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How to Choose Between Standard and Advanced Decision Table Types
Optimize your rule management based on the size and complexity of data by selecting the right decision table type. This categorization improves system performance and storage efficiency, ensuring fast and scalable decision-making processes. Customize your tables to improve flexibility and resource allocation.
Required Editions
| Available in: Lightning Experience |
| Available in: Enterprise, Unlimited, and Developer Editions for clouds that have Business Rules Engine enabled |
| User Permissions Needed | |
|---|---|
| To create, edit, and activate a decision table: | Rule Engine Designer |
| To run decision tables: | Rule Engine Designer OR Rule Engine Runtime |
Complex Rule in Decision Tables
A rule is complex if it uses only OR conditions. This is because the decision table looks through all the fields in a database to find the match, increasing latency and affecting performance. AND conditions, in contrast, specify which fields to check, making the lookup faster.
Differences Between Standard and Advanced Tables
These are the key differences between standard and advanced decision table types.
When to Use Standard and Advanced Decision Tables
Here are some scenarios to help you choose between standard and advanced decision tables.
These additional features are available only in advanced decision table type. If you want to use any of these features, you must use the advanced decision table type.
| Features | Description |
|---|---|
| CSV Data Upload | If you want to upload data through a CSV file. |
| Standard Objects | If you want to use standard objects like Account, Lead, Contact, Opportunity, and Case |
When you need complex rules and want to access features that are available only in advanced decision tables, simplify your rules that use at least one AND condition. Then, use the advanced decision tables.
Standard Decision Table
A bank wants to offer a special loan to customers who meet at least one of these criteria:
- Condition 1: The customer has a credit score greater than 700.
- Condition 2: The customer has been an active user of the bank for more than 5 years till 2024.
- Condition 3: The customer has a monthly income greater than $5,000.
- Condition 4: The customer holds investments worth more than $100,000 in the bank.
The decision to offer the loan is based on OR conditions across these criteria. The decision table condition logic for this scenario is 1 OR 2 OR 3 OR 4.
To determine loan eligibility, review the sample customer details. Each criteria is captured as an input condition field and the loan eligibility output is captured as a result field in the decision table. Customers are eligible if any one of the conditions is met.
| Input | Output | ||||
|---|---|---|---|---|---|
| Customer ID | Credit Score (Condition 1) | Joining Date (Condition 2) | Monthly Income (Condition 3) | Investments (Condition 4) | Loan Eligibility |
| C001 | 720 | 11.11.2023 | $4,800 | $90,000 | Yes |
| C002 | 680 | 03.03.2015 | $5,200 | $80,000 | Yes |
| C003 | 680 | 07.10.2021 | $4,800 | $90,000 | No |
| C004 | 690 | 01.05.2022 | $4,500 | $150,000 | Yes |
As the rule in this scenario uses only OR conditions, it’s considered complex, and a standard decision table type must be used.
Advanced Decision Table
A utility company wants to reward residential customers who cut energy use. They are offering financial incentives to customers who use less energy, use energy-efficient technology, or join energy-saving programs.
A customer’s eligibility for the energy-saving incentive is determined by these criteria:
- Condition 1: Energy Consumption Reduction: The customer reduces their energy consumption by at least 15% compared to the previous year.
- Condition 2: Energy-Efficient Technology: The customer has installed an energy-efficient heat pump.
- Condition 3: Participation in Utility Programs: The customer participates in at least one utility energy-saving program, such as a demand response program or time-of-use pricing.
- Condition 4: Annual Energy Usage: The customer uses less than 20,000 kWh annually.
The decision to award the incentive is based on a combination of AND and OR conditions. The decision table condition rule logic for this scenario is 1 AND (2 OR 3) AND 4. To get the energy-saving incentive, a customer must satisfy these conditions:
- 1 and 4
- Either 2 or 3
Review some of the sample customer details based on which the customer’s eligibility is determined. Each criteria is captured as an input condition field and the incentive eligibility output is captured as a result field in the decision table.
| Input | Output | ||||
|---|---|---|---|---|---|
| Customer ID | Energy Reduction <15% (Condition 1) | Installed Heat Pump (Condition 2) | Participated in Utility Program (Condition 3) | Annual Energy Usage < 20,000 kWh (Condition 4) | Incentive Eligibility |
| C001 | Yes | Yes | Yes | Yes | Yes |
| C002 | Yes | No | Yes | Yes | Yes |
| C003 | Yes | Yes | No | Yes | Yes |
| C004 | No | Yes | Yes | Yes | No |
| C005 | Yes | No | Yes | No | No |
As the rule in this scenario uses a combination of AND and OR conditions, it’s considered simple, and an advanced decision table type must be used.
Advanced Decision Table
A health insurance company wants to offer a wellness incentive to customers who meet specific health criteria. The eligibility for the wellness incentive is determined by these criteria:
- Condition 1: The customer has completed an annual health check-up.
- Condition 2: The customer has a BMI (Body Mass Index) within the healthy range (18.5 - 24.9).
- Condition 3: The customer participates in a fitness program.
- Condition 4: The customer has a non-smoker status.
The customer must have completed an annual health check-up, and must either have a BMI within the healthy range, or participate in a fitness program, or be a non-smoker.
The decision to award the wellness incentive is based on a combination of AND and OR conditions. The decision table condition rule logic for this scenario is 1 AND (2 OR (3 OR 4)).
Review some of the sample customer details based on which the customer’s eligibility is determined. Each criterion is captured as an input condition field and the incentive eligibility output is captured as a result field in the decision table.
| Input | Output | ||||
|---|---|---|---|---|---|
| Customer ID | Annual Health Check-up (Condition 1) | BMI within Healthy Range (Condition 2) | Participates in Fitness Program (Condition 3) | Non-Smoker Status (Condition 4) | Wellness Incentive Eligibility |
| C001 | Yes | Yes | No | Yes | Yes |
| C002 | Yes | No | Yes | No | Yes |
| C003 | Yes | No | No | Yes | Yes |
| C004 | Yes | Yes | Yes | No | Yes |
| C005 | No | Yes | Yes | Yes | No |
As the rule in this scenario uses a combination of AND and OR conditions, and at least one input column is required and uses the Equals operator, it’s considered simple, and an advanced decision table type must be used.

