Analysis and study reports produced by third parties usually have a warning or disclaimer statement that acts to relieve third parties of liability due to risk or uncertainty.

Good examples are proforma site analysis reports car wash equipment manufacturers use to help their clients accurately define trade areas and evaluate a site’s car washing potential.

Such reports are usually obtained as part of the due diligence process to determine if the proposed market and site are likely to be a success or a flop.

Principal reasons for disclaimers are factors that can affect accuracy such as quality of information and intangibles which are not known or controllable by third parties.

Consequently, the findings and conclusions arrived at in such reports are described as estimates or projections but not representations of actual results or a guarantee of any volume of business, sales, or income.

In other words, such analysis should be considered as a best effort opinion of anticipated results.

I say anticipated results because legal experts opine that “expectation” shows a level of certainty whereas “anticipate” is unconditional to a certain degree.

Consequently, it is advisable to obtain several opinions before deciding if a market and site merit further consideration for acquisition and development.

Similar to solving a medical problem, getting a second or third opinion can provide more cohesive information and help minimize the possibility of misdiagnosis.

When reconciling different opinions, it is important to understand the methods involved and the underlying assumptions and limiting conditions.

For example, a proforma site analysis usually begins with an estimate of cars washed per day. Most often, the method used for this purpose is an analog-based model.

An analog is a group of existing stores that have very similar location and site characteristics and sales volumes.

The model is organized into a checklist of factors and attributes that have been identified through statistical analysis as being most relevant to driving sales. For example, area profile, highway traffic, lot position, visibility, access, hours of operation, and so forth.

Some models also include a separate demographic component to account for population, income, age, and base price.

In practice, conditions at the site are compared with those in the model and a score is developed for each factor. Individual scores are then combined and a forecast interval for the sales of the new site is defined for average cars washed per day (i.e., low-side, high-side).

Although industry models may be similar in terms of method and organization, the opinion of the folks who apply the models are often not, which makes reconciliation difficult.

For example, proforma models typically contain an acquisition budget that is used to develop a debt allocation. However, the budget is a fill-in-the-blank summary of cost rather than an estimated cost basis tied directly to the sales forecast.

Moreover, the analog models do not account for factors such as unlimited wash options which have a great effect on sales volumes. Since budget and debt are not directly tied to sales forecast, this can affect accuracy of financial projections and analysis.

In the final analysis, accuracy is how close a measure value is to the true value. In pursuit of true value, principals should make a best effort to provide cohesive information and follow the equipment supplier’s process.

By following process, principals can identify a site’s potential performance, its standalone value, and obtain recommendations for best-fit business models.

Bob Roman is a car wash consultant. You can reach Bob via e-mail at or by visiting