02 Sep 2022

An Overview of Descriptive Analytics & Models in Supply Chain

Descriptive Analytics is a powerful approach that is used to improve decision-making. It uses tools and techniques to identify patterns, trends, and relationships in data. The information can then be used to make predictions and identify inefficiencies to improve in an organization.

An Overview of Descriptive Analytics & Models in Supply Chain

What is Descriptive Analytics?

Descriptive analytics is the process of turning raw data into readable and accessible insights. It helps organizations make better decisions by providing a clear picture of what has happened in the past. This type of analytics goes beyond simple data visualization. It uses tools and techniques to identify patterns, trends, and relationships in data. This information can then be used to make predictions about what will happen in the future.

This process is also known as statistical analysis or data mining.

What Are the Benefits of Using Descriptive Analytics in Supply Chain?

There are many benefits of this technique in the supply chain. By understanding what has happened in the past, organizations can make better decisions about the future.

Some of the specific benefits include:

  • Improved decision-making: It provides insights that can be used to improve decision-making at all levels of the organization.
  • Enhanced customer service: By understanding customer behaviour, organizations can provide a better level of service.
  • Increased efficiency: It can help organizations identify inefficiencies and areas for improvement. 
  • Reduced costs: Identifying trends and patterns can help organizations save money on inventory, transportation, and other costs.

These benefits provide a good idea about the importance of descriptive analytics in the supply chain. By understanding past trends, organizations can make better decisions that lead to improved efficiency and reduced costs.

 

Descriptive Analytics Tools and Techniques

There are many different tools and techniques that can be used to get the analytics done. The specific tools and techniques that are used will depend on the type of data being analyzed and the goals of the organization.

Some common tools and techniques include:

  • Data visualization: This is a way of representing data in a graphical format. It can be used to identify patterns and trends. Our eminent software provides all the advanced data metrics on a single platform which helps organizations to make better decisions.
  • Scenario Modelling: This is a technique that can be used to simulate different future outcomes. It can be used to test different what-if scenarios. Our Scenario Models predicts all kinds of future outcomes and provides decision support.
  • Business Intelligence: This is a set of techniques that are used to collect, store, and analyze data. It can be used to generate reports and dashboards. Our Business Intelligence solutions provides all in one platform where all the major stakeholders can create custom reports and dashboards as per the organization's requirements. It also monitors and analyzes the changes in data over time.

There are some descriptive analytics software too like Looker, Tableau, Microsoft Power BI, Google Data Studio etc., which can be used for analyzing data.

Descriptive Analytics Models

There are many different types of analytics models. The specific model that is used will depend on the type of data being analyzed and the goals of the organization.

Some common models include:

  • Regression analysis: This is a way of determining the relationship between two or more variables.
  • Classification analysis: This is a way of dividing data into groups. It is generally used to identify trends and patterns.
  • Clustering: This is a way of dividing data into groups. It can be used to find relationships and correlations.

Organizations should use the right combination of tools and techniques to meet their specific needs.

What Are the Applications of Descriptive Analytics?

There are many different applications for statistical analytics. Some common applications include:

  • Sales analysis: This is a way of understanding past sales data. It is generally used to predict future sales near-accurately.
  • Customer analysis: This is a way of understanding customer behaviour. It is generally used to improve customer service. 
  • Inventory analysis: This is a way of understanding inventory data. It is genrally to improve inventory management. 
  • Descriptive analysis: This is a way of understanding data. It is generally to improve decision-making.

Frequently Asked Questions

What is an example of descriptive analytics?

One example of this technique is data visualization. This is a way of representing data in a graphical format.

How does it work?

It uses tools and techniques to identify patterns, trends, and relationships in data. This information can then be used to make predictions about what will happen in the future.

When to use statistical analytics?

Statistical analytics can be used any time you need to understand what has happened in the past. It is a powerful tool that can be used to improve decision-making, but it is only one piece of the puzzle. Organizations should also use predictive and prescriptive analytics to get a complete picture of their data.

How can it help a business to grow?

This process can help organizations identify inefficiencies and areas for improvement by understanding customer behaviour, organizations can provide a better level of service.

Optimize Your Supply Chain Today with Descriptive Analytics

Use 3SC’s Descriptive Analytics to grow your business today. For more information, call on 0124-4616597 or email us at marketing@3scsolution.com. Alternatively, you can also fill the given form and send your query directly to us via the website.


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