Have you received a discount from your favorite clothing brand? Business rules were probably involved in the decision-making process. Often brands set business rules that award discounts every time a certain value is reached by the customer. But who defines and executes rules in a company? Basically, who rules the rules?
What are business rules?
Business rules play a crucial role in companies’ operations and processes, as they guide the everyday decision-making within the business. They express business goals, guidelines, regulations, performance requirements, etc. while automating processes.
A rule can be formulated to indicate a particular course of action to be followed under specific circumstances or to prevent certain actions from happening.
For instance, e-commerce analysts can set business rules to apply customer discounts or for pricing optimization, while financial institutions employ them to improve decision-making for risk management: they suggest to bank clerks whether a loan should be granted or not.
Moreover, business rules streamline operations. They can be set to conditionally process documents and invoices or to route customer service calls.
Business rules keep things going while helping maintain consistency across the organization.
Business rule engines: who rules the rules
Translating activities into concrete business logic is a great deal for companies in terms of efficiency and accuracy, as business rules reduce manual data entry, lowering the risk of potential errors, while automating repetitive tasks.
But who executes business rules, especially in complex environments where multiple constraints are involved?
That’s where business rule engines (BREs) come in.
A business rule engine is a piece of software that runs the rules on the provided business data, and if any condition
matches then it executes the corresponding actions, automatically responding to real-time situations.
Most rule engines, like Rulex Platform, don’t do just that. They also define new rules by using machine learning algorithms, integrating the existing rules provided by business experts.
Heuristic rules vs AI-generated rules
Heuristic rules are those that have been extrapolated from personal experience. Industry experts
define the decision logic after a careful analysis of historical data. They may compare new and old data patterns,
monitor new and real-time data, make assumptions to fill in the gaps, and then come up with a set of business
rules to apply to the business process.
AI-generated rules, on the other hand, are extrapolated by machine learning algorithms starting from the historical data of the business. In Rulex Factory, the heart of Rulex Platform, for example, these types of rules take the form of an if-then expression.
These two different types of rules can be merged together in the decision process, to achieve the best possible outcome.
How to manage business rules in Rulex Factory
Let’s take a look at how Rulex Factory manages business rules.
As business rules often have many dependencies, constraints, and mathematical formulas, Rulex has developed a
simple syntax that enables non-technical users to express these rules in a simple tabular format, such as an MS Excel file. With a simple drag and drop, you can then import the file into Rulex Factory and apply it to your business data.
If you have very simple rules, there is an even quicker way of managing rules. Once you have dragged and dropped
your data onto Rulex Factory’s canvas, just connect a Rule Manager task. This user-friendly task enables you to apply any pre-defined business rules to your data in a simple if-then format.
In the example, we added the business rule that defined which transport to use depending on the weather and working mode:
Weather = Sunny AND Smart Working = No, THEN Transport = Bicycle
There are two conditions, weather and smart working, which define the output, bicycle.
How to create business rules in Rulex Factory
Manually extrapolating the best rules from historical data is not always an easy task. However, specific algorithms
can analyze the data and generate business rules for us.
In Rulex Factory, we use the Logic Learning Machine (LLM), Rulex’s proprietary algorithm that produces clear and understandable if-then rules.
No technical expertise is required, and business users can create rules using the LLM with ease and confidence.
In the example, we connected the LLM task to our data, selected the attributes we want to use as input (e.g. weather conditions and working mode) and those that represent the output of the analysis (e.g. suggested method of transport), and computed the flow. By connecting a Rule Manager task to the LLM task, we can then easily check the AI-generated rules.
All the benefits of business rules engines
Rulex Factory is used every day by large-scale supply chains and financial institutions, and these are some of the main advantages pointed out by our clients:
- Improved efficiency: Programming business rules into workflows saves lots of time by automating tasks.
- Reduced complexity: Business rules are represented in simplified formats (if-then) that do not require coding skills.
- Increased consistency: Updates to business rules can be immediately applied without modifying the software code.
- Enhanced compliance: It makes it easy for businesses to comply with industry regulations and GDPR.
- Boost business agility: Enabling faster changes makes it possible to react more quickly to new opportunities.
Free overview course on Rulex Factory business rules engine
If you want to learn more about managing business rules, you can follow our introductory course “Creating Rules in Rulex Factory”. The course provides an overview of handling rules, and is completely free, you just need to sign up to Rulex Community.
