Define a hit policy and the completeness requirement

With the hit policy, you define how your decision table manages inputs that are handled by several rules and inputs for which no rules are defined. There are two types:

Single hit policies produce one result per input. Here, only one rule is applied at a time, even if several rules exist.
Multi hit policies produce an array of outputs. Here, all applicable rules are considered regardless of their position in the table. The resulting output can be a list or aggregated to a single value.

With the completeness requirement, you define whether your decision table is only valid if its rules consider all possible inputs. This means, a table is only valid if the modeler added rules for all input data. When checking the decision table with Verify, the completeness is checked as well.

Unique (single) is the default hit policy. Read more in section Hit policy types.

To select another hit policy for a decision table, follow these steps:

In a DMN diagram, click in the decision element.

The decision table opens.
Click the letter in the upper left corner.

The configuration dialog opens.

Example

Example:
Select the hit policy. Find details on each hit policy type below.
In case of a multi hit policy, select the aggregation:
- Collect (multiple)
- Sum
- Minimum
- Maximum
- Count
Select the completeness requirement:
- Complete: A complete decision table is only valid if it considers all possible inputs.
- Incomplete: An incomplete decision table is valid even if it doesn't consider all possible inputs.
Confirm with Save.

The hit policy and completeness is set.

Hit policy types

Unique (single)

One input combination is covered by exactly one rule. It's assumed that all inputs are independent of each other, so any combination is possible. Overlapping rules are not allowed.

Unique (single) is the default hit policy. In the decision table, it's indicated with the letter U.

Example

Example:

Depending on the current season, a retailer decides which product group to offer at a reduced price. Only one product group can be offered, since only one season exists at the same time.

Input	Output
Season	Product group
Spring	garden equipment
Summer	beverages
Autumn	clothes
Winter	food

Any (single)

Multiple rules cover the same combination of input values. This overlap is only allowed if the rules also lead to the same result.

In the decision table, this hit policy is indicated with the letter A.

Example

Example:

If a credit applicant is younger than 18 years old and is already in debt, the application is rejected. Otherwise the credit applicant gets a credit.

Input		Output
Age	Debt	Result
< 18	yes	rejected
-	no	approved
>= 18	-	approved

Priority (single)

Multiple rules can apply for one input value. The results are ordered according to their priority. The result with the highest priority is returned.

In the decision table, this hit policy is indicated with the letter P.

Example

Example:

In a decision table, the logic determines at what age customers get certain discount vouchers. Customers aged 18 or over get vouchers for sports equipment, and all customers older than 3 vouchers for toys. Both rules apply to a 30-year-old customer. As the sports equipment has a higher priority, the customer gets a voucher for this. Consequently, the output list is [sports equipment, toys, clothing].

Input	Output
Age	Voucher for
> 18	Sports equipment
> 3	Toys
-	Clothing

First (single)

Overlapping rules are allowed, but only the first applicable rule is used. As the rules are evaluated from top to bottom, you must sort the rules in the table.

In the decision table, this hit policy is indicated with the letter F.

Example

Example:

In a decision table, the logic determines at what age customers get certain discount vouchers. Customers aged 18 or over get vouchers for clothing, and all customers older than 3 vouchers for sports equipment. Both rules apply to a 30-year-old customer. As the rule for 18-year-old customers is at the top of the decision table, this rule serves as the basis for the decision. The customer receives a voucher for clothing.

Input	Output
Age	Voucher for
> 18	Clothing
> 3	Sports equipment
-	Toys

Collect (multiple)

By default, the collect hit policy collects the outputs of matching rules, but can be configured to determine the sum, minimum, maximum, or count of matching outputs instead.

In the decision table, this hit policy is indicated with the letter C.

Example

Example:

An online shop adds a discount coupon to specific orders. The discount depends on the total sum of an order. In the decision table below, the outcome differs depending on the aggregation set for the hit policy. Given a 250$ purchase order, the following applies:

Without aggregation set, the hit policy returns two coupons (5% and 25% discount) in no particular order.
With aggregation set to sum, the hit policy returns one coupon with 30% discount.
With aggregation set to maximum, the hit policy returns one coupon with 25% discount.
With aggregation set to minimum, the hit policy returns one coupon with 0% discount and disappoints the customer in this scenario.
With aggregation set to count, the hit policy returns 2, which doesn't provide any relevant information in this scenario.

Input	Output
Total order sum	Discount coupon
<= 50$	0%
> 50$	5%
> 200$	25%

Output order (multiple)

Results are ordered by the priority of the output values.

In the decision table, this hit policy is indicated with the letter O.

Example

Example:

An online shop adds small gifts to orders. The gifts a customer receives depend on the total order sum. If the order sum is 50$ or lower, the customer receives a discount coupon. If the order sum exceeds 50$, the customer receives a small pack of high-quality coffee in addition to the coupon.

With an output order hit policy, for the total order sum of 250$ the table below will return the result [Coffee, Discount coupon], sorted according to the order of the specified output list.

Input	Output
Total order sum	Gift = [Coffee, Discount coupon]
-	Discount coupon
> 50$	Coffee

Rule order (multiple)

Results are ordered by the order of matching rules.

In the decision table, this hit policy is indicated with the letter R.

Example

Example:

When applying a rule order hit policy, an input of 250$ will return the result [Discount coupon, Coffee], sorted according to the order of the applying rules.

Input	Output
Total order sum	Gift = [Coffee, Discount coupon]
-	Discount coupon
> 50$	Coffee

Next steps

Define a decision logic

DMN simulation