4.17
(6 Ratings)

Data Analytics for Supply Chain (Intro)

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About Course

Why data analytics is important in Supply Chain?

Data is important to businesses in formulating strategies, streamlining operations, introducing new products and services, and ensuring customer satisfaction. But data alone isn’t much good unless it’s analyzed, understood and acted upon. Data analysis is benefiting from new technology tools by allowing analysts to dig more deeply into supply chains. At the same time, human judgment remains the most important element in analysis.

Data is defined as facts, figures or information that are stored in a variety of places such as invoices, contracts, and bills of lading. By collecting data, a business can improve shipment transparency and visibility, operational efficiency, and products and services. All of which attracts more users.

Transparency and visibility are crucial, particularly if something goes wrong while shipments are in transit. By utilizing data, a split-second decision doesn’t have to be made without adequate support.

Transparency and visibility are also important when reviewing invoices and contracts with supply-chain partners. Despite good intentions, hidden costs can occur. They usually come in the form of surcharges such as extra delivery-area fees, additional handling, and fuel. Often they make the difference in a retailer’s ability to offer “free” or one-day delivery.

Access to data derived from goods fulfillment is central to the achievement of both visibility and speed. In today’s retail environment, speed to market, accurate order fulfillment and efficient last-mile delivery are keys to success. In addition, data plays a major role in forecasting and optimizing inventory. Consumption rates and inventory levels are among the data points critical to proper inventory planning and development.

However, data is just data unless it’s analyzed and acted upon.

Business consulting firm McKinsey describes supply-chain analytics as the ability to use data and quantitative methods to improve decision making for all activities across the supply chain. While data analysis has been utilized for years, the introduction of new technologies such as artificial intelligence, machine learning and more have led to the ability to uncover additional data elements that were never used before, and are now contributing to forecasting in today’s supply chains. For example, traditional data monitoring, which would involve sales and order tracking along with point-of-sale data, is now being supplemented with weather, events and news.

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What Will You Learn?

  • Understand the benefits of data analytics
  • Have an over-view of possibilities, including a few case studies

Course Content

Session 1 Data science vs data analytics

  • Value of data
    15:34

Session 2 CRISP DM

Session 3 Visualization

Session 4 Data evalution

Session 5 Supply chain analytics – basics

Session 6 Excel wonder

Session 7 Case study overview 1

Session 8 Case study overview2

Session 9 Employers expectation

Student Ratings & Reviews

4.2
Total 6 Ratings
5
1 Rating
4
5 Ratings
3
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1
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DV
10 months ago
I liked this course because it is very useful in the supply chain, especially in supplier selection and segmentation.
SV
10 months ago
Great information, new tools to apply in my work.Simple understanding and direct to the point.
VS
10 months ago
Great Course. I learned a lot about Data Analytics for Supply chains.. It`s a good opportunity to gain basic knowledge of the supply chain. Great Course
KM
10 months ago
being a fresher, this program has helped me to train myself.
KS
10 months ago
Very Insightful ,worth to pay
PR
10 months ago
Great Course and too much recommended
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