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Why data-driven decision-making is critical for utility-scale solar investment
Pre-construction assumptions, static P50 estimates, and fragmented reporting processes are increasingly misaligned with operational reality. This disconnect creates friction with investors, erodes trust with boards, and makes it harder to allocate capital confidently. Industry-wide analyses have found that U.S. solar projects chronically underperform their initial P50 production forecasts by around 5–13% on average, indicating a clear gap between investor expectations and actual field performance.
This disconnect creates friction with investors and erodes trust with boards "If unaddressed, such systemic underperformance can have serious implications for equity cash flows, investor returns, and the long-term credibility of solar as an asset class." – Norton Rose Fulbright. It becomes much harder to allocate capital confidently when promised yields don’t materialize.
To succeed in today’s market, solar investors and owners need credible, data-backed insights that translate operational performance into financial outcomes consistently, transparently, and at scale.
Clir supports this shift through an AI-powered platform built around four core applications that reflect how leading owners and asset managers now manage solar portfolios across the operational lifecycle.
1. Investor-grade portfolio reporting: Turning performance into confidence
As solar portfolios grow, reporting becomes more complex and more scrutinized. Boards and investors need a clear, comparable view of performance across assets, not disconnected site-level reports or manually assembled spreadsheets.
In practice, however, many asset managers still resort to exporting data from different systems into large spreadsheets with multiple tabs when creating portfolio-level reports. This manual process is time-consuming and error-prone. Studies show that nearly 90% of sizable spreadsheets contain significant errors, which undermines confidence in the reported numbers.
Clir’s AI platform enables investor-grade portfolio reporting by standardizing operational data across solar assets and translating it into consistent, board-ready outputs. Asset managers can quickly see which sites are over- or underperforming, understand why, and communicate risks and opportunities with confidence.
Instead of spending hours reconciling inconsistent reports, stakeholders gain:
- A single, trusted view of portfolio performance
- Clear explanations of performance drivers and risks
- Comparable benchmarks across sites, technologies, and regions
This level of clarity reduces uncertainty in decision-making and improves confidence in both strategy and execution, directly supporting better capital allocation and governance.
2. Budget reconciliation: Restoring credibility to forecasts and valuations
One of the biggest pain points for solar investors is repeated budget misses driven by outdated yield assumptions. Pre-construction models were never designed to reflect years of operating history yet they often remain the basis for budgets, valuations, and refinancing discussions.
Clir’s AI-driven budget reconciliation tooling replaces static assumptions with data-backed, forward-looking forecasts grounded in real operating performance. By applying AI models to historical production, resource variability, downtime, curtailment, and availability, owners can continuously reforecast expected energy yield with greater accuracy.
This enables:
- More realistic budgets and cash flow projections
- Stronger, more defensible valuations
- Clear explanations for underperformance that stand up to investor scrutiny
Most importantly, it helps rebuild trust with boards and lenders by reducing surprises and aligning expectations with reality a critical advantage in refinancing and capital raise scenarios
3. Portfolio monitoring: Protecting value through proactive operations
Once assets are operational, value is won or lost in day-to-day performance. Yet many solar owners still rely on reactive workflows, OEM tools, or manual SCADA analysis that make it difficult to identify issues early.
Traditional O&M strategies of the past often reacted to obvious fault codes or outages after the fact, an approach that can miss subtle performance declines and lead to unnecessary delays or missed opportunities.
Clir’s AI-powered portfolio monitoring empowers asset managers and technical teams to actively monitor performance, detect anomalies, and diagnose underperformance using standardized, portfolio-wide data.
With built-in anomaly detection, benchmarking, and AI-based loss attribution, teams can:
- Catch underperformance early and reduce lost energy
- Shorten root-cause analysis from days to hours
- Prioritize maintenance and engineering effort where it has the biggest impact
By linking operational insights directly to financial outcomes, owners protect revenue, improve availability, and maintain credibility when performance is challenged by leadership, insurers, or investors
4. Contractual availability reconciliation: Defending revenue and reducing leakage
For many solar portfolios, contractual availability directly impacts revenue through bonus payments and liquidated damages payouts to service providers. Yet availability calculations are often opaque, manual, and controlled by service providers with conflicting incentives.
In a recent industry analysis, multiple independent engineers found that they all had to rely on monthly operating reports produced by the project operators – reports which were rarely independently verified and followed no single standard definition of availability across the industry.
In other words, availability figures are often a black box, and owners may suspect (sometimes rightly) that the reported 98% availability is overly generous to the operator’s performance.
Clir’s AI platform enables reliable contractual availability reconciliation, giving owners and asset managers the tools to independently validate OEM calculations using a standardized, auditable framework.
This allows teams to:
- Reconcile SCADA data, logs, and contract definitions consistently
- Identify mislabeled or missing events that inflate availability figures
- Generate dispute-ready evidence faster and with greater confidence
By bringing transparency and rigor to availability calculations, owners can reduce unnecessary payouts, defend claims, and ensure contractual performance aligns with reality — protecting both revenue and long-term relationships
From data to decisions: A new standard for solar asset management
The solar market has matured. Success today depends not just on generating energy, but on explaining performance, managing risk, and proving value to increasingly sophisticated stakeholders.
Across reporting, forecasting, monitoring, and contractual reconciliation, Clir’s AI helps solar owners and investors move from fragmented data to credible, decision-grade insights. By grounding financial outcomes in operational reality and scaling that insight with purpose built AI, owners can manage portfolios with confidence, reduce downside risk, and unlock long-term value.
In a market where trust and transparency matter more than ever, a strong data strategy is no longer optional; it’s foundational.
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