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Supply Chain Analytics in Tableau or Power BI

📖 Background

As the main data analyst for Just In Time, I will help solve key shipment and inventory management challenges, analyze supply chain inefficiencies, and create insightful dashboards to inform business stakeholders about potential problems and propose structural business improvements.

import pandas as pd
data = pd.read_csv("data/orders_and_shipments.csv")
data

🧾 Executive summary

In a couple of lines, write your main findings here.

  • 2016 was the year with the highest number of orders but had about the same profit generated as in the year 2015.
  • USA, France and Mexico had the highest delayed orders with France being the top in 2015, USA being top in 2016 and Mexico being top in 2017.
  • Central America and Western Europe were the regions with the largest delayed orders.
  • Most orders using the first-class shipment mode were delayed. From 2015 to 2017, it was the shipment mode with the highest delayed orders followed by the standard class shipment mode.
  • Average gross sales across product department increased with decreasing number of days to refill stock. Technology department had the largest gross sales with an average of four days. Also health and beauty department had an average of two days to restock.
  • There seemed to be a weak positive correlation between the warehouse inventory and inventory cost per unit. As the cost per unit increased, the level of inventory increased

📷 Dashboard screenshot

🌐 Upload your dashboard

For Tableau: paste the link to your Tableau Public dashboard here.

For Power BI: upload your .pbix file to Files in the sidebar on the [left.] (Invalid URL)

⌛️ Time is ticking. Good luck!