Digital first is already a business model most companies follow, and hyperautomation is becoming the next step in enterprise digital transformation. However, companies must establish robust decision management practices to optimize human decision-making and achieve decision automation to automate as many business processes as possible.
Business rules are integral to decision management, and this article explores their importance, types, examples, and best practices for incorporating them into your business processes.
What are business rules?
A business rule is an instruction or a directive that describes, defines, or restricts how a certain business activity or task should be performed. Such rules assist employees in business decision-making under specific conditions. They’re often expressed with conditional logic statements such as “If-then”, “When”, “Only if”, “If-else”, etc.
For instance, “If a product’s stock level reaches the minimum stock level, then reorder the product” is a business rule. As you can see, business rules already exist in every business environment, whether or not they are formally defined and written down. However, formally defining and collecting these business rules provides several benefits as we’ll discuss below.
Why are business rules important?
Converting business activities into business logic by establishing and documenting business rules provides the following benefits:
It paves the way for process automation
Business rules formally defined with conditional statements can be incorporated into process automation systems. An automation system, such as an RPA or an intelligent automation bot, can use these rules to take action when it comes to a point where it needs to make a decision in order to continue the workflow.
It helps capture unwritten / tribal knowledge
Employees spend 3.6 hours searching for information every day, and 31% of them feel burned out because they cannot find the necessary information. Tribal knowledge, also called hidden knowledge, is one of the reasons for this problem. It’s the knowledge needed to accomplish a task but not documented and only known by certain individuals within an organization.
If undocumented, tribal knowledge leads to inefficiencies, errors, and poor employee experiences. Business rules ensure that all the knowledge of subject matter experts is captured and shared across the organization.
It improves decision-making
Business rules ensure employees know how to perform specific business activities and enable them to make better and more consistent decisions. For instance, an operations manager of a telco company can make accurate and timely decisions once the firm applies business rules to operator-alarm categorization.
It aligns individual actions with broader business strategy
It is estimated that 80% of the performance differences between organizations are due to their level of strategic alignment. Companies can use business rules to determine how individual actions can contribute to their overall business strategy and ensure that each action is aligned with it.
It saves time, reduces errors, and increases efficiency
Whether or not they are combined with automation tools, business rules increase overall productivity as they predetermine who will do what, when, and how. When combined with automation technologies and redesigned processes, it can reduce operational costs by 30%.
Types of business rules
Different sources categorize business rules in different groups, but it’s common to classify them as constraint rules and derivation rules, both having several subcategories:1
Constraint rules, as the name suggests, specify conditions that restrict behavior. There are three types of constraint rules:
- Stimulus and response rules define the action to be taken (response) based on a specific condition (stimulus). For instance, the example above regarding the stock level of a product is a stimulus and response rule which specifies a response (reorder) based on a stimulus (inventory level reaches the minimum).
- Operation constraint rules specify the conditions that must hold both before and after an operation. For instance, “An employee can achieve the senior title only if they have worked for the company for at least three years. They are then eligible to receive a yearly bonus” is an operation constraint rule that defines the precondition and postcondition of an operation.
- Structure constraint rules specify the conditions that cannot be violated in any case. For example, “The number of employees in the sales team cannot be greater than 10” is a structure constraint rule.
Derivation rules specify conditions for deriving or inferring facts from other information. There are two types of derivation rules:
- Inference rules specify that a particular conclusion can be drawn if certain conditions are met. For instance, “Bank accounts that haven’t been used for two years are considered dormant accounts and treated as such” is an inference rule.
- Computation rules are similar to inference rules but they use a computational algorithm to make the inference. For instance, “An applicant is considered loan eligible if their credit score is above the threshold” is a computational rule where the system can compute the applicant’s credit score using other data.
This is only one way to categorize business rules. Different categories can be used by different companies according to their needs, and certain business rules may not fit into any of these categories. For instance, business rules may include definitions of fundamental business terms that are used in other rules. So, this classification should be considered a guideline rather than a strict classification.
Examples of business rules
Some examples of business rules include:
- Insurance underwriting: A business rule can be employed to determine whether the applicant is eligible based on specified criteria and calculate the premium based on other business rules.
- Lead qualification: Leads can be qualified or unqualified based on a set of business rules, and then qualified leads can be contacted based on other business rules.
- Customer discounts: Marketing teams can offer customers discounts based on business rules such as “If a customer spends more than $5,000 within a year, then offer a 25% discount on their next purchase.”
These are just a few examples. For more, check our comprehensive article on different examples of business rules.
Incorporating business rules into your processes
Business rules can be defined manually for each business process and then hard-coded into these processes for automation. However, like any other manual process, manual business rules management:
- Is not scalable, as you’ll have to manage many interrelated business rules as your company grows.
- Slows the pace of change in your company because when you hard-code business rules into your business process, you have to rely on technical staff to update them.
A more agile approach is to use a decision management tool such as a business rules management system (BRMS). A BRMS:
- Helps organizations define, implement, manage, monitor, store, update, and automate business rules across their organization from a central platform.
- Enables non-technical users to create and implement business rules.
- Provides a business rules engine that allows other enterprise applications to access business rules and execute them when necessary.
These features make a BRMS an integral part of enterprise-wide automation initiatives.
If you have other questions about business rules or want to get started with business rules management systems, we can help:
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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