Why Fragmented Building and Energy Data is Costing You Millions

Commercial real estate portfolios are awash in data. Modern buildings generate millions of data points per year across building management systems, submeters, utility bills, energy procurement platforms, CMMS tools, sustainability reporting software, and bespoke spreadsheets maintained by engineering and energy teams.

But data alone is not a panacea. Many owners and operators still struggle with rising energy spend, underperforming capital projects, and decarbonization plans that feel increasingly expensive and uncertain. 

When building, energy, and financial data live in disconnected systems – owned by different departments, updated on different timelines, cutting across different organizational levels, and interpreted through different lenses – teams lose the ability to understand cause and effect. That loss of visibility quietly erodes operating margins, inflates capital risk, and slows progress toward climate goals. And for large portfolios, the cumulative cost can often be measured in millions of dollars per year. 

In this article, we’ll explore the hidden costs of disconnected data and share strategies for resolution. 

Data Fragmentation Is a Structural Problem for Real Estate

Data fragmentation in the real estate industry is not the result of poor decision-making. Rather, it’s the natural outcome of how buildings have historically been managed: 

• Facilities teams deployed BMS platforms to maintain comfort and reliability, focusing on performance at single buildings 
• Energy teams focused on procurement and utility relationships
• Asset management and finance teams reviewed utility spend retrospectively, often months after usage occurred, as a line item within broader OpEx budgets 
• Sustainability teams sought a variety of data for carbon accounting and other reporting and regulatory requirements 

In short, each function adopted tools optimized for their own objectives.

The result is a persistently fragmented operating environment:

• Real-time equipment and sensor data siloed away in building-level BMS 
• Interval energy data separated from price and contract terms
• Utility bills arriving as static PDFs long after decisions could have been influenced
• Emissions calculated in parallel systems with limited operational feedback or visibility 
• Capital planning based on audits, assumptions, and generic benchmarks rather than measured performance

No individual system above is deficient. The problem is that they were never designed to work together.

At the portfolio level, this fragmentation prevents executives from answering basic questions with confidence: Why did energy costs increase? Which assets are truly underperforming? Where will capital deliver the highest return? And at the asset level, it prevents learnings from being shared across regions, small wins from being connected to corporate goals and targets, and successful strategies from being measured and understood accurately. 

How Fragmented Data Translates Into Financial Loss

Fragmentation creates persistent financial drag in several predictable ways.

1. Energy Spend Becomes Difficult to Explain (and Control) 

When energy costs rise, teams often attribute the increase to weather or market conditions. Sometimes that is correct. Often it is incomplete.

Without aligning interval usage, pricing, weather, and equipment behavior, organizations struggle to distinguish external factors from operational inefficiencies. Control failures, scheduling drift, and degraded equipment performance can persist for months without detection.

Studies by the U.S. Department of Energy and Lawrence Berkeley National Laboratory consistently show that many commercial buildings operate 10–30% below optimal efficiency, largely due to operational issues rather than design flaws. 

Across a large portfolio, even a sustained 3–5% efficiency gap can equate to seven-figure annual energy waste. (More on that below!) 

2. Capital Is Allocated Based on Assumptions, Not Evidence

Capital planning in real estate remains surprisingly static. Equipment is frequently replaced based on age, nameplate data, or one-time audits that provide only a narrow snapshot of performance. Fragmented data makes it difficult to assess how assets actually perform under real operating conditions or how quickly degradation is occurring.

As a result:

• High-performing assets may be replaced prematurely
• Underperforming systems may escape attention until failure
• Payback and savings are incorrectly estimated and calculated 

Data-driven capital planning that is grounded in measured performance rather than assumptions or generic benchmarks can materially improve ROI on energy and infrastructure investments. Fragmentation makes that rigor difficult to achieve.

3. Operating Teams Are Consumed by Manual Reconciliation

From an executive perspective, labor efficiency is often overlooked in energy discussions. 

Fragmented systems force building engineers and energy managers to spend significant time exporting data, reconciling meters to bills, normalizing units, and explaining discrepancies across departments. This work is necessary, especially in the absence of a unified system or technology solution, but it does not scale.

As operating teams grow leaner and the decision-making environment becomes more complex, this hidden workload limits portfolio oversight and increases key-person risk. Strong operators become indispensable not just because of strategic insight, but because they know where the data gaps are (and how to patch them manually). Over time, this dynamic drives higher labor costs, slower response times, increased team burnout, and greater risks to operational continuity. Additionally, fragmentation can prevent site-level learnings and wins from being applied elsewhere, artificially limiting the impact of optimization strategies across the portfolio. 

4. Decarbonization Efforts Become More Expensive Than Necessary

Decarbonizing the built environment is fundamentally an operational problem, not just a reporting one.

Carbon outcomes depend on when and how energy is consumed, the carbon intensity of the grid at that moment, and how building systems respond. But when energy, operational, and emissions data are disconnected, organizations default to blunt strategies: blanket retrofits, static intensity targets, and annual reporting cycles. 

These approaches miss lower-cost, asset-level opportunities such as load shifting, operational tuning, demand response, and grid-aware control strategies – even as industry bodies like RMI have emphasized that operational improvements and controls optimization are among the lowest-cost paths to near-term emissions reduction in buildings (and should be tackled before deeper retrofits). 

Unfortunately, the operational challenges brought on by data fragmentation often make these approaches infeasible (if not impossible) at scale, relegating decarbonization to an abstract compliance exercise (or a costly case for capital upgrades) rather than what it is supposed to be: the material reduction of emissions. 

Why the Cost of Fragmentation Is Increasing

The financial impact of fragmented data is growing, not shrinking, with several structural trends amplifying the downside:

• Increased energy price volatility, raising the value of operational flexibility
• Proliferation of distributed energy resources such as solar, battery storage, and EV charging
• Tighter carbon regulations requiring auditable, defensible data
• Continued pressure to operate larger portfolios with smaller teams

Each new system adds data – and another integration boundary. Without a unifying data layer, complexity accumulates faster than insight.

What More Integrated Organizations Do Differently

Leading owner/operators are not replacing every system in their stack. They are focusing on integration and alignment.

Common characteristics include:

• A portfolio-wide source of truth for energy and operational performance
• Time-aligned data across meters, equipment, pricing, and weather
• Clear mappings between physical assets, utility accounts, and financial reporting
• Continuous performance visibility instead of quarterly or annual surprises

This integration enables more disciplined decision-making, in which energy cost changes are explainable, capital allocation is empirical and evidence-based, engineers leverage data for day-to-day operations and management, and financial and sustainability objectives reinforce each other. 

The Executive Cost of Inaction

Fragmented data rarely appears as a discrete budget line item. Instead, it shows up as:

• Chronic energy overruns labeled as “market-driven”
• Capital projects that miss projected savings
• Missed incentive, demand response, and flexibility revenues 
• Operating teams stretched thin by manual processes  

Individually, these issues are easy to rationalize. Collectively, they represent a material and persistent drag on portfolio performance.

For large owner/operators, the difference between fragmented and integrated data environments can equate to millions of dollars per year, not due to one single failure but rather hundreds of small inefficiencies that compound over time. 

To put this into perspective, consider a large commercial owner/operator with 10 million square feet under management. A conservative average energy spend for that portfolio might be $2–3 per square foot annually, or $20–30 million per year in total energy costs.

According to the U.S. Department of Energy, portfolios that deploy integrated energy information systems and analytics consistently achieve 3 to 9% annual energy savings through improved visibility, fault detection, and operational optimization.

Applied to this hypothetical portfolio, that translates to:

• $600,000–$900,000 per year at the low end (3%)
• $1.8–$2.7 million per year at the high end (9%)

Importantly, these savings are not driven by a single major retrofit. The DOE’s analysis shows they largely come from identifying and correcting hundreds of small operational inefficiencies – ranging from control errors, scheduling drift, simultaneous heating and cooling, sensor failures, and unnoticed degradation – that persist when data is fragmented across systems.

Over a five-year period, even the conservative case can represent $3–5 million in avoidable operating cost, before accounting for avoided capital misallocation, labor efficiency gains, or carbon-related incentives.

Final Thoughts 

Buildings are complex, interconnected systems. Managing energy, operations, finance, and sustainability as separate domains was once unavoidable – but today, it has become a strategic liability.

Fragmented data obscures cause and effect. It makes rising energy costs harder to explain, capital harder to allocate with confidence, operating teams harder to scale, and decarbonization efforts more expensive and ineffectual than they need to be. The result is a steady accumulation of small inefficiencies that quietly erode portfolio performance year after year. 

By contrast, organizations that invest in integrating their building and energy data gain something far more valuable than dashboards or reports: control. They can see how assets actually perform, understand why costs change, intervene earlier, scale successful strategies, and align operational decisions with financial and climate outcomes. Over time, those advantages compound – just like the costs associated with fragmentation. 

The question facing today’s real estate owners and operators is no longer whether they have enough data; most already do. The real question is whether their organizations are structured to turn that data into coherent insight and disciplined action.

In an environment defined by volatile energy markets, tightening margins, and increasing regulatory pressure, integration is no longer an IT concern – but a core operational and financial strategy.

About Noda

Noda is a data and analytics company on a mission to make every building smarter, more efficient, and more sustainable. Recently ranked in the top 10 tech companies leading the charge on climate action, its AI-powered suite of products surface unique insights that empower real estate teams to reduce costs, decrease time spent on routine work, and find and act on opportunities to save energy and carbon. Discover how Noda's solutions can unlock the potential of your assets and accelerate the transition to net zero. Visit us at noda.ai to learn more.