Business Rules Applied

Business Rules Applied
Barbara von Halle

Business rules: A formal expression of knowledge or preference, a guidance system for steering behavior (a transaction) in a desired direction. They are the guidance system that influences the collective behavior of an organization's people and information systems.
Business rules system: An automated system in which the rules are separated, logically and physically, from other aspects of the system and shared across data stores, user interfaces, and perhaps applications.
Business rules approach: Focusing on the "thinking" or decision-making capacity of the organization. A formal way of managing and automating an organization's business rules so that the business behaves and evolves as its leaders intend.
Business event: An activity in the business environment (external to the system) that requires a response from the system. Can include the simple passage of time.

Business event	Business decisions	Rules
Customer agent requests order for product	Is customer known? Is product known? Is product available? Is product low on inventory?	If customer id exists, then customer is known. If customer is preferred and quantity exists on shelf, then product is available. If customer is not preferred and quantity+10 exists on shelf, then product is available. If quantity on hand < reorder quantity, then product is low on inventory. If product is low on inventory, then reorder product.

Chapters

The need for a business rules approach
Business rules concepts
Introduction to business rule methodology
Scoping for success
Project planning with business rules
Discovering initial requirements
Discovering rules and data
Discovering rules through facilitated sessions
Analyzing data
Analyzing rules
Analyzing process
Designing for a business rules approach
Implementing business rule systems using data-change-oriented rules products
Implementing business rule systems using service-oriented products
Rule management

Chapter 7 - Discovering rules and data

Identify rule sources
Select a rule discovery roadmap
Select or confirm rule standards
Plan rule discovery time and commitment
Discover rules though the roadmap
Authenticate the rules
Give rules business value
Define terms
Define facts
Begin a term/fact model
Add concrete scenarios

Chapter 9 - Analyzing data

Identify candidate entities
Determine relationships among entities
Identify primary and alternate keys
Propagate foreign keys
Determine key business rules
Add attributes
Normalize attributes
Analyze relationships
Determine detailed rules
Combine with related logical models
Integrate data models with broader business perspectives
Anticipate the future in the model
Identify rule-created entities
Identify rule-created relationships
Identify rule-created attributes
Correlate rules with the rule-enriched logical data model

Chapter 10 - Analyzing rules

Make each rule atomic
Understand the underlying rule patterns
Remove redundant rules
Resolve overlaps among rules
Resolve inconsistencies among rules
Ensure completeness among rules
Identify dependencies among rules
Refine the process based on rule family dependencies or data activities
Optimize the rules for the business

Chapter 11 - Analyzing process

Uncover and expand a preliminary core process flow
Assign decisions and rules to the rules capability
Confirm the essential core process flow
Consider alternative core process flows
Create a simple workflow diagram to show maximum concurrency for the core process flow
Finalize the preferred core process flow
Create a simple workflow diagram for the core process flow
Revise core workflow diagram using concrete scenarios
Reference business context (again!)
Confirm the core workflow diagrams
Study important state transitions
Round out all tracks
Create other process analysis deliverables for the core process flow
Create a workflow diagram for the rule flow, if necessary

The book's core value system

STEP principles	Purpose of the principle
Separate rules	To reuse rules To apply special techniques to optimize rule quality To change rules independently of other system aspects
Trace rules	To determins, over time, if the rule remains a correct rule for guiding the business To access the impact of rule changes
Externalize rules	To allow everyone to know where rules can be known To allow everyone to know what the rules are To allow everyone to challenge the rules
Position rules for change	To enable easy rule changes To enable quick rule changes

The book's classification scheme

Business rule classification	Definition	Example
term	A noun or noun phrase with an agreed upon definition.	Customer credit rating code
fact	A statement that connects terms, through prepositions and verbs, into sensible business-relevant observations.	Customer can place order.
mandatory constraint	A complete statement that expresses an unconditional circumstance that must be true or not true for the business event to complete with integrity.	A customer must not have more that 10 open orders at one time.
guideline	A complete statement that expresses a warning about a curcumstance that should be true or not true.	A customer should not have more that 10 open orders at one time.
action enabler	A complete statement that tests conditions and upon finding them true, initiates another business event, message, or other activity.	If a customer order is valid, then initiate the Place Order business event.
computation	A complete statement that provides an algorithm for arriving at the value of a term where such algorithms may include sum, difference, product, quotient, count, maximum, minimum, average.	The total-amount-due for an order is computed as the sum of the line-item amount(s) for the order plus tax.
inference	A complete statement that tests conditions and upon finding them true, establishes the truth of a new fact.	If a customer has no outstanding invoices, then the customer is of preferred status.

"All business rules are about data." [p37]

Terms define data concepts and details.
Facts define associations among data.
Guidelines and Constraints test data values.
Computations arrive at a data value.
Inferences arrive at a data conclusion.
Action Enablers evaluate data values prior to initiating action.

"Business rules create information, called knowledge. Each atomic rule creates only one piece of new information or knowledge." [p207]

A Computation rule creates a value for the computed attribute.
An Inference rule creates an existence of an entity, sets a flag, or sets another attribute value.
A Guideline, Constraint, or Action Enabler creates a truth value. A truth value is a yes or no indicator denoting whether the guideline or constraint is violated, or whether the conditions for action are met.

"Business rules reference pieces of information to determine compliance to a constraint or a guideline, compute a formula, or qualification for an inferred knowledge rule or action-enabler rule." [p206]

This is a business activity

"Business rules are first and foremost for business people." [p187]

"A formal rule stewardship program establishes permanent business people whose job includes rule management." [p184]

"[For terms and facts], the business audience simply needs to identify them and their definitions. The rest (organizing them into entities and attributes of object classes) is the responsibility of analysts or designers." [p205]

"How to" quotes

"Should any piece of information referenced in a rule clause change in value, it is possible that the rule should fire and verify that the database still remains in compliance with business rules or policy." [p39]

"When you discover database action within the scope of the system, classify the corresponding rule as an inference." [p37]

"The methodology in this book provides guidelines for preserving the connection between rules to database activities. If you do not design your object/methods around the attachment of rules to database events, you need to be sure you are not disintegrating the data integrity." [p41]

Notes

"Shared rules and shared data result in shared knowledge. Shared knowledge makes for a smarter learning enterprise." [p25]

"Placing rules as a third design principle between data modeling and workflow concepts." [iii]

The book emphasizes four distinct and concurrent workflows of project execution: the process track, the rule track, the data track, and the technology track.

Commerial products

"The book divides the world of commercial rules technology into two broad categories, which are quite different from each other: data-change-oriented, and service-oriented." [p17]

data-change-oriented rules product: Executes rules when a running application touches data for which rules have been declared. With this approach, as an application attempts to update data, the rules capability watches for conditions that must ne true about the data as well as conditions that should cause a reaction, such as the creation of new data. Versata VLS, and USoft Developer.
service-oriented rules product: Executes rules upon request by a running application, not because the application directly attempted to touch data. In this case, the rules service waits until an application calls on it to apply rules to data. The rules are not bound to data or object structure. Usually, the application passes the data to the rule service. The rules are not bound to data structures. They are free-floating. HNC Blaze Advisor, and ILOG Jrules.

Review

The book does a remarkable job of balancing: process prescriptions, implementation heuristics, a case study demonstration, and commercial product implementations. Given that the holy grail of reuse has suffered more from political and cultural issues than from technical issues, her emphasis on process improvement is a very pragmatic choice. It is clear the author hails from a strong data modeling background, but that does not unduly skew her worldview. On page 30, six competing business rule classification schemes are summarized. The author chooses her own extended subset as the foundation for the book.