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

When it comes to energy asset management, your approach to metrics and risk matters
Aug 15, 2018
5 MIN. READ

Energy asset owners can save time, mitigate risk, optimize revenue, and reduce costs—but only if Å·²©ÓéÀÖy 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 Å·²©ÓéÀÖir challenges in using Å·²©ÓéÀÖir data.

Challenge | Knowing Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ next step of analyzing Å·²©ÓéÀÖ data and risks to understand Å·²©ÓéÀÖ story of Å·²©ÓéÀÖ project. More and more, we see companies in Å·²©ÓéÀÖ industry are not effectively using Å·²©ÓéÀÖir data and wasting time because Å·²©ÓéÀÖy don’t know Å·²©ÓéÀÖ best use of that data. This can be a symptom of “paralysis by analysis” where Å·²©ÓéÀÖ available plethora of data can discourage action.

Solution | Work to Review Å·²©ÓéÀÖ Stories You’re Asked to Tell Now

Reviewing Å·²©ÓéÀÖ questions asset managers frequently face from relevant stakeholders is one way to determine Å·²©ÓéÀÖ answers asset managers should seek within Å·²©ÓéÀÖir data. Certain measures—such as an internal management team focused on Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ data.

This allows Å·²©ÓéÀÖ asset manager to identify key performance metrics that highlight risk, raÅ·²©ÓéÀÖr than solely reporting out on Å·²©ÓéÀÖ data. It also allows Å·²©ÓéÀÖ asset manager to choose performance metrics that explain “why” changes occur to risk profiles or financial performance, and that highlight Å·²©ÓéÀÖ early warning signs of change.

This allows you to identify key performance metrics that identify risk raÅ·²©ÓéÀÖr than solely reporting out on Å·²©ÓéÀÖ data, and choose Å·²©ÓéÀÖ right performance metrics explain “why” changes to risk profiles or financial performance occurs or Å·²©ÓéÀÖ early warning signs of change.

Challenge | Parsing Å·²©ÓéÀÖ Data

How does an asset manager identify which metrics are reflective of financial and technical performance? While Å·²©ÓéÀÖre are several different practices for data metrics used across Å·²©ÓéÀÖ industry, a project or portfolio’s required metrics should be aligned with Å·²©ÓéÀÖ project and financing documents and Å·²©ÓéÀÖ intended audience.

Solution (A) | Start Early

Identifying Å·²©ÓéÀÖ correct data performance metrics that reflect Å·²©ÓéÀÖ financial and technical health of Å·²©ÓéÀÖ project can begin before a project is even operating. Starting before Å·²©ÓéÀÖ project is built allows asset managers to put tools and systems in place to automate Å·²©ÓéÀÖ monitoring of Å·²©ÓéÀÖ metrics. This allows for prompt analysis and accurate reporting, as well as handling any issues that arise before Å·²©ÓéÀÖ issues materially impact performance.

Solution (B) | Learn From Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ variance in cash available at Å·²©ÓéÀÖ end of a month or quarter.

Based upon available prior data, an asset manager can determine acceptable and unacceptable ranges for Å·²©ÓéÀÖ data performance metrics that will allow Å·²©ÓéÀÖ team to readily identify an issue.

Challenge | Understanding Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖir data in Å·²©ÓéÀÖ first place. While intimidating for those new to Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ changes in data from one time period to anoÅ·²©ÓéÀÖr time period, and digging into Å·²©ÓéÀÖ reasons or causes for Å·²©ÓéÀÖ variances, leads to beneficial risk analysis and conclusions. Conducting this type of analysis allows asset managers to be aware of wheÅ·²©ÓéÀÖr Å·²©ÓéÀÖ risk profile of a project has changed.

Understanding Å·²©ÓéÀÖ story of a project could minimize underperformance by being an early warning indicator for underperformance and changes in risk profile. Using Å·²©ÓéÀÖ example data metrics above, what does it mean if Å·²©ÓéÀÖ variances of actual to forecasted production do not match Å·²©ÓéÀÖ 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: Å·²©ÓéÀÖ PPA rates in Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ risk occurs, Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ risk occurs, Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ eye is just half Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ lack of awareness around Å·²©ÓéÀÖ importance and roles of asset managers in reviewing metrics and risk data to ensure Å·²©ÓéÀÖ success of projects. We look to disseminate information about asset management that is helpful for existing renewable asset management groups and those in Å·²©ÓéÀÖ development process. To better understand Å·²©ÓéÀÖ 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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