How to value non-compete agreements

Many issues must be addressed when placing a value on a non-compete agreement. Not all such contracts have a value. Here's how the TMG firm approaches the issue:


...The value of non-compete agreements comes from the potential loss from competition, the probability of competition and the likelihood that the agreement will be enforceable. These factors are taken into consideration utilizing a differential discounted cash flow analysis (“DCF”). The differential DCF reflects two scenarios. Scenario one is a forecast with the non-compete agreement in place and scenario two is a forecast without the non-compete agreement in place. Usually, the difference between the two differential DCF methods estimates the value of the non-compete agreement. An important issue is the discount rate that is being used in the two differential DCF methods. We believe that the discount rate used in the two differential DCF methods should be the same discount rate because it is the different forecasts that account for the risk in the two scenarios, not the discount rate. The risk is best reflected in the forecast of the two differential scenarios. By using different discount rates for the two differential DCF methods, we believe the risk would be double counted. 

In order to project the differential scenarios described above, an analyst must consider the historical loss or gain from similar competition, the historical growth of revenue and management estimates. Furthermore, an analyst must estimate the duration of the affects caused by the non-compete agreement. Factors that affect the duration are age of the individual, their job satisfaction, market demand for this individual and expectation for success of the business. Other qualitative factors must be considered to compute the final value for the non-compete agreement. These factors relate to the desire, ability, motivation and goals of the individual covered by the non-compete agreement.

In computing the value of the non-compete agreement, we gather specific data, such as:

1. History of enforcement – has the company ever had to enforce a non-compete agreement.
2. Age of Individuals cover by the Non-Compete Agreement – the older the individuals are the less likely they will have the desire to compete.
3. Historical Financial Data – used to help project future operating results.
4. Business Forecasts – used to help project the differential scenarios.
5. Copy of the Non-Compete Agreement – to understand the terms of the agreement.
6. Bios on Individuals cover by the Non-Compete Agreement – used to help estimate the probability they will compete.

Once the data is gathered, an estimate of the probability of competition must be quantified. This is accomplished by considering several factors. When the potential value of competition to the individual is low, we would expect a lower probability of competition. In a recent example, the individual had a lucrative earn out in three years from the date of the acquisition. Consequently, it was assumed that the desire to compete was low which reduced the value of the non-compete agreement. Other factors include age of the individual, the financial strength of the individual, historical experience of the individual and the individual’s ability to earn similar compensation without violating the non-compete agreement. Rarely do we assume that the probability is 100% that the individual will compete. As a result, the value of the non-compete agreement is not only based on the difference compute in the two DCF scenarios, but must be multiplied by the probability percentage that competition will occur. We typically compute the difference in the DCF scenarios and apply a probability percentage to compute the final value for the non-compete agreement. If the individual has no incentive, desire, ability, motivation and goals to compete, the value of the non-compete agreement could be worth a nominal value.