Which of the following are common pitfalls associated with reconciliation?

• A. Predestined conclusions
• B. Incorrectly disregarding data
• C. Incorrect data
• D. All of the above

Answer: (D)

Reconciling value requires objective synthesis and careful handling of data. Predestined conclusions show bias where you arrive at a final value before weighing all the evidence, trying to fit data to a desired outcome rather than letting the data drive the result. Disregarding data means you omit relevant comps or adjustments that could change the value conclusion, which weakens the credibility of the reconciliation. Using incorrect data introduces errors from the start, such as misdated sales, mischaracterized properties, or wrong adjustments, and those mistakes propagate into the final value.

Because each of these issues can skew the final number in different ways, all of them are common pitfalls to avoid. The best practice is to stay objective, consider all relevant data with justification for inclusion or exclusion, verify data accuracy, and document the rationale and weighting used in the reconciliation.