Decision Tables for Smarter Rule Management: Higson Example

Imagine simplifying complex business logic into a clear visual format that both your IT team and business executives can understand at a glance. That’s what decision tables are. In this article we’ll show you how they work, why they’re changing rule management and how Higson is using them in real world scenarios.

You’ll see how decision tables can simplify your operations, improve team collaboration and make your decision-making more efficient, consistent and accurate. Whether you’re dealing with policy pricing, loan approvals or any set of complex business rules, this guide will show you a better way to manage them.

Decision Tables: The Foundation of Clear Business Logic

Decision tables are structured tools that simplify complex business logic into a digestible format. They help with evaluating and executing complex decisions consistently. Decision rules are defined precisely, allowing for efficient analysis of various scenarios.

They consist of rows representing different conditions or scenarios and columns for inputs and outputs. This grid like structure condenses multiple if-then statements into a more manageable format so both technical and non-technical stakeholders can understand complex rule sets at a glance.

In reality a decision table might look like this:

This shows how different conditions (customer type and order total) determine a specific outcome (discount percentage). Decision tables are great at representing complex business logic in a clear and concise way, reducing ambiguity and rule definition errors.

Decision Tables for Business Rules

Clarity and Simplicity

Decision tables are visual, so it’s easier to understand and communicate complex logic. No misinterpretation and everyone is on the same page.

Decision tables make it more efficient to break down complex decisions into smaller sub-decisions. A more structured approach to decision-making tasks.

Completeness and Accuracy

Decision tables find rule gaps. By listing all possible combinations of conditions they ensure no scenarios are missed. Better decision-making.

Flexibility and Scalability

As business needs change, decision tables can be easily changed. New rules can be added by inserting rows, and new conditions by adding columns. Businesses can adapt quickly to changing requirements.

Faster Decision-Making

Decision tables make rule processing and automated decision making faster. When integrated into business rules management systems like Higson they can handle large datasets and complex rule sets. In our tests Higson was 63x faster than the competition.

Easier to Maintain

The structured format of decision tables makes it easier to update and change rules over time. Less chance of out of date or conflicting rules in the system.

Stakeholders

One of the challenges is explaining complex decision models to stakeholders. Using visual representations of decision tables will help stakeholders see and understand the logic more easily and also engage with the decision model creation and implementation.

IT and Business Team Collaboration

Decision tables are a bridge between IT and business teams.

Common Ground

Decision tables provide a shared framework that both IT professionals and business users can understand. This common ground reduces miscommunication.

Business Users Empowered

With their simple format, decision tables allow non-technical users to create decision tables and modify them. This empowers more accurate and relevant business rules as those closest to the business process can influence the decision logic directly.

Simplified Rule Management

By using decision tables the dependency on IT for rule changes is reduced. Business users can propose and sometimes implement changes themselves, speeding up the rule management process.

Better Documentation and Compliance

Decision tables are clear, auditable records of decision-making. This is particularly important in regulated industries like insurance and finance where decision rationales need to be documented and justified.

Faster Iteration and Testing

The structured format of decision tables allows for easier testing and validation of rule changes. This enables quicker iteration and more agile response to business needs.

Higson’s Decision Tables

Higson’s Business Rules Management System (BRMS) uses decision tables to integrate with existing business processes. It is a platform for creating, managing and executing complex decision logic.

Higson’s decision tables stand out in the following ways:

1. Scalability: The system can handle large decision tables with thousands of rows, large datasets are handled efficiently. This is particularly important for insurance companies with many policy types and risk factors.
2. In-memory indexing: Higson uses in-memory indexing techniques for fast lookups and high performance even with complex rule sets. This is essential for real-time decision making in financial transactions.
3. Dynamic rule updates: Decision tables in Higson can be updated on the fly without downtime. This allows insurers and financial institutions to respond quickly to regulatory changes or market conditions.
4. Custom functions: Higson allows custom calculations to be added directly into decision table cells. This enables handling of exceptions or unique cases that standard decision tables can’t cover.

Higson's system allows for different types of decision models, including those that handle default values and complex decision rules. This flexibility enhances its capabilities in managing diverse business scenarios.

Watch our video tutorial too see how it works in practice:

Real-World Applications in Insurance and Finance

Here’s an example of how Higson’s decision tables might be used in an insurance context:

This decision table allows insurers to adjust pricing dynamically based on multiple factors. As market conditions or risk assessments change the table can be updated quickly to reflect new pricing strategies.

In finance, Higson’s decision tables might be used for loan approvals:

This table simplifies the loan approval process and ensures lending criteria is applied consistently across all applications.

Best Practices for Decision Tables

When defining decision tables, it's crucial to identify the key elements that drive the decision-making process. This often involves conducting a gap analysis to ensure all relevant factors are considered.

To get the most out of Higson’s decision tables:

1. Design:
   • Define the decision problem clearly.
   • List all conditions and actions.
   • Order conditions from most to least discriminatory to optimize performance.
   • Use consistent naming conventions for clarity.
2. Maintenance and Updates:
   • Review and validate decision tables regularly to ensure they reflect current business rules.
   • Document the reasoning behind rule changes for future reference.
   • Implement version control to track changes over time.
   • Test thoroughly after any changes to prevent unintended consequences.
3. Training and Adoption:
   • Train technical and business users fully.
   • Start with simple decision tables and gradually add more complex scenarios.
   • Involve IT and business teams during creation and update of decision tables.
   • Show early wins to build confidence in the system.

Future of Decision Tables in Business Rule Management

The use of decision tables in business rule management will grow due to:

1. Artificial Intelligence: Future versions of decision table systems may include AI to suggest the best rule configuration based on historical data and outcomes.
2. Better Visualization: Advanced visualization techniques will make complex decision tables even more intuitive and potentially include interactive elements to navigate large rule sets.
3. Real-time Collaboration: Cloud-based decision table platforms will allow simultaneous editing and real-time collaboration across geographically dispersed teams.
4. Regulatory Compliance: As regulations get more complex decision tables will be even more critical in financial and insurance industries to ensure and demonstrate compliance. 

Future developments may focus on enhancing the ability to handle increasingly complex decisions, potentially incorporating advanced analysis techniques to optimize decision rules.

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