Every location recommendation rests on a foundation of assumptions — about labor markets, infrastructure, incentive availability, cost projections, and client priorities — and when those assumptions are invisible, the recommendation is fragile. Documenting them with discipline transforms a persuasive pitch into a defensible advisory record that survives scrutiny, client changes, and deal revisions.
Why Assumption Documentation Matters in Site Selection
A location recommendation is not simply an address delivered with confidence. It is the endpoint of dozens of explicit and implicit judgments about what the client values, what the market can provide, and what the future is likely to hold. When those judgments live only in an adviser's head, every conversation risks misalignment and every revision risks starting from scratch.
Documented assumptions give a recommendation its evidentiary spine. A client who later asks why a particular submarket was chosen — or why a competing location was excluded — receives a clear, traceable answer rather than a reconstructed narrative. That traceability protects both the adviser and the client when conditions shift mid-search.
Assumption documentation also disciplines the analysis itself. The act of writing down why you expect labor costs to remain stable in a given corridor, or why you believe a municipality's incentive program will apply to the client's use case, forces the adviser to test the logic before presenting it. Weak assumptions surface early, before they become embarrassing gaps in a board-level presentation.
The site-selection process involves multiple workstreams running simultaneously — real estate, tax, legal, HR, and operations — and each produces its own assumptions. Without a shared documentation layer, contradictions accumulate silently. A tax team's assumption about eligibility thresholds may conflict with the real estate team's headcount timeline, and neither team discovers the conflict until late in diligence.
Establishing the Client Brief as the Assumption Baseline
Every assumption chain starts with the client brief. Before any market is evaluated, the adviser must capture what the client has stated as requirements, what they have implied but not stated, and what they have explicitly ruled out. These three categories produce very different assumption risks.
Stated requirements — square footage range, headcount capacity, access to specific transportation nodes — carry the lowest assumption risk because they are documented in the client's own words. Implied requirements — cultural fit with a particular city, proximity to existing leadership, preference for ownership over leasing — carry higher risk because they must be inferred and confirmed. Explicit exclusions carry the highest risk, because misunderstanding them can produce a shortlist the client dismisses entirely.
The adviser's first documentation task is to convert every implied preference into a written assumption, share it with the client, and obtain acknowledgment. This is not bureaucratic formality. It is the only way to ensure that a location scored highly on proximity to the client's preferred talent pool was scored against a criterion the client actually holds, not one the adviser assumed they hold.
Scoring criteria should be weighted at this stage, not after the market analysis. Weighting decisions made before data collection carry more analytical integrity than weights adjusted to justify a predetermined answer. Record the weights, the rationale behind each, and the client stakeholder who approved them.
Structuring the Assumption Register
A working assumption register is not a notes file or a slide appendix. It is a structured record with consistent fields: the assumption itself, the category it belongs to, the data source or reasoning behind it, the date it was recorded, who recorded it, and the conditions under which it should be revisited.
Categories should map to the analytical workstreams in a typical site selection engagement. Labor and workforce assumptions cover availability, wage expectations, commute shed, and competitive employer density. Infrastructure assumptions cover power, water, fiber, transport, and physical site constraints. Cost assumptions cover base rent, operating expenses, build-out projections, and total occupancy cost. Incentive assumptions cover program eligibility, benefit quantum, and timing. Regulatory assumptions cover zoning, permitting timeline, and use restrictions.
Each assumption should carry a confidence classification. A common three-tier approach labels assumptions as confirmed — supported by a primary source the adviser has reviewed — working — derived from secondary data or reasonable inference — or provisional — based on judgment or early-stage information that requires verification before the recommendation is finalized.
Revisit triggers are as important as the assumptions themselves. If an assumption about a market's available labor pool is based on published workforce data, the assumption should be flagged for review if a major employer announces significant hiring or layoffs in that market after the data was pulled. Building this logic into the register turns a static document into a living analytical tool.
Sourcing and Citing Assumptions Correctly
The quality of an assumption is bounded by the quality of its source. An assumption about average asking rents derived from a broker's market report is a different class of evidence than one derived from a signed lease abstract. Advisers who treat these as equivalent introduce invisible risk into their recommendations.
Primary sources include executed leases, building permits, utility capacity studies, published incentive statutes, government labor statistics, and direct conversations with economic development officials documented in writing. Secondary sources include market reports, brokerage surveys, news coverage, and aggregated data platforms. Tertiary sources include industry rule-of-thumb figures and peer comparisons with no direct data chain.
Every assumption in the register should carry a source tier designation alongside the actual source citation. When a recommendation is built on a stack of tertiary assumptions, that fact should be visible — not buried — so the client can decide what additional due diligence is warranted before committing.
Source currency matters as much as source type. A labor market study from three years ago may not reflect post-pandemic migration patterns. A utility capacity assessment may be superseded by a new industrial tenant that has since absorbed available capacity. Date every source, and flag any source older than twelve months as requiring revalidation before a final recommendation is issued.
Documenting Market Screening Decisions
The markets that did not make the shortlist are as analytically important as those that did. Documenting why a market was screened out creates a record that prevents re-litigation and demonstrates that the adviser's shortlist was not arbitrary.
For each screened market, record the specific criterion it failed to meet. A market eliminated because wage rates exceed the client's modeled threshold should have the threshold stated, the wage data sourced, and the delta quantified — even if only as a hypothetical illustrative range. A market eliminated because incentive eligibility was unconfirmed should note what outreach was attempted and when.
Market screening documentation also protects the adviser when a client later receives an unsolicited proposal for a location that was screened out. With a clear record, the adviser can immediately explain the basis for exclusion and invite the client to reconsider if the underlying assumption has changed — for example, if the municipality has since confirmed a new incentive program the adviser could not confirm at screening.
Advisers working across multi-market searches often face pressure to compress the screening phase to reach shortlist faster. Documented screening decisions provide a professional check on that pressure. When the rationale is written down, shortcuts that would weaken the analysis become visible.
Recording Financial and Cost Assumptions
Financial assumptions are among the most consequential in any site selection engagement, and among the most frequently glossed over. A lease NPV calculation, an effective rent comparison, or a total occupancy cost model all rest on assumptions about discount rates, escalation structures, operating expense treatment, free rent periods, and capital contribution timing.
Every financial model presented to a client should carry an explicit assumption schedule. The discount rate used in a lease net present value calculation should be documented alongside the rationale for choosing it — whether it reflects the client's internal hurdle rate, their weighted average cost of capital, or a benchmark rate the adviser has proposed. The same principle applies to rent escalation assumptions, term length, and renewal probability.
Operating expense assumptions deserve particular care. Gross, modified gross, and triple-net structures produce very different effective occupancy costs, and the differences compound over a lease term. When a model compares options across lease structures, the assumptions used to normalize each structure to a common basis — full-service equivalent or base rent plus estimated expenses — should be documented and presented with the comparison, not embedded invisibly in a formula.
Build-out cost assumptions carry project risk that financial models often understate. A hypothetical illustrative example: if a model assumes tenant improvement allowance covers ninety percent of fit-out cost but the client's actual program requires a specialized build that typically exceeds standard TI rates, the gap creates a financial exposure that was never visible in the comparison. Document the basis for every build-out assumption, including who provided the estimate and when.
Documenting Incentive Assumptions with Rigor
Economic development incentives can represent a meaningful component of a location's economic case, but they are also among the most assumption-intensive elements of any site selection analysis. Programs change. Eligibility thresholds shift. Approval is not guaranteed by eligibility.
When an incentive is modeled into a location's financial case, the assumption register should capture: the program name and administering authority, the statutory or regulatory basis for eligibility, the specific eligibility criteria applied to the client's projected investment and headcount, the stage of confirmation — available, applied for, or awarded — and the timing of expected receipt relative to the client's cash flow model.
Advisers should resist the temptation to model incentives as guaranteed before formal confirmation. A location that appears most competitive only because of unconfirmed incentive value carries a different risk profile than one that is competitive on base economics alone. Document this distinction explicitly and present it to the client as a risk factor, not a footnote.
State and local policies vary significantly and change through legislative cycles. Nothing in a site selection record should assert specific incentive values or eligibility determinations without directing the client to verify the current position with qualified tax and legal counsel. The adviser's role is to frame the incentive landscape and the assumptions behind it, not to provide a legal opinion on eligibility.
Linking Assumptions to the Final Recommendation Narrative
The finished recommendation document — whether a board presentation, an executive summary, or a formal site selection report — should make the assumption structure legible without overwhelming the client with technical detail. The solution is a layered documentation approach.
The recommendation narrative presents conclusions clearly: market, property type, preferred option, financial comparison, and rationale. A supporting appendix presents the assumption register in full, organized by category. A separate source log documents every primary source cited, with retrieval date. This structure lets a board-level reader follow the conclusion, while a CFO or legal reviewer can audit the assumptions in depth.
The recommendation narrative itself should acknowledge key assumptions explicitly rather than treating them as background noise. Phrases such as "this recommendation assumes the client's headcount projection of X reaches the relevant threshold within the program's qualifying window" or "the effective rent comparison assumes a consistent operating expense load across options — individual lease verification is required before execution" convert invisible risk into disclosed risk.
Disclosed risk is not a sign of analytical weakness. It is a sign of professional maturity. Clients who understand that their adviser has identified the load-bearing assumptions in a recommendation — and documented them — are better positioned to monitor those assumptions as the engagement progresses.
How to Document Assumptions Behind a Location Recommendation in a Connected Workspace
The methodology described in this article works best when it is built into the workflow from the first client conversation, not assembled after the fact from email threads, model files, and slide decks. This is where the choice of operational environment matters.
Advantai is a commercial real estate intelligence and operations platform that connects client relationships, property research, documents, and financial decisions in one workspace.
The platform license is $299 per user per month, with an optional Super Agent upgrade at +$99 per upgraded user per month for teams that need specialist, source-backed research built into their analytical workflow.
Building a Review and Version Control Protocol
A documented assumption register is only as useful as the process that keeps it current. Assumptions made at the brief stage will evolve as market data comes in, as the client's requirements crystallize, and as incentive conversations progress. Without a version control protocol, the register becomes a historical artifact rather than a living analytical record.
Establish version milestones that correspond to the engagement's decision gates. An initial version is created when the brief is confirmed and screening criteria are set. A second version is updated when the market shortlist is finalized and primary source data is incorporated. A third version reflects the final recommendation state, including any assumption changes that resulted from diligence findings or client feedback.
Every version change should be logged with a date, the name of the person making the change, the specific assumptions affected, and the reason for the change. This log creates an audit trail that is valuable in post-transaction reviews and in disputes about what was represented at each stage of the engagement.
Peer review of the assumption register before each client presentation is a professional standard that many advisory teams implement informally but few formalize. A second adviser reviewing the register specifically for internal consistency — do the labor assumptions support the headcount model, does the incentive eligibility assumption align with the client's projected investment level — catches logical gaps that the primary analyst may have normalized over the course of the engagement.
Communicating Assumptions to Clients Without Losing Clarity
The goal of assumption documentation is not to bury the client in qualifications. It is to give them the information they need to make a sound decision. That requires translating the assumption register into client language without sanitizing the risk it contains.
One effective technique is to identify the three to five assumptions that carry the most consequence for the recommendation's conclusion — the load-bearing assumptions — and call them out explicitly in the executive summary. For a labor-dependent location decision, the load-bearing assumption might be the client's ability to attract talent from a defined commute shed. For a cost-driven decision, it might be the discount rate used in the lease NPV comparison. Making these visible gives the client a clear audit checklist for the months ahead.
Scenario framing is a useful companion to assumption disclosure. If a key assumption proves incorrect — the incentive program is not confirmed, or the market's effective rent rises before lease execution — what is the impact on the recommendation? Presenting a base case alongside a scenario that stress-tests one or two key assumptions demonstrates analytical depth and prepares the client for contingency rather than surprise.
Clients often receive location recommendations as finished conclusions. Introducing them to the assumption structure behind the recommendation repositions the adviser as a thinking partner rather than a vendor delivering a shortlist. That repositioning strengthens the relationship and creates a foundation for the next engagement.
Maintaining the Assumption Record Beyond the Transaction
The assumption register does not become obsolete at lease signing. It becomes the baseline for portfolio management, lease renewal analysis, and future expansion decisions. An adviser who maintains this record and makes it available to the client creates a durable asset.
When a lease approaches expiration, the assumptions recorded at the time of the original location decision provide context for evaluating the renewal. Has the labor market performed as assumed? Has the operating expense load tracked the model? Have the incentives been received on the timeline documented? Answering these questions from a maintained record is far more reliable than reconstructing the analysis from memory or archived files.
These principles align with the professional standard that assumption documentation should be accessible, auditable, and role-appropriate throughout the engagement lifecycle.
For portfolio teams managing multiple locations, maintaining assumption registers across assets creates a reference library. When a new location decision arises in a market where a prior decision was documented, the historical assumptions — wage expectations, incentive landscape, infrastructure constraints — provide a starting point for the new analysis and highlight what has changed.
The adviser who delivers a recommendation also delivers a record. When that record is maintained beyond the transaction, it becomes the foundation for the next recommendation. That continuity of analytical history is what separates a transactional broker from a trusted strategic adviser. The assumption register, consistently documented and maintained, is one of the primary instruments of that distinction.
About Advantai
Advantai is a commercial real estate intelligence and operations platform operated by ADVANTAGE AI LLC, a Delaware limited liability company. It connects client relationships, property research, documents and financial decisions in one workspace for commercial real estate teams — advisers and brokerage teams, occupier and facility teams, and portfolio teams. The platform covers CRM and origination, requirements and site selection, Property X-Ray (an interactive 3D building workspace), financial modeling and comparison, document intelligence, transactions and diligence, client collaboration, and portfolio strategy with critical dates. The optional Super Agent upgrade adds specialist, source-backed research and automated scenario analysis.
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