Data Fragmentation Is the Core Barrier to Energy Performance

Energy performance is not constrained by data availability.
It is constrained by fragmentation.

Meters, control systems, engineering models, utility programs, and analytics tools all describe performance differently. Each uses its own assumptions, baselines, and definitions of success.

As a result, energy performance is measured — but rarely comparable.

Fragmentation Eliminates a Common Reference

When performance is defined differently across:

Buildings
Engineers
Contractors
Utility programs

There is no shared reference for “good.”

This makes it difficult to:

Compare performance across assets
Verify savings consistently
Defend results to regulators
Scale analytics beyond individual projects

Fragmentation Breaks Accountability

Most analytics describe behavior, but do not establish a standard.

Without a consistent, measured reference:

Benchmarks vary by tool
Baselines vary by methodology
Results vary by interpretation

Fragmentation turns analytics into reporting, not verification.

Measurement Is the Only Scalable Unifier

Fragmentation is resolved when performance is defined by measurement, not assumption.

When measured behavior is normalized across operating conditions and compared across peer groups, performance becomes:

Comparable
Repeatable
Verifiable

That measured reference enables analytics to function as a standard, not an opinion.

Why This Matters

Without resolving fragmentation:

Energy performance cannot be scaled
Savings cannot be defended
Programs cannot persist

Resolving fragmentation at the measurement level is a prerequisite for credible analytics.