Writing Clear Conditions and Actions

Consider a bank’s loan approval process. The decision depends on factors like income, credit score, and employment history. A poorly phrased condition like “Good credit” introduces ambiguity—what qualifies as good? By contrast, a well-defined condition such as “Credit score ≥ 650” removes subjectivity and ensures consistent interpretation across teams.

My experience building decision tables for insurance, finance, and healthcare systems has taught me that vague or inconsistent language in conditions and actions is the leading cause of misaligned logic, incorrect implementations, and audit failures.

This chapter delivers actionable techniques for crafting conditions and actions that are unambiguous, consistent, and ready for implementation. You’ll learn how to define variables, normalize expressions, and use precise language to build decision logic that stands the test of time and scale.

Why Clarity in Conditions and Actions Matters

Decision tables are only as good as the precision of their components. Ambiguity creeps in when conditions rely on subjective phrasing like “high income” or “recent employment.” These expressions vary between stakeholders and lead to inconsistent rule interpretation.

Clear conditions and actions are the foundation of traceable, testable, and maintainable business rules. They enable seamless integration into BPMN workflows, software requirements, and automated rule engines.

When conditions are precise, actions become predictable. When actions are unambiguous, implementation teams know exactly what to code. This avoids rework, reduces disputes, and accelerates delivery.

Best Practices for Writing Decision Table Conditions

Define Variables Early and Consistently

Every condition must reference clearly defined variables. Do not assume shared understanding.

For example, instead of using “customer has a loan,” define the variable as:

• HasActiveLoan — Boolean: true if the customer has a loan that is not paid off.
• CreditScore — Integer: ranges from 300 to 850.
• MonthlyIncome — Decimal: gross monthly income in local currency.

These definitions should appear in a glossary or metadata section, referenced by all decision tables.

Use Uniform Expression Patterns

Standardize how comparisons and ranges are expressed. Avoid mixing formats like:

• “Income > 50,000”
• “Monthly income is more than 50K”
• “Greater than 50,000”

Instead, adopt a single format: “MonthlyIncome ≥ 50,000”. This reduces cognitive load and prevents misreading during validation.

Normalize Logical and Linguistic Variants

Users often express conditions using natural language variations. Normalize them to a consistent structure.

For instance, the following are equivalent:

• “Credit score is less than 600”
• “Credit score under 600”
• “Credit score below 600”
• “Credit score is smaller than 600”

Standardize all to: CreditScore < 600.

Use Boolean Logic with Care

Combine conditions logically using AND, OR, and NOT—but never assume clarity. Always group complex expressions using parentheses.

Example:

HasActiveLoan = false AND CreditScore < 600 OR OverduePayments > 2

This is ambiguous. Use:

(HasActiveLoan = false AND CreditScore < 600) OR (OverduePayments > 2)

Even better, break complex conditions into simpler sub-conditions if possible.

Best Practices for Writing Decision Table Actions

Make Actions Verbs-First and Outcome-Focused

Actions should start with a clear verb and describe a concrete outcome. Avoid vague or passive phrasing.

Weak:

• “Consider rejection”
• “Review application”

Strong:

• “Reject application”
• “Forward to underwriter”
• “Approve loan with 5% interest”

The verb communicates intent. The remainder specifies the action’s scope or conditionality.

Define Action Parameters Explicitly

If an action depends on a value, specify it clearly.

Instead of:

• “Approve”

Use:

• “Approve loan with interest rate of 4.5%”
• “Approve loan with 5-year term”

These are actionable and traceable. They can be directly mapped to code or workflow steps.

Avoid Ambiguous or Overloaded Verbs

Phrases like “handle the case” or “process request” are too vague. They don’t define what happens.

Instead, use verbs that reflect actual system behavior:

• “Send denial notice via email”
• “Submit to credit bureau for scoring”
• “Schedule review in 30 days”

Each of these triggers a specific action in the system.

Common Pitfalls and How to Avoid Them

Even with best intentions, teams introduce flaws in decision table conditions and actions. Here are the most frequent issues—and how to fix them.

Pitfall	Impact	Solution
Using subjective terms like “high income” or “recent employment”	Creates inconsistency across reviewers and systems	Define thresholds: “MonthlyIncome ≥ 70,000”
Combining multiple actions in one line	Hard to test and debug; violates single responsibility	Break into separate actions: “Send email”, “Log decision”
Using inconsistent variable names across tables	Breaks traceability and causes implementation errors	Enforce a shared variable dictionary
Overusing “other” or “default” conditions	Misses edge cases; leads to untested logic	Define all possible combinations explicitly or label as “invalid”

These pitfalls are not failures of intelligence—they’re symptoms of poor process. Implementing a review checklist reduces their likelihood.

Validation and Review: The Final Gate

Crafting good conditions and actions is only half the battle. You must validate them.

Use this checklist before finalizing any decision table:

1. Are all variables defined in a shared glossary?
2. Do all conditions use the same expression format?
3. Are actions verb-driven and outcome-specific?
4. Do all conditions and actions avoid subjective language?
5. Have you double-checked negations (e.g., “not approved”) for clarity?

Run a simple “readability test”: Have a non-technical stakeholder read a rule and explain it. If they can’t, the rule needs rewriting.

Frequently Asked Questions

How do I ensure consistency when multiple people write decision tables?

Establish a standard variable dictionary and syntax guide. Use shared templates in tools like Visual Paradigm. Require peer review for all new tables. This turns individual instinct into collective discipline.

Can I use natural language in decision table actions?

Only if it’s unambiguous and consistently formatted. Prefer structured phrasing: “Approve loan with interest rate X” over “Give approval.” Natural language can be useful in prototypes, but real-world tables must be precise.

What if a condition depends on a complex calculation?

Define the calculation as a separate variable. For example:

• DebtToIncomeRatio = TotalMonthlyDebts / MonthlyIncome

Then use: “DebtToIncomeRatio ≤ 0.4” in your condition. This keeps the condition readable and testable.

How do I handle edge cases like null or invalid values?

Address them explicitly. Add a condition like:

• “MonthlyIncome = null” → “Flag for manual review”

Never assume default values. Document how missing inputs are handled.

Is it okay to use abbreviations in conditions and actions?

Only if they are defined and universally accepted. For example, “CIC” (Credit Information Center) is acceptable only if defined. Avoid “cust,” “loan,” or “app” as stand-ins. Clarity trumps brevity in decision logic.

How often should I review decision table conditions and actions?

Review every time business rules evolve, or at least annually. Update conditions to reflect new policies, and retire obsolete actions. Treat decision tables as living documents, not static artifacts.