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Bias Management in Business Valuation

Business valuation is a mathematical process dealing with data and assumptions as well as numerous examinations, decisions and more assumptions that invites personal judgement, and hence bias.


As polarising interests are at stake, bias will inevitably be at play while valuing a business. Hence bias management is necessary to avoid crippling the business valuation.

For an effective bias management, it is important to first identify places where bias is likely to occur, and then select the appropriate measure to reduce its unwanted consequences.

The Usual Origins of Bias Are As Follows:


1. Forecasts

For valuation models grounded on future cash flows, forecasts are the main suppliers of information. A forecast is a prediction of the future sales and revenue, and the movement of money in a business in years to come.

Much bias can happen in the process of forecasting. One example involves over-relying on personal reflections of past events and instincts to approximate revenue growth rates and profitability metrics. Information with solid evidence or from valid sources should be used instead.


Another is the confirmation bias, which happens even when factual information is used. Confirmation bias occurs when evidence is gathered to support or ‘confirm’ pre-conceived notions or views. This leads to a skewed analysis that may be overly optimistic or pessimistic.

A last example of bias lies in the use of past performances and results of the business, usually referred to as the ‘historical data’ of a business. There must be caution to relying on historical data as their raw value may have been stripped off after normalisation.

2. Valuation Inputs

Besides forecasts, there are other valuation inputs that involve assumptions to a significant degree where bias can occur. These inputs are connected to the working capital, capital expenditure requirements, criteria for redundant assets, discount rates and terminal value adjustments.


In the case of discount rates, which inform about the risks involved in the future cash flow of a business, bias occurs when identifying the factors and their degree of influence. This will lead to biased considerations, which are then used to set the discount rates. A business valuation formed from such inaccurate inputs will no longer be able to fulfill its original purpose.

3. Valuation Multiples

This form of relative valuation is a common approach in most valuation models. It involves surveying a set of comparable companies or businesses available in the market. Problems arise when the comparable company or business is publicly traded and its information is not easily accessible or readily available.


Bias then occurs when using the next viable candidates that are less comparable in terms of size, product mix, end markets and so on.


It will also happen when using the valuation multiples based on open market transactions - some of them may be outdated hence not true representative of the ones from the most comparable (but not accessible) candidates.


Even with the actual valuation multiples of the most comparable business, bias can still occur when there is data selection to fulfill the objective of valuation.

4. Application of Discounts or Premiums

In cases of valuations of private business for income taxes and other disputes like the shareholder dispute, discounts and premiums are usually used. These include the illiquidity discount, the minority discount and the control premium.


As factual details about discounts and premiums are limited, they can be used with bias to raise or lower the resulting valuation to fulfill the circumstances.

Each Of The Biases Above Can Be Managed According To Their Nature. Some of These Methods Are Listed As Follows:


1. Corroborate Forecast Inputs

Macroeconomic influences such as the industry growth rates and market share, can be used to reduce the effects of biases in approximating growth rates in revenues.


Valid and substantial data that are contradicting should still be considered by using them as ‘stress-test’ for the forecast. For example, a forecast may predict a business to develop and expand faster than the industry’s average growth rate while data suggests a general trend of businesses following the industry’s average growth rate in the long run, then the forecast should use a longer time period to increase its validity.


To reduce the bias in using historical data, the historical figures of profit margins as a percentage of revenues should be verified as much as possible using industrial evidence from valid sources.

2. Corroborate Valuation Inputs

As much as possible, factual information that can be verified through valid sources should be used when determining the substantial valuation inputs. Examples of such information are the historical data (for valuation inputs like the working capital and capital expenditure requirements); market-based information (for discount rates).


Industrial data is also useful for determining working capital and capital expenditures in cases of scarcity of historical data or immature data.

3. Cross Check Results

This can be done with a second valuation using a valuation model different from the first one. So if the first business valuation was done via the cash flow based method, then the second one must use another unrelated approach. This second valuation can then verify the logic and consistency of the results from the first one, which then proves the validity of the inputs and forecasts.


Cross checking for the valuation multiples of a business can be done through making comparisons with similar multiples of comparable businesses or its earlier transactions. When the cross check is appropriately implemented, the results can then be used to stress-test the approach of the first valuation.

4. Valuation Range

The numbers used in business valuation are approximate in nature. Hence they should be represented in a range to allow for the natural margin of error.


This range can be derived from viable possibilities and/or the maximum to minimum approximation. The final version should hence be the most accurate representative of the actual value and the most encompassing of its true form.

As business valuations are based on predictions, generalisations and numerous assumptions due to the macroeconomic factors, the industry and the business itself, they are ultimately not definite by nature, and hence cannot be completely bias-free.


However, these biases and their impact can be reduced to minimum through valuation approaches that engage factual data and information with valid sources.


Hence it is very important that the valuation process is conducted by a trained and experienced valuer instead of relying simply on ‘feelings’ and estimations.

If you think your case is complex and want to speak to a specialist, do not hesitate to contact us for a non-obligatory initial consultation.


www.businessvaluation.com.sg

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