Seeing the Unseen: How to Track and Estimate Missing Data

Maintain energy performance and fulfill carbon reporting requirements by overcoming missing data

When managing energy performance across multiple facilities, missing data is inevitable. Utility bills arrive on different schedules, and some facilities have real-time metering while others rely solely on monthly bills. And if you operate globally, you also deal with different currencies, different rates, and fragmented utility data.

Yet, decision-makers need accurate, real-time Key Performance Indicators (KPIs) to optimize operations.

That’s where energy data estimation comes in.

What is Estimated Data?

Estimated Data is Nsight’s intelligent process for ensuring that your facility and portfolio-level energy KPIs are always complete, even when data is missing. It works by:

1. Aligning billing data with calendar months for accurate reporting
2. Prioritizing the best available data sources (AMI, utility bills, or real-time metering)
3. Filling in missing or delayed utility bills with intelligent estimations
4. Handling currency conversions for global operations

With KPI Estimated Data, your Energy Performance Indicators always reflect the most accurate, representative data possible, even when utility information is fragmented.

The Problem: Delayed, Incomplete, or Missing Data

Most companies expect their energy KPIs to match their utility bills—but real-world energy data is more complex.

What causes incomplete utility data?

1. Utility bills don’t align with calendar months – KPIs need to be structured for accurate reporting
2. Real-time meters aren’t the official source of record – IoT metering provides insights but must be corrected against utility data
3. Technical challenges – Integrations and 2FA must be re-established, various file formats parsed correctly, and manual scans require quality control.

How Does Nsight Prioritize Energy Data?

To ensure accuracy, the Nsight® Energy Intensity Platform follows a structured data prioritization system, selecting the best available source at any given time.

For energy usage (kWh), Nsight selects data from:

• Advanced Metering Infrastructure (AMI) – Utility-provided, granular data
• Utility Bills – Monthly statements from energy providers
• Installed IoT Meters – Real-time readings for operational insights

For energy spend ($), Nsight automatically:

• Applies blended rate calculations to normalize costs
• Converts global currencies into a standard portfolio currency (e.g., USD)
• Estimates missing utility bills using past spending patterns

How Nsight Ensures Accuracy: Correction Factors

Even when real-time meters are installed, they may capture slightly different values than what appears on utility bills. To resolve this, Nsight applies correction factors, which are small adjustments that align IoT meter readings with utility-reported data.

Daily Correction Factor: If utility bill data is available, the system compares it against IoT data and adjusts accordingly.

Rolling 12-Month Correction Factor: If utility data is missing, Nsight calculates an average of the last 12 months to estimate the most accurate possible values.

This means KPI calculations dynamically adjust in real-time as new billing data arrives, ensuring accuracy without manual intervention.

Why Data Estimation Matters

With KPI Estimated Data, Nsight ensures that:

1. You always see the most accurate, complete energy performance indicators
2. Global energy costs are standardized for easy portfolio-wide tracking
3. You never have to guess why data is missing—our system fills in the gaps intelligently

The result? You get a clear, uninterrupted view of your energy performance—even when utility data is fragmented.

The Importance of Measuring Missing Data for Carbon Reporting Standards

For organizations reporting under carbon disclosure frameworks like CDP, accurately assessing data completeness is critical. Carbon emissions calculations rely on utility data, and gaps or inconsistencies can lead to underreporting, overestimations, or compliance risks. CDP, GHG Protocol, and other sustainability reporting standards require transparency about data coverage and estimation methods—meaning organizations must track what percentage of their energy and emissions data is actual versus estimated, and they must explain how they fill in data gaps.

Nsight’s KPI Estimated Data not only ensures that missing data is intelligently filled, but it also enables companies to quantify how much of their carbon reporting is based on estimates versus actual utility records. By actively measuring incomplete data, companies improve the credibility of their reports, enhance decision-making, and increase their CDP scores—all while maintaining a clear, audit-ready trail of energy and emissions data.

Missing Data: Conquered

Data challenges shouldn’t prevent you from making smart energy decisions. Nsight’s KPI Estimated Data ensures continuous, reliable insights, whether you’re dealing with missing bills, real-time metering discrepancies, or global energy costs.

Ready to get better energy insights? Contact us today to learn more about how KPI Estimated Data can help optimize your facility and portfolio-wide Energy Performance Indicators.