4 Smart Visualizations for Supply Chain Descriptive Analytics
<p>Supply chain Analytics can be defined as a set of tools and techniques your organization should use to get supply-chain operational insights from data.</p>
<p>In a <a href="https://www.samirsaci.com/what-is-supply-chain-analytics-2/" rel="noopener ugc nofollow" target="_blank">previous article</a>, I defined the four types of Supply Chain Analytics that answer different operational questions.</p>
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<p><a href="https://youtu.be/3d7C4pShykI"><img alt="" src="https://miro.medium.com/v2/resize:fit:700/1*sCYOiuhTEBuf__yueX4IrA.png" style="height:221px; width:700px" /></a></p>
<p>4 Questions of Supply Chain Analytics — (Image by Author)</p>
<p>It starts by building the foundation of <strong>Descriptive Analytics</strong> to monitor the present and analyze the past.</p>
<p>In this article, I will share <strong>four Python smart visualizations for descriptive analytics that provide key insights to understanding your supply chain.</strong></p>
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