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One might argue that - because of the fact that the decision tables are semantically equivalent - it does not matter if you model the first or second table. However, there are two differences that are worth addressing and should be taken into account when designing decision tables:

1. If the party, company or product 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.

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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 the attribute values, this is not advised and only to be used . Because of legibility it is advised to only use this strategy when necessary.

Focus on result in stead of completeness

A safe and fairly easy way to approach the design of a decision table is by creating a result alternative for each possible combination of attribute values. However, this will result in a combinatoric explosion of result condition alternatives and very large decision tables. When all result alternatives differ, this is the correct approach. Most likely, they will not. In that case, the focus should be on the result alternatives in stead of the combination of attribute values. To illustrate this, see the small example below.

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Because of the fact that there are two genders and three age categories, it might not be a big surprise that there are six result alternatives. However, a closer look at these alternatives - with the focus on 10% - reveals two possible design alternatives:

1. All males under 21 receive a 10% discount. If party, company or product that uses this decision actually talks about "males under 21", this is a good approach.

2. All applicants under 18 receive a 10% discount, no matter the gender. If party, company or product that uses this decision actually talks about "anyone under 18", this is a good approach.

Extreme focus on results

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