Every business process, from fulfilling customer orders to developing new software, comprises a series of decisions. Business rules are the logical guidelines that ensure those business decisions lead to the right outcomes. Business rules dictate what business activity should occur under which circumstances.

A formal business rule is composed of two fundamental elements:

1. A condition, which outlines the situation in which action should occur.
2. An action, which defines the thing that should happen in response to a given condition.

Consider the example of a customer asking to return a product. The business rules determining how the return will be processed might look like this:

Scenario 1:

• Condition: It has been 30 days or less since the customer ordered the product.
• Action: Offer the customer a full refund.

Scenario 2:

• Condition: It has been more than 30 days since the customer ordered the product.
• Action: Offer the customer store credit.

Defining formal business rules allows companies to automate business decisions by creating a coherent system of decision logic that can be applied across business processes. Formally defined business rules tell automated workflows what to do in any given situation (e.g., when to start a process, when to stop a process and when to take certain actions within the process).

Formalizing business rules isn’t always easy. Even simple situations, like a customer return, require multiple business rules to account for the various factors that can influence the final outcome. The complexity of decision logic only increases in highly regulated industries like healthcare and finance. The decisions that go into processing a customer’s loan application, for example, are subject not only to the business’s criteria but also to a host of regulatory requirements to prevent discrimination, fraud and other illegal outcomes.

A business rules management system (BRMS) provides business users with the technology tools necessary to codify business rules in a repeatable, reliable, and automatable manner.

Business rules management — not to be confused with business process management (BPM) — refers to the process and practice of formally defining business rules, implementing them, managing them and automating their deployment. A business rules management system (BRMS) is the technology platform through which this process is carried out. A BRMS offers tools to facilitate the entire business rules lifecycle, from defining and storing rules as formal business logic to auditing existing rules and managing the overarching decision logic that guides automation across the entire enterprise technology ecosystem.

The primary advantage of a BRMS for automation efforts is that rules don’t have to be separately coded into each business application. Instead, a BRMS allows the enterprise to maintain a single source of business rules — either on-premises or in the cloud. Other applications in the technology ecosystem can simply draw their rules from the BRMS. This makes business rules truly scalable — they only have to be created once, and any department or workflow can use them.

A BRMS typically consists of three distinct but interconnected components:

1. A development environment for defining and creating business rules

For business rules to be readable by automated applications, they must be expressed in terms of conditional programming language. Think of the formal logic qualifiers used in coding projects: “IF-THEN”, “IF-ELSE”, “ONLY IF”, “WHEN”, etc.

A BRMS contains a low-code or no-code development environment so that non-technical business people can author business rules in this conditional language. Consider again the customer refund request outlined above. The conditional expression of the rule governing that process might look something like this:

IF it has been less than 30 days since the customer ordered a product, THEN refund the product. ELSE, offer store credit.

Business rules can also be expressed as decision tables, which are useful when crafting rules in which more than one condition influences the proper action. For example, if item pricing also influences the return procedure, a business user might prepare a decision table that looks like this:

Many BRMSs also include the ability to simulate rules so that team members can test rules to see how they might affect decision outcomes. For example, if adding a new rule to a loan approval process requiring a credit score of 700 or above, a team member could see how that rule would change the approval rate before actually implementing it.

2. A repository where rules are stored

After rules are defined, they are placed in the BRMS’s central repository. Here, rules can be reviewed, edited, shared across the entire enterprise and accessed by different applications.

3. A business rules engine

The rules engine is the software component that allows other applications across the enterprise ecosystem to access the rules repository and execute those rules in a runtime environment. The application sends a request — including all the relevant data the rules engine needs to make a decision — to the BRMS. The rules engine then checks the request against the relevant rules and returns a decision. Finally, this decision triggers the application to take some specific action.

Consider the example of a SaaS company that provides three different tiers of subscriptions to its platform: one for small businesses, one for medium-sized businesses and one for large enterprises. When new leads come in through the company’s website, the company wants to automatically funnel those leads to the appropriate sales team, based on the size of the lead’s organization. The company could create a decision service to govern this process in a BRMS like so:

1. The SaaS company would begin by authoring rules within the BRMS development environment to outline how leads should be distributed:
   • IF a lead has under 100 employees, THEN direct the lead to the small business sales team.
   • IF a lead has between 100 and 1000 employees, THEN direct the lead to the medium-sized business sales team.
   • IF a lead has more than 1000 employees, THEN direct the lead to the enterprise sales team.
2. Once the rules are drafted, they’ll be contained within the repository. All the applications involved in the lead allocation process — such as document processing systems, customer relationship management (CRM) systems and robotic process automation (RPA) bots — can access the rules in this repository.
3. When a lead comes in, the RPA bots responsible for copying lead information into the CRM can check with the rules engine to determine how to assign the lead. The RPA bots would send the rules engine information about company size from the lead capture form, and the rules engine would use this information to return a decision in real time. Based on the decision provided by the rules engine, the RPA bots would assign the leads to either the small, medium or enterprise sales teams within the CRM.

With a BRMS, rules are stored in a central repository separate from application codes. The repository creates a single source of truth for business rules that can be accessed by all applications across the enterprise. As a result, business rules are scalable, and business decisions are kept up to date, consistent and reliable at all times.

• Efficient automation: BRMSs are essential to the efficient automation of enterprise workflows. Multiple workflows can be automated using a single repository of company-wide decision logic. That way, IT does not have to write different decision logic programming for each application.
• More consistent outcomes: When business decisions are automated according to a set system of enterprise-wide business rules, all decisions are made according to the same logic. This leads to more consistent outcomes, as business decisions will no longer be influenced by human discretion except when necessary.
• Reduced complexity: When faced with business decisions, human workers don’t have to weigh multiple factors or ensure they’re following every rule. Instead, applications can check with the BRMS, which uses the business rules database to determine the proper outcome. Decisions happen faster, and employees are freed up to do more high-value work.
• Reduced dependency on IT: No-code tools in the BRMS allow business analysts and other non-technical workers to create business rules using their own business vocabulary. That means teams can create and adjust rules as needed and don’t need to get IT involved in every update.
• More responsive decisions: Rules can be updated easily within the BRMS repository because managing rules does not require changing the code of existing applications. Therefore, rules can be readily changed in response to new regulations, market developments, customer demand and other factors.
• Automated compliance: Relevant policies and regulations can be embedded within business rules, ensuring that automated decision-makers follow all relevant laws and guidelines. This also creates an audit trail, as the rules leading to any given business decision can always be reviewed.
• Better business rules overall: Thanks to the ability to run predictive simulations of rules before implementing them, teams can ensure the business rules they create have the outcomes they want before implementation occurs.

BRMSs can be used to automate most, if not all, business decisions across a variety of industries and departments. A few common examples of BRMS use cases include the following:

• Allocating critical resources: The UK National Health Service Blood and Transplant used a BRMS to automate decisions about allocating organ transplants. When an organ becomes available, the BRMS triggers certain workflows to find the next recipient on the transplant list and make a match between organ and patient.
• Reviewing applications: The PNC Financial Services Group used a BRMS to automate the loan application process, creating a set of rules to govern whether applications are accepted or rejected. Employees used to review all loans, but they now only have to review 10-20%, resulting in faster, more reliable and more compliant loan decisions.
• Maintaining compliance: As an e-commerce organization in a highly regulated industry, Brownells Inc., uses a BRMS to automate compliance. The company ensures customers can only purchase products available in their geography by using a system of rules based on where a customer is located.
• Communicating with customers: Panalpina World Transport used a BRMS to help automate shipping updates to customers. Customer information is automatically uploaded to Panalpina’s database, and business rules help determine when to trigger messages to customers.

Intelligently automating business processes of any kind requires first defining a set of clear business rules to govern automated decision-making. A powerful BRMS like the IBM Operational Decision Manager (ODM) gives enterprises the tools they need to develop, store, manage and implement business rules across the entire technology ecosystem.

IBM ODM is a comprehensive decision management solution that enables enterprises to discover, capture, analyze, automate and govern business rules with precision in today’s complex computing environments. The solution can authorize a loan, decide on promotional offers or detect a cross-sell opportunity with high precision and customization. With IBM ODM, teams can add or update new rules at any time using no-code tools, and they can simulate rules prior to deployment to ensure maximum efficiency.

Get the IBM Operational Decision Manager as part of IBM Cloud Pak® for Business Automation. Built for any hybrid cloud, IBM Cloud Pak for Business Automation includes the broadest set of AI- and machine-learning-powered automation capabilities in the market, including content services, document processing, decision management, workflow automation, robotic process automation (RPA) and process mining. With actionable AI-generated recommendations, built-in analytics to measure impact and business-friendly tooling to speed innovation, our software has helped clients reduce process completion times by 90%, decrease customer wait times by half, reduce risk and save thousands of work hours that were then reallocated to higher-value work.