POSTED BY Scott Creed | POSTED IN Analytics, Blog, E/CTRM

Second Question Answered By CTRM Analytics: When and Where Do I Need to Move Product?

In our last article, we discussed question 1 what commodity-trading-and-risk-management (CTRM) analytics answer.

Question 2: When and where do I need to move product?

CTRM systems essentially manage trading contracts and the associated data. You agree to buy or sell a product at a particular price, from a specified location, and in a certain timeframe. The challenge is that trading data on its own doesn’t give much guidance to schedulers as they make decisions about the logistics of moving product.

Currently, the approach that many schedulers take is to figure out the details associated with managing a schedule outside their organization’s CTRM system. They use many separate systems, including pipeline-operations and rail-monitoring systems, and Excel. They also rely on their own knowledge of their network to come up with best estimates and forecasts. In small networks, this approach can work. However, in bigger, more complex networks, this approach can be extremely difficult.

Without analytics, schedulers are less likely to be able to effectively perform a variety of critical tasks:

  • Projecting and targeting inventory levels at each location
  • Incorporating supply and demand forecasts
  • Determining fleet availability
  • Gaining visibility into transit times and pump dates on pipeline systems
  • Understanding the impact of interruptions, such as outages and weather events (CTRM systems don’t even tell you that an interruption has occurred, much less inform you about the impact)
  • Modeling and comparing various scenarios
  • Analyzing past data to uncover trends


CTRM analytics bring together all trading data, supply and demand forecasts, and scenario data for a given period into one place: a centralized dashboard with a visualization tool. From here, schedulers can transform data into meaningful information and perform all of the above tasks. In short, analytics makes their job much easier.

For example, analytics lets schedulers build and model scenarios, create more concrete plans, and use their CTRM system to schedule activity according to their chosen scenario. These models factor in constraints on transportation assets and inventories, as well as network interruptions, so you can visualize the impact of these scenarios and make decisions grounded in reality. Additionally, analytics help schedulers target inventory levels based on supply and demand forecasts so that they know where to schedule product now and in the future. Furthermore, if flexibility exists regarding transportation assets, analytics can help schedulers determine which is the most cost-effective and efficient use of an organization’s transportation options.

Stay tuned for question 3: how is my portfolio exposed to shifting market prices?

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