Business rules guide the everyday decision-making within businesses by outlining the relationships between objects, such as customer names and their corresponding orders. This translation of an organization's business activities into concrete business logic allows software engineers and business analysts to apply these rules within workflow tools or other applications to enable process automation. Without them, updating processes can become more arduous and time-consuming, and documents can be subject to more human error and inconsistencies. By implementing business rules across an organization, a business can save time and money by streamlining work to the right stakeholders and reducing churn.
Some people can confuse the terms, business rules and business requirements, but they are actually very distinct and different. As a result, it's worth noting how they are used within business settings.
Business rules provide the foundation for automation systems by taking documented or undocumented information and translating it into various conditional statements. For example, when conducting a purchase order, there may be a different approval process depending on the cost. Tools and services that are under five thousand USD may only need manager approval, but as costs get higher, they may require approval by the C-suite. Business rules formalize this process by setting thresholds under which invoices are sent to upper management vs. first line managers. Conditional statements, such as these, are applied across a number of business processes.
Business requirements establish the success criteria for a given project. By specifying the tasks and resources needed to complete the project, teams can more clearly see the gaps and barriers to achieving their goal. This exercise is usually completed at the start of a business project to set expectations among stakeholders and address any additional needs for project completion.
Business rules can be classified in several ways, and they can vary in their classification depending on the source of information. However, irrespective of their categorization business rules are typically expressed using formal logic qualifiers, such as: "IF-THEN", "IF-ELSE", "ONLY IF", "WHEN", et cetera. This syntax is used across the following different types of business rules:
These types of rules are the foundation of rules engines, allowing organizations to automate business decisions to expedite a variety of processes, like customer orders and shipping. They enhance business processes by providing guidance on when these processes should be initiated, stopped or altered in order to enforce policies consistently across the business.
Business rules are used for a variety of use cases, which can be based on either internal or external constraints. Some of these include:
Business rules can yield a number of benefits to organizations, which streamline business operations and subsequently reduce overhead.
Process mining and other business analysis can help identify areas where business rules can be applied within your company to capitalize on these benefits.
To help organizations remain responsive and agile, decision process automation software makes it possible to manage business rules independently from other business computing processes. In particular, business rules management systems (BRMSs) are capable of automating the creation and implementation of business logic in real-time without dependencies on other applications and processes, so that a single repository of decision logic can easily be shared across the entire enterprise.
Common tools for defining and managing the decision logic and a common runtime environment allow both developers and stakeholders with less technical backgrounds to efficiently implement and change automated decision-making processes. They also enable complex rule sets to be enforced consistently across large environments.
A business rules engine transforms one or more business rules into business logic that functions in a runtime production environment. Today, most business rules engines are integrated into full-scale BRMS solutions that can be integrated into services-oriented or microservices-based architectures. Modern BRMSs often employ machine learning or rules-based expert systems to optimize decision-making, improve customer experience and facilitate smoother operations.
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Microservices architecture is an approach in which a single application is composed of many loosely coupled and independently deployable smaller services.