Launching TRD - Measuring Supply Chain Risk Daily
- BCMstrategy, Inc.
- 6 days ago
- 4 min read
Delighted to announce that a new thematic vertical for PolicyScope data -- TRD (trade policy data) -- is now live on Initial Data Offering! Strategists and portfolio managers (and their automated AI assistants) now can access easily a twice-daily data feed for managing and measuring supply chain risk.
About Initial Data Offering (IDO)
It is no secret that the AI revolution cannot exist without data. Our friends and colleagues at Initial Data Offering (IDO) understand this well. The team there is "committed to curating and showcasing the most interesting datasets."
We are honored and delighted that the IDO team included TRD data this week....and that they included our energy and climate data (CRRM3) last year.
Why Measuring Supply Chain Risk is No Longer Optional
Liberation Day Tariffs. Venezuela. Iran. Critical Minerals. Electric Vehicles. LNG. Wind Turbines. Solar Panels. Retaliatory Tariffs. IEEPA. Section 122. Section 301. Section 232. USMCA renegotiation. The world has changed in the last year. Going back to "normal" is no longer an option.
We are all living through the tail of the distribution, where historical correlations and underlying assumptions about policymaking do not help identify potential future policy decisions. We are also living in a highly noisy news cycle which can make it difficult to spot strategically significant but highly technical shifts in policy when they occur.
AI amplifies these informational blind spots because world-class pattern-matching mechanisms face significant limitations. Training your generative AI on decades of trade policy documents cannot prepare your machine for out-of-the-box thinking at the highest levels of policymaking. Training your quantitative AI on news-based sentiment data skews your trend projections because the center of gravity quantitatively lands on opinion rather than cold, hard facts. For more details on the data challenges, see our January 2026 blogpost: Addressing Structural Breaks in Global Macro Historical Time Series Data
Forming a solid view to support strategic decisions -- with or without AI's assistance -- requires serious professionals to up their game. But the pace of the policy and news cycles regarding trade policy collides with bandwidth limitations. Chasing new developments crowds out higher-value activities like analysis and strategy. You need better inputs that match the speed and precision with which you operate. TRD Data can help.
TRD Data To The Rescue
Twice a day, the award-winning, patented PolicyScope process scans the globe for new trade policy developments at the source. The system automatically reads, measures, labels, sorts, and stores in minutes more trade policy content than a human could read in a week.
Coverage details appear on the right.
The real game-changer, however, is in in the delivery mechanism.
Wherever you are in your AI journey, TRD data is there to help you extract the most value from the data.
Quantitative Data and Use Cases
Tickerized quantitative data in .csv format is available to enterprise portfolio managers through secure sandbox environments on Databricks and Snowflake as well as through direct access to dedicated S3 buckets. Your teams can now evaluate public policy shifts using the quantitative values generated by the patented PolicyScope process.
The quantitative data opens up new avenues for quantitative analysis based on volume, velocity, and volatility as well as MACD, anomaly detection, and other technical analysis. For more details, see our July 2025 blogpost: How to Spot Tariff Policy Trends.
Tickerizing the data enables portfolio managers to articulate trade-related time series in relation to any tradeable asset. We started with the Russell 3000, but so many more options exist.
Combining TRD data with other datasets (e.g., shipping volumes, port volumes, tariff schedules) and the news cycle (yes, we can score this also using our patented process) delivers additional insight into the shape and structure of supply chain risk.
No two TRD users will likely use the exact same combination of datapoints to support their portfolio decisions.
Language Data and Generative AI Use Cases
TRD PolicyScope Data can also be delivered as fully structured .json files to support automated research assistants deployed by large enterprises. This is what it means to be an AI-native data company. We set out to generate quantitative data, but we always knew that compliance and audit trail requirements at large financial institutions would require that the data be stored in Golden Source format (not changing a word) with a time stamp. Like all other PolicyScope data feeds, TRD includes these components at no additional fee.
Here is the best part: the .json files include the quantitative data tags. Your automated research assistant can therefore generate not just first drafts for internal memos and research notes....it can also generate charts and graphs from PolicyScope data. Again, .json files can be retrieved twice a day from dedicated S3, Databricks, or Snowflake portals.
For more details, see our February 2025 blogpost:
Language training data is currently only available to enterprise customers with their own internal generative AI deployments.
BCMstrategy, Inc. uses award-winning patented technology to generate data from the public policy process for use in a broad range of AI-powered processes from predictive analytics to automated research assistants. The company automatically generates multivariate, tickerized time series data (notional volumes) and related signals from the language of public policy. The company also automatically labels and saves official sector language for use in generative AI, deploying expert-crafted ontologies. Current datafeeds cover the following thematical verticals
