What are business rules in database design?

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. 

Business rules vs. business requirements  

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.

Types of business rules

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:

• Constraint rules set conditions that place restrictions on object structures. This can be further broken down into three different subsets of rules, which include stimulus and response, operation constraints, and structure constraints. Stimulus and response rules require conditions to be true prior to an action being taken while operation constraint rules places restrictions before and after a given operation. Finally, structure constraint rules establish policies around classes, objects and the relationships between them that should not be disregarded.
  
  
• Derivation rules define conditions under which facts can be inferred from other information. These rules are broken out into two subsets, which include inference rules and computation rules. Inference rules specify that if certain facts are true, a particular conclusion can be determined, while computation rules utilize algorithms to make these inferences. 

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.

Examples of business rules

Business rules are used for a variety of use cases, which can be based on either internal or external constraints. Some of these include:

• Compliance: Regulatory agencies can apply strict rules around a variety of verticals, such as finance, insurance, healthcare, and marketing. Business rules can help ensure that any documents that are reviewed by any regulatory bodies meet their respective requirements. 
  
  
• Application Approval: Banking and real estate markets leverage business rules for application processes for housing loans or rental properties. For example, an organization may reject an applicant if their credit score is under a specific threshold. 
  
  
• Subscription Services: Companies can leverage business rules to terminate their services to a specific client if payment is not received within a set number of days. This ensures that the company does not waste resources on a customer that is not generating revenue. 
  
  
• Purchase Orders and Returns: Business rules can also be applied within the retail industry. For example, a business can reject a customer's return claim for a given product if it falls outside of a 30 day window.
  
  
• Personalization: Marketing automation tools allow companies to customize their website based on the visitor attributes, allowing marketers to leverage a set of business rules to message across different audience segments. For example, if you're a returning visitor to a website, the business may serve you photos of the product category that you last looked at on their homepage whereas a new visitor may be served images of the company's most popular product.

Benefits of business rules

Business rules can yield a number of benefits to organizations, which streamline business operations and subsequently reduce overhead. 

• Increased efficiency: Programming business rules into applications and workflows can save time in the long term. When business rules need to be updated due to changes into regulations or company standards, only this aspect of the program needs to be updated instead of manual updates throughout a software application. These updates can usually be handled by less technical resources, like business analysts, saving technical resources for more complex business problems. 
  
  
• Improved consistency: Business rules ensure that tasks are executed consistently as specific criteria needs to be met in order for a given task to be executed. For example, regulatory agencies may require the completion of certain documents. Companies can create custom templates which will not be marked as complete until all required fields have been met. As a result, less human error occurs and if all business rules have been implemented accurately, leaders can rest assured that they're meeting compliance requirements, avoiding any unnecessary fees and penalties. 
  
  
• Less complexity: Documentation of business rules can potentially translate to other lines of business, and teams can potentially repurpose documents for other workstreams, reducing complexity across the organization as a whole.  

Process mining and other business analysis can help identify areas where business rules can be applied within your company to capitalize on these benefits. 

Business rules engines and business rules management systems (BRMSs)

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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