To operate effectively from short-term market execution to long-term resource and transmission planning, you need data—and plenty of it. But not just any data will do when high-impact decisions rely on accurate, complete and timely information.
You have varied options for organizations providing load forecasting, real-time market movement and historic pricing data, but how can you evaluate all of them and find the best fit for your organization?
Start by asking these nine questions.
Data completeness
Many analytical models are sensitive to missing inputs. Data gaps can distort aggregations, skew analyses and lead to flawed conclusions. Missing values from one data stream could lower the correlation coefficients between other data streams when comparing data, making a variable seem less important to the final result than intended. In data-driven power markets, ensuring completeness is essential to preserving analytical accuracy and decision integrity.
To start evaluating data completeness, ask:
- How far back do you have power market data for each ISO?
- What do you do when an ISO revises an LMP or other data point after initial publication?
- What happens if an ISO energizes or de-energizes a node?
Data freshness
Understanding the impact of data latency on decision-making is essential for those who depend on timely information to maintain reliability. Even small delays or gaps in data can introduce significant risk. In fast-moving power markets, access to accurate and real-time information isn’t optional—it’s fundamental to risk management and optimizing market performance.
To explore data freshness, ask:
- How frequently do you update your data feeds, and what is the typical latency between data being reported and its availability to your customers?
- Can you provide specific examples of your data refresh rates for critical market data such as locational marginal prices (LMPs), supply and demand figures and weather-related data?
Data lineage
Utilities depend on large volumes of data to inform critical decisions. Confidence in those decisions requires a clear understanding of where the data originates, how it’s changed and when updates occurred. Even minor misalignments in time-series data or small information gaps can cause significant financial and operational consequences. Transparent data lineage (or knowing where data comes from and how it’s changed) is essential to maintaining trust in the information driving your decisions.
To begin assessing data lineage, ask:
- Do you clean or standardize the raw data, and if so, what type of cleaning do you do?
- What visibility and observability do you have in your system for customers to track all data revisions and changes and calculated data?
- What type of internal monitoring do you have to track the state of the data in your system?
- How much enriched or calculated data do you have in your system, and how do you enrich it?
What’s next?
Want to see our complete list of questions to ask a potential power market data provider—plus what to look for in the answers? Get the full checklist and guide.
