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Data Analysis of Ecommerce

  • Correlation is not causation*

“AI is just statistics on Steroids!”

Was a statement that echoed in a conference I attended 4 years ago.

That statement has been echoing in my head ever since.

It keeps popping up because I see a lot of confusion when it comes to using statistical analysis in supply chain.

Let us say you are trying to predict estimated delivery time of your ecommerce products.

You do an exploratory data analysis and you come up with the table attached.

There seems to be a correlation between Discount Offered and Reach on Time variables.

But Correlation is not Causation.

  • Goods offered on discount reach on time because they have high demand.
  • Reached on time is motivating Marketing to discount further and sell units.
  • There is a pandemic, and the loss leading product is in high demand.
  • The correlation can be an act of randomness.

My point is that ambiguity is the nature of data.

Data simply spells out the “What”.

It is us as leaders to give it context and find out the “Why?”

Only then can we have a truly transformation digital experience in supply chain.

Code

This repository code you will find all the code used to explain the concepts presented in the article.

About me

Supply Chain Professional with international experience and a passion for data science. Connect with me on LinkedIn: Profile

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