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Case study: Turning market complexity into clarity for better real estate decisions

 Learn how data-driven analysis brought clarity to a complex industrial lease decision.

About the client: Industrial real estate owner navigating market rent pressures

A large public sector organization with a significant real estate portfolio supporting critical infrastructure, transportation, and operational functions across a major metropolitan area has a real estate team that is responsible for evaluating complex lease transactions, navigating shifting market conditions, and ensuring that decisions are well supported, transparent, and defensible. Given the public nature of the organization, each real estate decision must withstand heightened review and scrutiny from multiple stakeholders, requiring a high degree of rigor and clarity.

The challenge: Building a defensible rent position from incomplete market data

Determining market rent in today’s industrial real estate environment is increasingly complex, particularly in markets experiencing uneven growth, shifting demand drivers, and wide variation in lease structures. While access to data has improved significantly, consistency, transparency, and reliability have not kept pace. 

For this engagement, the client needed a clear, supportable view of market rent and operating costs for a newly constructed industrial facility in Chicago’s South submarket. Initial market data appeared directionally helpful, with reported rental rates spanning a wide range based on recent leasing activity, broker insight, and third-party databases.

However, a deeper review quickly revealed a more complicated reality. Many of the available data points were not directly comparable, reflecting meaningful differences in submarket location, building quality, tenant size, lease terms, and the structure and magnitude of concessions such as tenant improvements and rent abatements. In some cases, key details necessary to interpret the data were either not disclosed or could not be independently verified.

At first, available market data appeared helpful. But a deeper review showed that many data points were not directly comparable, making it difficult to rely on headline rents alone. For a public sector client operating in an environment where decisions must be both defensible and transparent, that level of uncertainty was not acceptable.

The client was not simply looking for a range of numbers; They needed clarity. Specifically, they needed to understand what the market was actually indicating, how different data points should be interpreted, and how to translate that information into a defensible position for negotiation and internal decision-making.

Our approach: Moving beyond headline rents with multi-layered lease validation

CohnReznick’s Valuation Advisory team approached the engagement with a clear objective: Move beyond reported figures and uncover what the data truly represents.

Rather than relying on any single source, the team developed a comprehensive and defensible analytical framework that combined data validation with real-time market insight. The team’s approach included: 

    • Independent verification of comparable lease transactions and evaluation of the completeness and reliability of reported data
    • Direct engagement with active brokers and market participants to understand current leasing trends, concession structures, and negotiation dynamics
    • Adjustment of reported rental rates to reflect effective economics by normalizing for tenant improvements, free rent, and other incentives 
    • Careful assessment of submarket differences, scale, and property characteristics to ensure appropriate comparability
    • Quantification of above market deal components, including significant landlord funded improvements, and incorporation of those elements into an adjusted rental framework

This multi layered process helped ensure that each data point was tested, contextualized, and aligned with actual market behavior rather than accepted at face value. 

What the data revealed: Hidden variability in industrial market rent

The analysis confirmed that widely referenced “market” rents often mask significant variability in underlying deal structures.

Leases in more central or infill locations demonstrated clear pricing premiums driven by access, density, and demand drivers. At the same time, several transactions included substantial tenant improvement packages and concession structures that elevated reported rents while materially altering the true economics of the deal.

By normalizing these differences and aligning each data point on a consistent basis, we were able to develop a supportable rental range that reflected both the subject property’s competitive position and the realities of the current market. Just as importantly, the analysis clarified how to interpret the broader data landscape, giving the client a more reliable framework for evaluating future opportunities.

This level of engagement was driven by the report’s ability to connect technical analysis with real world application. By clearly explaining how factors such as tenant improvements, operating cost structures, and submarket dynamics influence value, the analysis translated complex concepts into practical understanding.

As a result, the client came away not only with a supported conclusion, but with a stronger ability to interpret market conditions, evaluate competing data points, and make more informed decisions in a rapidly evolving environment.

Client perspective: A different class of real estate analysis

The value of the engagement extended well beyond the delivery of a single conclusion.

With more than two decades of experience reviewing appraisal reports, the client noted a clear distinction in both the depth of analysis and its practical relevance to their role: “I have reviewed countless appraisal reports over the past two decades. The reports I receive from CohnReznick are in a completely different class than what I had become accustomed to.”

That difference was reflected in how the report was used. Rather than scanning for a conclusion, the client engaged with the analysis in full, noting that they read the report from beginning to end and returned to it a second time to fully absorb the insights.

"I had never read an appraisal report from cover to cover. I read yours front to back – twice."

The strategic outcome: A repeatable framework for confident lease negotiations

With a clear and well supported analytical framework in place, the client was able to move forward with lease negotiations and strategic planning decisions with a significantly higher degree of confidence.

The final deliverable provided more than a concluded rental range; It offered a transparent and defensible explanation of how that range was derived, including how to evaluate competing data points and reconcile differences across sources. This clarity enabled the client to align stakeholders internally while also supporting their position in external discussions where assumptions are often challenged.

The engagement also helped reduce the inherent risk associated with relying on incomplete or inconsistent market data. By distinguishing between headline lease rates and true economic terms, the client was able to approach negotiations with a more accurate understanding of value, supporting fair and balanced outcomes.

Importantly, the benefits extended beyond the immediate transaction. The analytical framework developed through this process provides a repeatable approach that the client can apply to future real estate decisions. In a market where conditions continue to shift and data can often be misleading, having a disciplined method for interpreting information is critical.

The result was not just a well-supported conclusion, but a more informed and confident decision maker equipped to navigate complex market dynamics with greater clarity.

At CohnReznick, we help clients move beyond surface-level metrics by digging deeper into the marketplace to uncover meaningful insight. This approach supports more accurate, defensible conclusions and ultimately leads to better decision-making in even the most complex environments. 

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