improvements to provide a competitive edge.
Hence, what is the need to become a supply chain analyst? Supply chain analytics is becoming increasingly important in the day-to-day operations of today’s most successful firms. Organizations are paying more attention to these figures than ever before, and they’re utilizing a variety of analytics approaches to improve each connection in the network. We at Imarticus help you learn about the supply chain with our SCM program.
Types of Supply Chain Analyst
Mainly there are four types of supply chain analytics, and we at Imarticus, through the SCM program, brief about them:
Descriptive Analytics
Descriptive analytics examines the past and recognizes trends in historical data. This data could come from internal and external systems that provide visibility across suppliers, distributors, sales channels, and customers. Analytics can uncover patterns and postulate potential reasons for change by comparing the same type of data from different times.
Predictive Analytics
Predictive analytics assists businesses in predicting what might happen and the business impact of various situations, such as supply chain interruptions and other outcomes. Leaders can be proactive rather than reactive by forcing them to evaluate these prospective circumstances before they arise. They have enough time to plan a strategy for a potential surge or drop in demand, for example, and can react appropriately.
Prescriptive Analytics
Prescriptive analytics combines descriptive and predictive analytics data to propose what actions a company should take right now to achieve its objectives. This type of analytics could aid businesses in resolving issues and avoiding significant supply chain interruptions by assessing internal and external data. Because prescriptive analytics is more complicated, powerful software can quickly handle and analyze large amounts of data.
Cognitive Analytics
Cognitive analytics aspires to mimic human thinking and behaviour, and they can assist businesses in answering challenging, complex problems. Though, when it comes to evaluating data, these analytics can recognize things like context. Cognitive analytics utilizes artificial intelligence (AI), notably machine learning and deep learning to accomplish this.
