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What is the supply chain, and what is supply chain analytics ?

Supply chain analytics is the analysis of information that companies derive from a number of supply chain-related applications, including supply chain execution systems for inventory procurement, inventory control, order processing, storage management and execution, and freight management.
Each step in the network of the supply chain affects the one after it, and ultimately, any problem at any step can impact the company's capacity to meet its commitments to customers.

Supply chains  management include many different operations, workers, and organizations, which generates an overwhelming amount of information. That's where supply chain analytics come into play: by turning this massive amount of data into understandable dashboards, reports and visualizations that drive key decisions and lead to better outcomes. Easy access to these analytics has become crucial in an increasingly competitive environment.

What are the 4 types of supply chain Analytics?

Descriptive Analysis

Descriptive analytics examine what has happened in history to identify patterns in data. These insights can come from internal supply chain execution software as well as from external systems that provide visibility into suppliers, distributors, different sales channels and customers.

Data driven Analytics can compare the same type of data in real time over different time frames to pinpoint patterns and generate hypotheses about the potential causes of changes.

An electronical device company can look at a descriptive analytics dashboard on a daily basis and discover that half of its deliveries to distributors are late. The company's executives can then dig deeper into this problem and learn that trucks have slowed down due to a torrential rain in the district around this group of distributors.

Predictive analytics

As the name suggests, predictive analytics takes the guesswork out of predicting what might happen and the business impact of various scenarios, from potential supply chain disturbances to other outputs. By forcing executives to consider these possible scenarios before they happen, they are enabled to act proactively rather than reactively. It gives them time to develop a strategy for dealing with an expected increase or decrease in demand, for example, and they can respond correspondingly.

Considering the same electronical device company, it may examine the latest economic projections from the Federal Reserve and anticipate a 10 to 20 percent decline in sales in the next quarter. In light of this, he orders fewer raw materials from his providers and lowers the working hours of part-time staff for the following 30 days. It could therefore be a real competitive advantage if competitors do not have the same metrics and perspectives.

Prescriptive Analysis

Prescriptive analysis combines the results of descriptive and predictive analysis to recommend actions a company should take now to accomplish its goals. Such analysis could help companies fix challenges and avoid major supply chain disruptions, potentially by evaluating both its own information and its partners' information. Since prescriptive analytics are more complex, they require more powerful software that can quickly process and interpret massive amounts of data.

Prescriptive analytics can tell our electronical device company that one of its key suppliers in Western Europe is likely to go out of business in the next year. A consistent history of back orders, reduced capacity, and declining economic conditions in the region are all indicators of this risk.

In response, the manager could request a meeting with the supplier's management to determine if they are in financial trouble and how it could help. If no clear solution is found, the company can begin to look for other suppliers to replace this one before it's too late.

Cognitive Analytics

Cognitive analytics attempt to replicate human thinking and behavior to help companies answer difficult and complex questions. These analytics are able to understand real precise information like context when interpreting results. To do so, cognitive analytics relies on artificial intelligence (AI), including machine learning and deep learning, which allows it to become more intelligent over time. This can significantly reduce the volume of work needed, of people to produce that reporting and analysis, and can grant a great degree of autonomy to people beyond the data science squad to draw out the results and figure them out.

With its Artificial Intelligence-powered software, our electronics company could be able to further automate a significant amount of demand planning work. The system could process all existing data, as well as both internal and external factors, to make very accurate and detailed suggestions on how much of each product it should manufacture for the upcoming period to meet demand. This would cut down on the extra expense of building up more stock than needed or lost revenue due to the inability to satisfy demand.

Key difference between Supply Chain Analytics and Business Analytics

Business analysis centers on providing new perspectives and insights into business behavior based on large amounts of data and statistical analysis methods.
On the other hand, Supply chain Analytics is traditionally focused on using a consistent set of metrics to measure historical performance and drive business planning, which is similarly driven by data and statistical methods.

The fact is that an impressive number of companies currently have not embraced Big Data yet. "Big Data" skills are more in demand as companies begin to ask how they can be more successful in a super competitive environment.

Why is Supply chain Analytic so important ?

Well, simply cause it will push organizations forward thanks to a faster, more precise and more informed decision making process. That’s why Supply chain analytics are a key part of the business model.

Identiying potential risks, improve planning, reduce costs, waste of time, drive inventory, meet customer’s growing expectations etc. Each part of the process can be improved with reports and dashboards from Supply Chain Analytics.

We hope that our description will meet your expectations and facilitate your choice. We would be pleased to welcome you to our Business Analysis program.
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