Chapter 5 Business Rules and Models Continuation PDF

Chapter 5 Business Rules and Models Continuation Topics Tools to support rule management Tools Repository Repositories and rules engines Tools to support rule management Here are the most important things you should have in your toolkit in relation to b...

Chapter 5 Business Rules and Models Continuation Topics Tools to support rule management Tools Repository Repositories and rules engines Tools to support rule management Here are the most important things you should have in your toolkit in relation to business rules: 1. Modeling tool. Business rules are rooted in business models, so you're going to need an efficient way of modeling your requirements. Some level of UML compatibility is essential, but don't expect UML alone to be the answer. Separation of structure from presentation; the ability to import and to export a range of formats, including XML; and automation capabilities are much more important than are colored icons. 2. Rule definer. You can produce perfectly good rule statements by using nothing more than a simple text editor, but it can become hard work, and it's easy for errors to creep in. A better option is a tool that's specialized for defining rules. In earlier chapters, we  saw some of the basic principles that could be used: controlling rule structures through templates, enforcing references to the fact model, and so on. 3. Logic simulator. It's virtually impossible to check even a moderately complex rule set by eye. We looked at a typical scenario in other chapter and saw how using even a simple spreadsheet could reveal unsuspected features lurking in our rules. Little is available on the market in this specialized area, so you may decide to use something that you already have lying around, even though it's not perfect. 4. Repository. In a large organization, rule populations can run into the thousands, and controlling them with a paper system alone would be well-nigh impossible. A good repository is probably the key tool in rule management. It will contain not only the definitions of every rule but also a number of cross-references and other supporting information. 5. Other management tools. Most of the other tools you'll need will probably already be around because they're a feature of most IT shops. On the development side, these tools include a decent configuration-management tool, or version-control system. On the operations side, such tools as alert detection and log analysis should already be in place. Overall, having a well-equipped toolkit comprising these essential components is critical for effectively managing and implementing business rules within an organization, ensuring consistency, accuracy, and compliance with business requirements. Business rules management Business Rule Management (BRM) refers to the process of capturing, storing, organizing, and managing business rules within an organization. It involves defining, maintaining, and enforcing the rules that govern how business processes are executed and decisions are made. BRM aims to ensure consistency, accuracy, and compliance with business policies, regulations, and objectives across the organization. Key components of business rule management include: 1. Rule Definition: This involves identifying and documenting the specific rules that govern various aspects of business operations, such as pricing, eligibility criteria, approval processes, and compliance requirements. Rules are typically expressed in a clear and unambiguous format that can be easily understood and implemented. 2. Rule Repository: A centralized repository or knowledge base is used to store and organize the business rules. This repository serves as a single source of truth for all rules within the organization, making it easy to access, update, and reference them as needed. 3. Rule Authoring: Business rule authors, often subject matter experts or business analysts, are responsible for creating and maintaining the rules. Authoring tools and platforms may be used to facilitate this process, providing features such as rule templates, validation checks, and version control. 4. Rule Validation and Testing: Before being deployed into production, business rules undergo validation and testing to ensure they function as intended and achieve the desired outcomes. This may involve unit testing, integration testing, and validation against real-world scenarios and data. 5. Rule Execution: Once validated, the business rules are deployed into the organization's systems and processes for execution. Rule engines or rule execution environments are used to automate the evaluation and enforcement of rules in real-time as part of business operations. 6. Rule Monitoring and Maintenance: Business rules are continuously monitored to ensure they remain effective and aligned with evolving business requirements, regulations, and market conditions. Regular maintenance and updates may be required to address changes in rules or underlying business processes. 7. Rule Governance: Rule governance processes and policies are established to manage the lifecycle of business rules, including rule creation, review, approval, deployment, and retirement. Governance helps ensure that rules are managed in a systematic and controlled manner, with appropriate oversight and accountability. Overall, business rule management plays a critical role in enabling organizations to implement and enforce consistent, transparent, and agile decision-making processes across the enterprise. By effectively managing business rules, organizations can improve operational efficiency, reduce risk, enhance compliance, and drive business innovation and agility. Nature of business rules within the organization 1. Decision Management: Business rules are often a fundamental component of decision management systems. Decision management involves automating and improving decision-making processes within an organization by leveraging business rules, analytics, and other technologies. It aims to make decisions more consistent, transparent, and efficient. 2. Business Rules Engines (BRE): Business rules engines are software tools or platforms designed to execute and manage business rules efficiently. These engines provide features such as rule execution, inference, versioning, and monitoring. They are often integrated into larger business process management (BPM) or decision management systems. 3. Rule Interchange Formats: To facilitate interoperability between different rule management systems, various rule interchange formats have been developed. cs. Examples include the Decision Model and Notation (DMN) standard and the Rule Interchange Format (RIF). 4. Rule Mining: Rule mining is the process of automatically discovering business rules from data or existing systems. This technique is particularly useful when dealing with legacy systems or complex datasets where manual rule extraction is impractical. Rule mining algorithms analyze data patterns and correlations to infer implicit rules. 5. Regulatory Compliance: Business rules play a crucial role in ensuring regulatory compliance within organizations. Industries such as finance, healthcare, and telecommunications are subject to numerous regulations and standards. Business rules are used to codify these regulations into automated decision-making processes, helping organizations remain compliant while minimizing the risk of non-compliance penalties. 6. Continuous Improvement: Business rules should not be seen as static entities. They often need to be updated or refined based on changing business requirements, regulations, or market conditions. Continuous improvement practices, such as rule testing, monitoring, and optimization, help ensure that business rules remain effective and aligned with organizational goals. 7. Domain-Specific Rule Languages: In some cases, specialized rule languages are developed to express domain-specific rules more effectively. For example, the Drools rule engine provides a domain-specific language (DSL) for expressing rules in the context of business processes and workflows. 8. Natural Language Processing (NLP): With advancements in natural language processing (NLP) technology, there's growing interest in techniques for automatically extracting and interpreting business rules from unstructured text sources such as contracts, legal documents, and policy manuals. NLP can help streamline the rule discovery process and ensure that no important rules are overlooked. Examples of business rules Let's create a simple example to illustrate both business rules and a business model. Example: Online Retail Store Business Rules: 1. Order Processing Rule: If a customer places an order on the online retail store's website, then the order must be processed within 24 hours. 2. Inventory Rule: If a product is out of stock, then it cannot be added to the customer's shopping cart. 3. Shipping Rule: If the order total is above $50, then shipping is free; otherwise, standard shipping fees apply. 4. Return Policy Rule: If a customer returns a product within 30 days of purchase and it's in its original condition, then a full refund will be issued. 5. Promotion Rule: If a customer enters a valid discount code during checkout, then the discount will be applied to the order subtotal. Creating Business Rules 1. Identify Requirements: Understand the needs and goals of the online retail store, such as ensuring timely order processing, managing inventory effectively, providing a positive customer experience, and maximizing sales through promotions. 2. Analyze Processes: Review existing processes and workflows to identify where rules are needed to govern decision-making and operations. For example, consider the steps involved in order processing, inventory management, shipping, returns, and promotions. 3. Define Rule Logic: For each aspect of the business, define the specific conditions and actions that constitute a rule. Use clear and unambiguous language to express the rules in a format that can be easily understood and implemented. 4. Document Rules: Document the business rules in a structured format, such as a rule repository or knowledge base, to ensure they are accessible to relevant stakeholders and can be easily referenced and updated as needed. 5. Test and Validate: Test the business rules to ensure they function as intended and achieve the desired outcomes. Identify any potential conflicts or inconsistencies between rules and address them accordingly. 6. Implement and Monitor: Implement the business rules within the online retail store's systems and processes. Continuously monitor and evaluate the effectiveness of the rules, making adjustments as necessary to adapt to changing business requirements and market conditions. By creating and implementing these business rules, the online retail store can ensure consistency, efficiency, and compliance with its operational objectives and customer expectations. These rules serve as the guiding principles that govern how the business operates and interacts with its customers. Consider another example in the context of a subscription-based streaming service like Netflix. Example: Subscription-Based Streaming Service Business Rules: 1. User Registration Rule: If a user wants to access the streaming service, they must register for an account using a valid email address and create a password. 2. Subscription Plan Rule: If a user wants to access premium content, they must subscribe to a paid plan. Free trial subscriptions are available for new users for a limited period. 3. Content Availability Rule: If a user searches for a specific movie or TV show, only content available in their subscription plan or region should be displayed. 4. Streaming Quality Rule: If a user's internet connection speed is below a certain threshold, the streaming quality should automatically adjust to ensure smooth playback. 5. User Profile Rule: If a user watches specific genres or types of content, personalized recommendations should be provided based on their viewing history. 6. Payment Rule: If a user's subscription payment fails, they should receive a notification and be prompted to update their payment information to avoid service interruption. 7. Content Licensing Rule: If a license for a particular title expires, it should be removed from the streaming service's catalog until a new license is obtained. Creating Business Rules: 1. Identify Business Objectives: Understand the goals of the streaming service, such as attracting and retaining subscribers, providing a seamless user experience, and complying with content licensing agreements. 2. Analyze User Interactions: Analyze the different touchpoints and interactions users have with the streaming service, including account registration, content browsing, playback, and billing. 3. Define Rule Conditions and Actions: For each aspect of the service, define the conditions that trigger specific actions or decisions. For example, determine the criteria for recommending content, adjusting streaming quality, or handling payment failures. 4. Document Rules: Document the business rules in a centralized repository or knowledge base, ensuring they are accessible to relevant stakeholders, including product managers, developers, and customer support teams. 5. Test and Validate: Test the business rules in a controlled environment to verify they function as intended and achieve the desired outcomes. Address any issues or inconsistencies identified during testing. 6. Implement and Monitor: Implement the business rules within the streaming service's software systems and processes. Continuously monitor user interactions and system performance to identify opportunities for optimization and refinement of the rules. By implementing these business rules, the streaming service can deliver a tailored and reliable experience to its subscribers while efficiently managing content availability, user preferences, and payment processing. These rules serve as the backbone of the service's operations, guiding decision-making and ensuring consistency and compliance with business objectives. If you've adopted a particular rules engine, it may bundle in some tools, and these are the ones you'll probably end up using, however far from ideal they may be. When you're evaluating rules engines, don't forget to include the management tools as part of the assessment. Most organizations will always prefer to buy a product to do a job rather than go to all the trouble and effort of building one themselves. This is usually the right decision because of one simple factor: support. It can sometimes seem strange that you need to go outside to get support for something that's crucial to your organization, but it reflects the economies of scale. Taking a cold-blooded mathematical view of the world, it's obvious. If the cost of supporting a tool is x, then: Support cost for home-brew tool = x * 100% Support cost for purchased tool = x * i/n * 100% where i is an inefficiency factor, taking into account that the vendor needs to make a profit, and n is the number of customers supported. For an in-house tool, i = 1, and n = 1, so they cancel out. For a purchased tool, i is generally much smaller than n, so it's clear that the economics are likely to be better. There's also a simpler existence proof. If doing it inhouse were really cheaper, there wouldn't be any products around. The one area that might be an exception is a rule repository. This is so important that it deserves a separate section. Repositories and Rule Engines If you have a rules engine, it will already provide at least some of the features just listed, so it's reasonable to ask whether you need a rule repository in addition or whether the rules engine alone is sufficient. The answer hangs on what your rules engine does about external rules: rules that it doesn't implement but that nevertheless exist elsewhere in the system. Most rules engines ignore the existence of any other kind of business logic. Unfortunately, you can't afford to do this. A rule repository is a centralized storage system or database where organizations store and manage their business rules. It serves as a single source of truth for all the rules within an organization, providing a structured and organized environment for storing, accessing, and managing rules throughout their lifecycle. However wonderful your rules engine, it's not realistic to put absolutely everything in it. The fact that the do-everything expert systems of the 1980s and 1990s are no longer around in their original form is a testament to the failure of this line of thinking. The plain fact is that you're bound to have some rules for which your only alternative is to locate them outside the rules engine: in a fat client, in a database, in a legacy system, in a workflow tool, or in a number of other places. You can take the attitude that only the rules in the rules engine are proper rules, that all the others can be ignored. But this would be a big mistake. You will lose the ability to check your business logic properly, because chunks of it will be missing. You will not be able to have a rational discussion about whether a rule should be implemented inside the rules engine or outside, if logic outside the rules engine is deemed not to exist. You may be forced into a tortuous realization of a rule or rule set within the rules engine that could have been done in a simpler way outside, just to get some management control. The other possibility is for a rules engine to introduce a little distance between the definition of a rule and its implementation. In principle, this would allow the rules engine to act as the central control point for all rules and the implementation route for some. For rules not implemented internally, the rules engine could provide a place for the user to add information about how the rule had been realized, along with a modicum of additional housekeeping information. Unfortunately, most current products lean toward the closed-world assumption and aren't very adaptable. It's more fruitful to think about this in a different way. You would like to have a rule repository that covers all the angles we described, without being boxed in by what a rules engine allows. So treat yourself and have one! It's not as scary as it sounds, and we'll look at the practicalities shortly. Figure below shows the kind of configuration we want to achieve. Rule definition refers to the process of identifying, articulating, and documenting the specific rules that govern various aspects of business operations. During this phase, organizations establish the guidelines, conditions, and actions that determine how decisions are made and processes are executed within the business. Rule realization refers to the implementation and execution of the defined rules within the business processes and software systems of an organization. It involves translating the abstract rules into executable logic that can be applied to real-world scenarios and decision-making scenarios. But what to do if you also have a rules engine? Won't they conflict? Not if you manage things correctly. The key point to remember is that most rules engines try to combine rule definition and rule realization. You can treat your rules engine as a kind of container that implements rules in a particular way: a superduper container, for sure, much better than a lump of C++ or Java but ultimately just something that contains some rules. Figure below shows the concept. A rule engine is a software component or system that evaluates and executes business rules within an application or system. It provides a framework for defining, organizing, and applying rules to make decisions and automate processes based on specific conditions or criteria. Rule engines are commonly used in various industries and domains, including finance, healthcare, manufacturing, and telecommunications. This is not belittling the rules engine; it's enhancing it. You can still use all its facilities, and you'll probably find it a more comfortable way to implement your rules than most alternatives. But you have to make it a member of your family of realizations. The head of the family is the rule repository, which knows who's related to whom and knows about all the tribal relationships. But not everyone lives with the head of the family; in fact, most members of the family are out living their own lives in their local communities. The wise old repository understands this fact but still keeps lists of addresses and birthdays and a whole load of other things that bind the family members together. What if you don't have a rules engine? It's not a problem. Contrary to what some vendors will tell you, rules can and do exist without their products. You can think of the repository as a "virtual rules engine," with the implementation aspects federated out to a number of separate resource providers. You can choose the providers and the way that they realize the rules, and you can make a different choice whenever you want to.