When it comes to energy asset management, your approach to metrics and risk matters

Aug 15, 2018

Energy asset owners can save time, mitigate risk, optimize revenue, and reduce costs—but only if they surmount common challenges posed by a wealth of data.

Data from a project can be a treasure trove for asset owners. The expansive data set of metrics collected on renewable projects and portfolios can be used to not only save time, but to mitigate risk, optimize revenue, and reduce costs. We want to help companies overcome their challenges in using their data.

Challenge | Knowing the Stories You Need to Tell

Metrics and risk factors combined tell a story of a project. Most asset owners and stakeholders already collect financial and technical performance data, but fail to take the next step of analyzing the data and risks to understand the story of the project. More and more, we see companies in the industry are not effectively using their data and wasting time because they don’t know the best use of that data. This can be a symptom of “paralysis by analysis” where the available plethora of data can discourage action.

Solution | Work to Review the Stories You’re Asked to Tell Now

Reviewing the questions asset managers frequently face from relevant stakeholders is one way to determine the answers asset managers should seek within their data. Certain measures—such as an internal management team focused on the performance of new assets or external investors asking about specific financial performance stats—can consistently provide clues to where an asset manager should “dig in” and set up routine monitoring systems to develop stories explained by the data.

This allows the asset manager to identify key performance metrics that highlight risk, rather than solely reporting out on the data. It also allows the asset manager to choose performance metrics that explain “why” changes occur to risk profiles or financial performance, and that highlight the early warning signs of change.

This allows you to identify key performance metrics that identify risk rather than solely reporting out on the data, and choose the right performance metrics explain “why” changes to risk profiles or financial performance occurs or the early warning signs of change.

Challenge | Parsing the Data

How does an asset manager identify which metrics are reflective of financial and technical performance? While there are several different practices for data metrics used across the industry, a project or portfolio’s required metrics should be aligned with the project and financing documents and the intended audience.

Solution (A) | Start Early

Identifying the correct data performance metrics that reflect the financial and technical health of the project can begin before a project is even operating. Starting before the project is built allows asset managers to put tools and systems in place to automate the monitoring of the metrics. This allows for prompt analysis and accurate reporting, as well as handling any issues that arise before the issues materially impact performance.

Solution (B) | Learn From the Past

If you’re playing catch up and applying data analysis to existing projects, a review of previous or current metrics with an experienced professional can guide you to understanding future warning signs or problems. Some examples:

  • A spot check of metered production data and PPA rates compared against revenue figures, and comparing this to the financial model forecasts.
  • Review availability, actual versus forecast production plus a review of variances with actual versus forecast revenue.
  • A more cash flow focused metric is a review of variances in operating expenses and the variance in cash available at the end of a month or quarter.

Based upon available prior data, an asset manager can determine acceptable and unacceptable ranges for the data performance metrics that will allow the team to readily identify an issue.

Challenge | Understanding the Story Told

For teams not regularly analyzing data right now, or for those who have been working on it for years, putting it into a real-world context can be hard. This challenge may prevent many asset managers from looking in-depth at their data in the first place. While intimidating for those new to the process, or for those who lack time to focus on data, regularly taking a straight forward and fresh approach to data analysis is an important step.

Solution | Set the Bar for Success

On a monthly or quarterly basis, we recommend reviewing data and variances, and comparing to a baseline from closing or from previous calendar years. Being curious about the changes in data from one time period to another time period, and digging into the reasons or causes for the variances, leads to beneficial risk analysis and conclusions. Conducting this type of analysis allows asset managers to be aware of whether the risk profile of a project has changed.

Understanding the story of a project could minimize underperformance by being an early warning indicator for underperformance and changes in risk profile. Using the example data metrics above, what does it mean if the variances of actual to forecasted production do not match the actual to forecasted revenue variances? (Hint: maybe a blended revenue rate is being used.) What could be happening if actual revenue is consistently below forecast revenue but actual production is on target with forecast production? (Hint: the PPA rates in the forecast may be incorrect.)

Write Your Own Story

If potential issues are identified proactively through data analysis and a strategy is in place before a risk occurs, when or if the risk occurs, the decision-making time, outage time and adverse cash flow impact are reduced because a strategy has been proactively established through data and risk analysis.

If potential issues are identified proactively through data analysis and a strategy is in place before a risk occurs, when or if the risk occurs, the decision-making time, outage time and adverse cash flow impact are reduced because a strategy has been proactively established through data and risk analysis.

Understanding that your data has more to provide than initially meets the eye is just half the battle. To dive deep into data, and use it to write your own story of triumph, can be accomplished with experienced and successful advisors like ICF. We’d be interested to hear your own stories of dealing with data and how we may help.

ICF would like to change the lack of awareness around the importance and roles of asset managers in reviewing metrics and risk data to ensure the success of projects. We look to disseminate information about asset management that is helpful for existing renewable asset management groups and those in the development process. To better understand the role of asset managers, see our last post, "Minimizing Risk and Maximizing Return: A “Crystal Ball” Approach to Portfolio Asset Management."

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Meet the authors
  1. Katie Janik, Asset Management Advisor, Energy

    Katie is a financial strategy professional with substantial project finance experience, particularly in the renewable energy, oil, gas, and financial services sectors. View bio

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