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1. Whenever the result depends on multiple input values, it is best to use a decision table.
2. Whenever the result is a calculation, it is best to use a form with a business rule.
3. It is recommended to formally decide which method to use and capture that in an architecture document. A consistent use of a style throughout a project will help the maintainability of a project. There are many roads that lead to Rome, but within one project it is best if all business engineers follow the same road.

Size of a decision table

With multiple inputs or value categories decision table can get very large in size. Decision tables that are too large in size are not easy to oversee and by that to understand. In general you can state that a table should have a maximum of 12 columns. When the number of columns exceeds this number it is advised to split up the table. 

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1. If the party that uses this decision views its customers mostly by their gender, the first table is preferred. If they view their customers in age categories, the second is preferred.
2. In general the legibility of a decision table improves when the conditions are declared with the number of condition alternatives increasing from top to bottom. So even if the first argument of gender and age categories does not apply, there is a theoretical preference for the first table. This is illustrated below.

Conditions versus attribute values in a decision table

If possible, it is strongly advised to model attributes with their values in stead of conditions about these values. See the two decision tables below.

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The bottom decision table uses a condition in stead of attribute values, this is not advised and only to be used when necessary.Persoonlijk vind ik de tweede leesbaarder... Was dat van klein-naar-grot wel zo'n goed argument?

Focus on result in stead of completeness

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1. All males under 21 receive a 10% discount.

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2. All applicants under 18 receive a 10% discount, no matter the gender.

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Extreme focus on results

In the example above, there are in fact four discounts: 10%, 20%, 25% and 30%. It is a fairly common mistake that this means that the decision table should have exactly four result alternatives. See the decision table below, which is absolutely not advised:

Decision table or data rule?

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