The Difference Between Predictive Insights and Prescriptive Recommendations in the Digital Supply Chain

The Difference Between Predictive Insights and Prescriptive Recommendations in the Digital Supply Chain

[vc_row][vc_column width=”2/3″][vc_custom_heading text=”By analyzing the behavior of carriers, ports, lanes, manufacturing facilities, warehouses, etc. over time, and under varying conditions, machine learning algorithms can establish patterns of behavior that are valuable inputs to predictive analytics.” font_container=”tag:h3|text_align:left” use_theme_fonts=”yes”][vc_column_text]In addition to learned behavior models, other inputs that feed predictive analytics engines are real-time data about the live and predicted movement of conveyances, inventory, and the external events that surround them (i.e., severe weather, natural disasters, wave heights, road traffic, port congestion, temperatures, labor strikes, etc.).

Processing all these data elements within an AI-based framework, capable of analyzing massive amounts of data very quickly, can yield impressive predictions. We call them predictive insights.[/vc_column_text][vc_row_inner][vc_column_inner width=”1/3″][vc_single_image image=”2079″ img_size=”full”][/vc_column_inner][vc_column_inner width=”2/3″][vc_custom_heading text=”Download this education series now to understand the difference between predictive insights and prescriptive recommendations” font_container=”tag:h3|text_align:left” use_theme_fonts=”yes”][vc_column_text]

  • What are predictive insights and relevant examples?

  • What are prescriptive recommendations and relevant examples?

  • How does a digital supply chain solution produce prescriptive recommendations and how are these recommendations operationalized across a business?

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