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January 1, 2010

Addressing the Intraday Trading Position Conundrum

By Edward Cuoco and Victor Milligan

Casting Light on Suitable Solutions

In order to leverage the full range of available supply and demand data on an intraday basis, trading organizations must look outside of typical CTRM or business intelligence tools. As an example, industries such as telecommunications and manufacturing make good use of process-driven analytic tools in order to address analogous issues in their spaces.  These process-driven tools have many of the key elements needed to ensure that detailed data is quickly and granularly analyzed.  Specifically, they are data-architecture-independent, they allow business users to create and change analytics quickly and without a major IT engagement, and they allow both logic and data to be modeled in the same tool.

Equally important is that process-driven solutions support an analytic methodology where discovery and analysis happen simultaneously—occurring when business users create analytic tools collaboratively even as they investigate the data itself. This combination of technology and methodology enables energy companies to enhance their risk reporting and fulfill their core need for integrating supply and demand data intraday.  When looking to acquire this type of technology, organizations should consider the following critical criteria and select a solution that:

• Enables the organization to access and apply data quickly, including acquiring and analyzing data in near-real-time.
• Allows the organization to maintain sufficient data granularity in order to improve position reporting at quarter-hour increments.
• Is able to analyze supply/demand data in the context of trading and contract logic.
• Supports an agile analytic methodology, allowing business teams to adapt and tweak analytics and explore new data sources quickly and easily.
• Creates output that can be audited and tracked—providing confidence in output and reducing the likelihood of needing revisions.
• Delivers value within three to six months and can consistently adapt itself to new data inputs and analytics within days or weeks.

By leveraging this class of tool, it is possible to create a solution that is managed and maintained within the process analytics team or perhaps in the mid-office. This eliminates the risk and expense of a large-scale IT implementation but does so without sacrificing the ability to convert these analytics into standing operational controls and while maintaining transparency and audit capabilities.