Can you understand that all three of the following business rule statements mean the same thing? Here’s what must be true: If you mow the lawn on Sunday your lawn mower is to be electric; otherwise the lawn is not to be mowed on Sunday.

1. It is permitted that the lawn be mowed on Sunday only if the lawn mower is electric.

2. It is prohibited that the lawn is mowed on Sunday if the lawn mower is not electric.

3. It is obligatory that the lawn not be mowed on Sunday if the lawn mower is not electric.

I’m fairly certain you can. And if you can determine they all mean the same thing, I contend a machine ought to be able to do so too. I mean as stated in this exact same human-friendly, structured natural language form. And tell you that the statements mean the same thing (in effect, that they are redundant). That’s the kind of language-smart (cognitive) capability that business innovators should be expecting – no, demanding – from software vendors.

P.S. In the OMG standard Semantics of Business Vocabulary and Business Rules (SBVR) the three statements are a restricted permission statement, a prohibition statement, and an obligation statement, respectively. You might prefer one or another of these forms of statements, but each is correct and reasonably understandable. Here are the RuleSpeak^©[1] equivalents – even more friendly:

1. The lawn may be mowed on Sunday only if the lawn mower is electric.
   
   
2. The lawn must not be mowed on Sunday if the lawn mower is not electric.
   
   
3. (same as 2)

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Get trained: Instructor-led, online, interactive training: April 4-6, 2017 – Business Analysis with Business Rules: From Strategy to Requirements. http://www.brsolutions.com/services/online/strategy-to-requirements/

©Business Rule Solutions, LLC 2017. www.BRSolutions.com

[1] Free on www.RuleSpeak.com

How does legality work with business rules? To say that differently how should an intelligent tool work so as to help you establish the business regimen you want to follow where legality is involved? Consider the example of Same-Sex Marriage. Let’s suppose you want to make it illegal. SBVR[1] does not have an innate concept/approach for “legality” in the sense of MWUD[2] 1: attachment to or observance of law. So if you wanted “is legal” in the most direct sense, you must define a unary verb concept for the concept Same-Sex Marriage. In a looser sense, if you are in an organization (business) with the standing to define business rules, you could do several things, as follows. (I’ll make up a bit of vocabulary here.) 1. Specify a behavioral rule A behavioral rule is one that can be potentially violated by people or organizations. The relevant rule might be expressed as follows:

The people united in a marriage must not be of the same gender.

Then you would decide how strictly you want to enforce the rule. Options range from strictly enforced to guideline. The rule would be active when a relevant state of affairs arose (i.e., specific people get married). 2. Define several definitional rules A definitional rule is one that cannot be violated; it exists to ensure the consistency of the concept system you chose to follow. Relevant definitional rules might be expressed as follows:

• The people united in a marriage are not to be of the same gender.
• The people united in a same-sex marriage are to be of the same gender.

See the conflict? Your friendly intelligent tool would (immediately) disallow one or the other specification. The rules are clearly in conflict; the logical conflict would simply not be allowed to stand. 3. Define the relevant definitions

• Marriage: the uniting of people of different genders in wedlock
• Same-Sex Marriage:  the uniting of people of the same gender in wedlock

Again, your friendly intelligent tool would (immediately) disallow one or the other specifications. The definitions are clearly in conflict; the logical conflict would simply not be allowed to stand. Actually, under the covers, approaches 2 and 3 work exactly the same way In SBVR. SBVR recognized that some people prefer to do things via rules, some with definitions, and if truth be told, most times you will do some of both. ~~~~~~~~~ www.BRSolutions.com    

The standard Semantics of Business Vocabulary and Business Rules (SBVR)[1] offers fundamental insights about how to express business rules well. These common-sense insights can and should directly inform all expression of business rules – and any language that purports to support them. The first of these insights is the notion of practicable, which I discussed in my previous post. See: http://www.brsolutions.com/2015/06/29/practicable-insight-for-expressing-business-rules-well/ The second of these insights is the principle of wholeness. The descriptive text below is taken directly from SBVR itself.[2]Wholeness essentially means each business rule statement can be taken as fully trustworthy even in isolation from all other rules. The principle precludes priority schemes and rules that disable other rules, both of which can act to make any given rule less than fully trustworthy. ~~~~~~~~~~~~~~~~~~~                          Principle: An element of guidance means only exactly what it says, so it must say everything it means. Explanation: Each element of guidance must be self-contained; that is, no need to appeal to any other element(s) of guidance should ever arise in understanding the full meaning of a given element of guidance. The full impact of an element of guidance for a body of shared guidance, of course, cannot be understood in isolation. For example, an element of guidance might be in conflict with another element of guidance, or act as an authorization in the body of shared guidance. The Wholeness Principle simply means that if a body of shared guidance is deemed free of conflicts, then with respect to guidance, the full meaning of each element of guidance does not require examination of any other element of guidance. In other words, each element of guidance can be taken at face value for whatever it says. ~~~~~~~~~~~~~~~~~~~~~~~~ www.BRSolutions.com

The standard Semantics of Business Vocabulary and Business Rules (SBVR)[1] offers fundamental insights about how to express business rules well. These common-sense insights can and should directly inform all expression of business rules – and any language that purports to support them. The first of these insights is the notion of practicable. The descriptive text below is taken directly from SBVR itself.[2]Practicable essentially means all ambiguity has been resolved. As a result, a practicable business rule can be given either to workers to apply ‘manually’, or to IT to implement under some platform, and the results will be exactly the same either way (barring human error or malfeasance). ~~~~~~~~~~~~~~~~~~~~~~~~~~ Definition: the element of guidance is sufficiently detailed and precise that a person who knows the element of guidance can apply it effectively and consistently in relevant circumstances to know what behavior is acceptable or not, or how something is understood Dictionary Basis: able to be done or put into practice successfully; able to be used, useful [Oxford Dictionary of English] Notes:

• The sense intended is: “It’s actually something you can put to use or apply.”
• The behavior, decision, or calculation can be that person’s own.
• Whether or not some element of guidance is practicable is decided with respect to what a person with legitimate need can understand from it.
  • For a behavioral rule, this understanding is about the behavior of people and what form compliant behavior takes.
  • For a definitional rule, this understanding is about how evaluation of the criteria vested in the rule always produces some certain outcome(s) for a decision or calculation as opposed to others.
• A practicable business rule is also always free of any indefinite reference to people (e.g., “you,” “me”), places (e.g., “here”), and time (e.g., “now”). By that means, if the person is displaced in place and/or time from the author(s) of the business rule, the person can read it and still fully understand it, without (a) assistance from any machine (e.g., to “tell” time), and (b) external clarification.

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OMG released version 1.3 of SBVR (Semantics of Business Vocabulary and Business Rules)[1] last month – comprehensively reorganized for approachability, but not changed.[2] Some thoughts … ~~~~~~~~~~~~~~~~~ Ever hear the conversation that three baseball umpires once had? If you don’t live in a baseball country, it’s an archetypical story, so you’ve probably heard some variant. By the way, in American English a ‘pitch’ is a throw of the ball for the batter to try to hit, not the field of play. Meanings matter!

• The first umpire says, “Some pitches are balls and some are strikes. I call them as they are.”
• The second umpire says, “Some pitches are balls and some are strikes. I call them as I see them.”
• The third umpire says, “Some pitches are balls and some are strikes. But they aren’t nothing till I call them.”

Most modeling techniques primarily focus on modeling the real world as it ‘really is’. They essentially take a first-umpire point of view or maybe second-umpire. I come from that tradition too. My 1987 book Entity Modeling was about doing that … modeling the real world as it ‘really is’. Pretty much all professionals with some IT background come from that world. Working with business people and business rules for the last 25 years, however, has taught me that business is really more of a third-umpire world. Think of laws, regulations, statutes, contracts, agreements, terms & conditions, policies, deals, bids, deeds of sale, warranties, prospectuses, citations, complaints, receipts, notices … and business policies. Even businesses that deal with tangible stuff (e.g., railroads, electrical transmission, infectious diseases, etc.) live in a third-umpire world. And many of the most automated organizations around have no tangible product at all (e.g., finance, insurance, government, etc.). They really exist only in a world of words (between people). It’s humbling to realize that the way the business world ‘really is’ is more directly the product of words exchanged by the players in a conversation game than anything IT professionals can model directly. But why would it be otherwise? Do IT professionals really know better than business owners, business managers, lawyers, engineers, subject matter experts, etc.? Really?! SBVR, in contrast to almost all other standards, doesn’t try to model the way the real world ‘really is’. Instead, its focus is on modeling what is said about the way the world really is. It’s fundamentally a third-umpire standard. You simply have to understand what the words mean – and that’s a human-communication issue. Yes, the SBVR world view is a game changer. It also happens to align closer with some of the most exciting new work in computerization today including cognitive computing and machine learning. I stand accused by peers in the standardization community of wanting to go beyond the ‘capture, exchange and production of information’. Sure, I can live with that. ~~~~~~~~~~ www.BRSolutions.com

When you show business people class diagrams or data models, you’re not really talking business. Class diagrams and data models are design artifacts that inevitably focus on how knowledge about real-world things is to be represented (and manipulated) as data in machines. If we want business people to talk business to us, we must talk business back. That means talking about their words, concepts and meanings. To do that you need to develop business vocabulary in a structured way – i.e., develop a concept model[1]. Practitioners are slowly starting to ‘get’ this. Examples: 

• IIBA’s recently released Business Analysis Body of Knowledge (BABOK) version 3 devotes a new section to concept models.
• A solid standard exists for concept models – OMG’s Semantics of Business Vocabulary and Business Rules (SBVR).[2] Version 1.3 of the standard, comprehensively reorganized – but not changed – is due out this week.
• Proven methodologies support concept modeling.[3]

~~~~~~~~~~~~~~~~~~~~~~~~~ www.BRSolutions.com

The two fundamental kinds of business rules relevant to business analysis are definitional rule and behavioral rule. These two kinds of rule come from OMG’s SBVR (Semantics of Business Vocabulary and Business Rules) standard.[1] They have very precise meanings based on formal logic. Here’s some background about that – more than business analysts really need to know, but informative nonetheless. At the end of the discussion I give pragmatic definitions. And the answer to the photo quiz. The SBVR definition for rule is deeply embedded in formal logic, which deals with propositions.  In modal logic, propositions can claim different modes. For business rules the two relevant modes are alethic and deontic.  

• Alethic rules are true ‘by definition’. As such they cannot be violated.  They are about how concepts, knowledge or information are defined or structured.
• Deontic rules are rules that can be violated. They are rules about behavior, not concepts, knowledge or information. Deontic rules are really about people, what they must and must not do, even if their activity (and the rules) are automated.

Both kinds of rules are important, of course, but deontic rules – people rules – are especially so since ultimately, businesses are about the activity of people. This situation is very different than in the semantic web, for example, where it’s all about only knowledge. Under modal logic, every rule must therefore ‘claim’ one of two modes. (In practice, the ‘claim’ arises naturally from the syntax of a rule statement or as a meta-property.)

• Alethic implications (rules) are established by ‘claiming’ necessity. Things are necessarily true. A concept is what it is; says what it says. That’s just the way things are.
• Deontic implications (rules) are established by ‘claiming’ obligation. Behavior is ‘obliged’ to follow the rule. But of course, people don’t always follow the rules, so there can be violations. Major difference.

So a rule ‘claims’ either necessity or obligation, which establishes what kind of rule it is. Therefore the SBVR definitions for the two kinds of rule are:

• Definitional rule:  rule that is a claim of necessity
• Behavioral rule:  business rule that is a claim of obligation

Why doesn’t the definition for definitional rule say “business rule” like the one for behavioral rule? Because some definitional rules are not ‘under business jurisdiction’ (in other words, business has no choice about them). Examples include the ‘law’ of gravity and all the rules of mathematics. Those rules are simply universally true. I recommend the following pragmatic definitions for business analysts.

• Definitional rule:  a rule that indicates something is necessarily true (or untrue); a rule that is intended as a definitional criterion for concepts, knowledge or information
• Behavioral rule:  a business rule that places an obligation (or prohibition) on conduct, action, practice, or procedure; a business rule whose purpose is to shape (govern) day-to-day business activity

Synonyms:  Early in the development of SBVR I introduced the terms structural rule and operative rule for the two kinds of rules, respectively. That was before the full implications of modal logic became clear. Since then the terms definitional rule and behavioral rule have become preferred, even in all internal SBVR discussion. The synonyms, however, remain valid. P.S. Did you guess correctly which kind of rule is represented in the photograph? Behavioral, of course. And the photo itself is a violation of the rule. www.BRSolutions.com

A concept model organizes the business vocabulary needed to communicate consistently and thoroughly about the know-how of a problem domain. A concept model starts with a glossary of business terms and definitions. It puts a very high premium on high-quality, design-independent definitions, free of data or implementation biases. It also emphasizes rich vocabulary. A concept model is always about identifying the correct choice of terms to use in communications, including statements of business rules and requirements, especially where high precision and subtle distinctions need to be made. The core concepts of a business problem domain are typically quite stable over time.[1] Concept models are can be especially effective where:

• The organization seeks to organize, retain, build on, manage, and communicate core knowledge or know-how.
• The project or initiative needs to capture 100s or 1,000s of business rules.
• There significant push-back from business stakeholders about the perceived technical nature of data models, class diagrams, or data element nomenclature and definition.
• Outside-the-box solutions are sought when reengineering business processes or other aspects of business capability.
• The organization faces regulatory or compliance challenges.

Definition of Concept Model a model that develops the meaning of core concepts for a problem domain, defines their collective structure, and specifies the appropriate vocabulary needed to communicate about it consistently

The standard for concept models is the OMG standard Semantics of Business Vocabulary and Business Rules (SBVR).[2] Concept Model vs. Data Model A concept model differs from a data model in important ways. The goal of a concept model is to support the expression of natural-language statements, and supply their semantics – not unify, codify (and sometimes simplify) data. Therefore the vocabulary included in a concept model is far richer, as suits knowledge-intensive problem domains. In short, concept models are concept-centric; data models are thing-entity-or-class-centric. Data models can usually be rather easily derived from concept models; the reverse is much harder (or impossible). Like data models, concept models are often rendered graphically, but free of such distractions to business stakeholders as cardinalities. The Components of Concept Models[3] Noun Concepts. The most basic concepts in a concept model are the noun concepts of the problem domain, which are simply ‘givens’ for the problem space.

• For BACCM these basic noun concepts are: need, stakeholder, value, change, context, and solution.
• In finance, basic noun concepts might include financial institution, real-estate property, party, mortgage application, lien, asset, loan, etc.

Verb Concepts. Verb concepts provide basic structural connections between noun concepts. These verb concepts are given standard wordings, so they can be referenced unambiguously.

• In BACCM some basic wordings for verb concepts include: Value is measured relative to Context, Change is made to implement Solution, Stakeholder has Need.
• In a financial business, some basic wordings for verb concepts include: Lien is held against Real Estate Property, Party requests Loan, Asset is included in Mortgage Application.

Note that these wordings are not sentences per se; they are the building blocks of sentences (such as business rule statements). Sometimes verb concepts are derived, inferred or computed by definitional rules. This is how new knowledge or information is built up from more basic facts. Other Connections. Since concept models must support rich meaning (semantics), other types of standard connections are used besides verb concepts. These include but are not limited to:

• Categorizations – e.g., Person and Organization are two categories of Party.
• Classifications – e.g., ‘Toronto Dominion Bank’ is an instance of Financial Institution.
• Partitive (Whole-Part) Connections – e.g., Dwelling and Land are two Parts of a Real Estate Property.
• Roles – e.g., Applicant is the role that Party plays in the verb concept Party requests Loan.

Strengths A concept model:

• Provides a business-friendly way to communicate with stakeholders about precise meanings and subtle distinctions.
• Is independent of data design biases and the often limited business vocabulary coverage of data models.
• Proves highly useful for white-collar, knowledge-rich, decision-laden business processes.
• Helps ensure that large numbers of business rules and complex decision tables are free of ambiguity and fit together cohesively.

Limitations A concept model:

• May set expectations too high about how much integration based on business semantics can be achieved on relatively short notice.
• Requires a specialized skill set based on the ability to think abstractly and non-procedurally about know-how and knowledge.
• Involves a knowledge-and-rule focus that may be foreign to stakeholders.
• Requires tooling to actively support real-time use of standard business terminology in writing business rules, requirements, and other forms on business communication.

For more information about Concept Models, refer to Business Rule Concepts 4^th ed, by Ronald G. Ross, 2013, Part 2. www.BRSolutions.com

Re-engineering knowledge work is the central problem of the knowledge economy. In recent work at Centers for Disease Control (CDC) and current work a major bank in Canada we used RuleSpeak® to create what I call a “single source of truth for operational business IP (intellectual property)”. This is far more than a conceptual data model. Beyond structured business vocabulary its central feature is comprehensive rules. It may be like what some professionals call a “conceptual ontology” (as opposed to an operational ontology to be embedded in IT systems). But we would never use the term “ontology” in our work.  Most business people and SMEs simply wouldn’t ‘get’ that. The idea is that all audiences (or subcommunities) in an organization should work off a single trusted source of explicit know-how (business vocabulary and business rules), no matter what their specific responsibilities:

• producing training materials for line workers.
• making changes in operational policies.
• providing proof of compliance for auditors.
• creating new products.
• communicating with IT.

Here are some key observations about our work to create a single source of business truth:

• Our primary audience is not IT. Yet our work is of sufficient precision that straightforward translation into an implementation form can basically be taken as a ‘given’.
• Our approach recognizes that people are the essential ingredient in business (as opposed to other kinds of knowledge problems). People can violate rules. For coordinating the work of people, direct support for behavioral rules, not just definitional or decision rules, is a must.
• Our work could not be undertaken without a structured natural language for business rules like RuleSpeak. The non-IT audiences do need rich business semantics, but they have no desire whatsoever to become semantic programmers. They simply would not commit if the work were conducted on that basis.
• No one today knows what the optimal syntax is for expressing all forms of business know-how in all circumstances. I suspect there isn’t one. That fact, plus the exponential increase in computer capability for processing natural language, indicates clearly that focusing on syntax is simply the wrong direction. RuleSpeak is based on, and was one of the reference languages for SBVR (Semantics of Business Vocabulary and Business Rules, on OMG standard), which supports a non-syntax approach. A language for ‘speaking’ with computers that is not a computer language – now that’s an idea whose time has definitely come!

www.BRSolutions.com

I have said many times programmers, even semantic programmers, are not the wave of the future for business rules. The future lies with enabling business people and business analysts to have dialogs with machines coming as close to unambiguous statements as they can (e.g., in RuleSpeak). The machine should ask questions to reduce ambiguity to an acceptable minimum. To protect against liability, the machine should log all assumptions, major and minor, in translating to an internal (formal and unambiguous) form so that results are traceable and improvable. Consider IBM Watson. If machines can win at Jeopardy against the best players in the world, that’s a pretty impressive feat for natural language capability. Let’s compare apples to apples. There will always be translation of business ”requirements” from human form to machine form. Even some perfect (a.k.a. formal semantic) implementation language would not reduce translation errors to an absolute minimum. Coders would still have to translate, and errors compound with every translation. So I say disintermediate; eliminate the middlemen – i.e. the coders. If you look across a great many industries, that’s the trend. Why should development of business applications be any different? I also suspect that any “formal semantic” language for business rules would inevitably be English-biased. That’s simply not acceptable in a global economy. RuleSpeak[1] has gathered increasing attention around the world. There are now versions in the works for Norwegian, Polish and Japanese, in addition to the original English and the existing Dutch, German and Spanish translations. A growing number of people find that RuleSpeak strikes just about the right balance between structured and unstructured expression. I’m not saying, however, that other useful approaches couldn’t be more formal – or less formal – than RuleSpeak. Perhaps they could. And that’s been my point for all these years working on SBVR[2] as a business rule standard. We simply don’t yet know the absolute best approach for expressing all business rules in all circumstances. No one knows enough. Perhaps there isn’t one. SBVR is brilliant precisely because it captures semantics without dictating expression form. Long term, that’s exactly what the industry needs. No, there hasn’t been rapid vendor implementation of SBVR since release of 1.0. I wouldn’t expect there to be. It threatens virtually every interface and mindset on the planet. Most people in the IT field still just don’t get it. In retrospect, OMG may have been the wrong forum for SBVR for at least two reasons:

1. OMG is the bastion of best-of-breed programming standards. Obviously there is an important role for that, but as above SBVR isn’t about programming.

2. The SBVR vocabulary is extremely useful for organizing business conversations about business vocabulary and business rules. OMG doesn’t ‘do’ business-facing standards of that kind (i.e., ones that don’t “compute”). IMO, that’s a major shortcoming. There is ultimately nothing more important than improving communication at the level of people. Get it wrong there and I promise it will be wrong in business automation, no matter how elegant the implementation language.

The bottom line is that machines for business (rule) automation now must learn to ‘speak’ human languages. The other way around is simply no longer acceptable – or even necessary. www.BRSolutions.com  

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