The Supply Chain Insights Platform: Synthesizing
Author : danika-pritchard | Published Date : 2025-05-28
Description: The Supply Chain Insights Platform Synthesizing economic data for supply chain analysis Krista Chan Kevin Li Christian Moscardi US Census Bureau FedCASIC April 17 2024 Note Any opinions and conclusions expressed herein are those of
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Transcript:The Supply Chain Insights Platform: Synthesizing:
The Supply Chain Insights Platform: Synthesizing economic data for supply chain analysis Krista Chan, Kevin Li, Christian Moscardi U.S. Census Bureau FedCASIC April 17, 2024 Note: Any opinions and conclusions expressed herein are those of the author and do not reflect the views of the U.S. Census Bureau. Goals for this talk Motivate development of supply chain tool Share tool Share challenges associated with supply chain data analysis Gather feedback and discuss with others experiencing similar challenges 2 Supply chain interest Supply chain crises Demand from data users Ongoing work @ DOC (ITA Supply Chain Center) "Tell us everything Census knows about" Baby Formula The automotive supply chain The pharmaceutical supply chain Etc. 3 Data sources 4 Economic Census Annual Survey of Manufacturers (ASM) Annual Wholesale Trade Survey (AWTS) Annual Retail Trade Survey (ARTS) Services Annual Survey (SAS) Quarterly Survey of Plant Capacity Utilization (QPC) Commodity Flow Survey (CFS) County Business Patterns+ ZIP Business Patterns (CBP/ZBP) Foreign trade import/export data Profile of importing/exporting firms Manufacturing and International Trade Report (MITR) Business Dynamics Statistics (BDS) Business Trends and Outlook Survey (BTOS) Longitudinal Employer Household Dynamics (LEHD) / LEHD Origin-Destination Employment Statistics (LODES) Economic Indicators Community Resilience Estimates (CRE) Challenge Given the needs of data users and a wide variety of data sources, how might we present a holistic view of a product's supply chain? 5 Desired functionality Searchable in natural language Visual, with a useful and informative visualization layer displaying key information Brings together disparate data sources and harmonizes datasets with different coding schemes, reference years, numeric values, etc. 6 7 8 Model turns free text into a product code in the Harmonized System (HS) Logistic regression classifier trained on customs declarations Accuracy 72% on curated test set of common queries 9 10 11 12 Data Harmonization 13 Data use a variety of coding schemes to identify products and industries Standard Classification of Transported Goods (SCTG) North American Product Classification System (NAPCS) Harmonized System (HS) codes North American Industry Classification System (NAICS) Custom BEA Detailed Industry Codes Coding schemes change on a regular basis Census data availability is redacted in more granular subsets of industry, product, and geography Data Harmonization 14 Building a back-end of data relationships for every product type, industry type, geography, and year of data, including many analyst-created concordance files This allows easy traversal across datasets and queries such as: What are the material inputs (Econ Census) of
