Definitions of business terms with subtle IT or ‘data’ bias are an anathema to effective communication with business partners. Good business definitions are oriented to what words mean when used by real business people talking directly about real business things.
Here are 5 basic criteria for great business definitions:
It should be easy to give examples for the thing defined, but there should be no counterexamples.
Each definition should communicate the essence of what a thing is, not what it does, how it’s used, or why it’s important.
The definition of a thing should focus on its unique characteristics.
Each thing you define should be distinguishable from every other thing you define using the definition alone.
Each definition should be concise and as short as possible without loss of meaning. A definition should be readable.
One thing may surprise you about great business definitions. The very first noun in each definition is absolutely key. These first words are the secret sauce of excellent business definitions. Read more in our new Primer (free download).
There’s a high premium on knowing how to craft great definitions. Every business analyst should know how. We’ve just published a new Primer on creating business definitions (see below – free download).
There are various schools of thought about how to define terms, some arising from professional terminologists and academia. But those approaches are often relatively arcane and not well-suited to everyday business practice.
So you should stick with common dictionary practices. They are perfectly adequate for your needs. By ‘dictionary’ I mean natural language dictionaries of course, not any kind of dictionary arising from IT (e.g., data dictionaries).
If you want to talk about how data is retained or exchanged, do a data model. A good data model has definitions too of course, but they subtly relate to fields and data types, not directly to things in the real world. That bias throws them off-center for business communication. This implicit mindset is often hard for those with a data or IT background to unlearn. But not impossible! If you fall into this category, our Primer will teach you how.
Our new Primer is organized as a set of guidelines, each with one or more examples. Each guideline can be understood on its own, but the overall set is mutually supportive and comprehensively interlocking. Master this set of guidelines and your definitions are guaranteed world-class.
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 does not have an innate concept/approach for “legality” in the sense of MWUD 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 ruleA 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 rulesA 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
Semantics of Business Vocabulary and Business Rules
Guest Post by Markus Schacher
We should first agree on the semantics of underlying concepts and only then start to think about the best terms for those concepts.
One particular technique I often apply in such cases is the following:
1. Name controversial concepts with proxy names such as “Greg”, “Mike” or “John” (or whatever name you prefer) to get potentially misleading names and their implicit connotations out of the way of progress.
2. Draw a concept diagram showing those concepts as well as important semantic relationships among them.
3. Formulate intensional definitions for each concept – still using the proxy names. Ensure that those definitions are consistent with the relationships shown on the concept diagram.
4. Identify one or more communities that “baptize” those concepts by giving them better names.
If synonyms and/or homonyms appear among those communities, that’s just how the world is; we simply have to live with it. This is why SBVR formally supports semantic communities as well as speech communities.
To understand the future of processes, you must dig a little deeper than many people do.
Process thinking goes back well over a 100 years, to the origin of modern iron and automobile production. The raw materials and finished goods of such manufacturing and production processes are literally spatial – 3-dimensional. What can you do to significantly improve productivity in a 3-dimensional world? The answer these days is simple: You build robots. Robotization has literally changed the world during the past 30-40 years.
Rather than manufacturing and production processes, however, the world is now increasingly focused on white-collar and digital processes. What 3-dimensional presence do the raw materials and finished goods of these processes have?
Well, exactly none. The raw materials and finished goods of these processes aren’t physical and simply have no spatial presence whatsoever (except maybe for paper artifacts). Robots (at least physical ones) aren’t an option. That fact of life makes a huge difference in how you have to think about automation for such processes.
Instead, the raw materials and finished goods of such processes are all about your operational business knowledge – your intellectual capital – and your capacity to express and apply it. That capability, in turn, depends directly on your business terminology and business language. For white-collar processes you have no choice – the world is semantic. So you must deal with the subject matter semantically.
That takes us in a very different direction than most professionals currently foresee. For one thing it takes us toward natural language and away from diagrams-for-everything. That’s a huge shift in mindset. Imagine having a business conversation with your smart phone about gaps and ambiguities in business policies and in the meanings of the vocabulary you use to talk about subject matter knowledge. Don’t think that’s possible? Have you watched your kids talking to their smart phones lately?
Sooner or later businesses will realize that operational business knowledge differentiates their product/services and enables their ever-more-automated processes to function. Capturing, managing and re-using that intellectual capital puts a premium on structured business vocabulary (concept models) and on business rules expressed in structured natural language. Those business rules are the only way you have to ensure quality from white-collar and digital processes.
Read more on this topic:
Are Processes and BPM Relevant in the Digital Economy? http://www.brsolutions.com/2015/10/19/are-processes-and-bpm-relevant-in-the-digital-economy/
Measuring Quality and Defects in the Knowledge Economy: http://www.brsolutions.com/2015/10/27/measuring-quality-and-defects-in-the-knowledge-economy/
Quality and Tolerances in the Knowledge Economy: http://www.brsolutions.com/2015/10/29/quality-and-tolerances-in-the-knowledge-economy/
Building Business Solutions: Business Analysis with Business Rules (2nd Edition) … Just Out! http://www.brsolutions.com/b_building_business_solutions.php
Get it on Amazon: http://goo.gl/HXxN1fWhat It’s About: How to develop business solutions working directly with business leads, create blueprints of the solutions, and then use those blueprints for developing system requirements. Engineering business solutions, not just requirements.We have applied the techniques described in this book successfully in hundreds of companies worldwide.
Kind Words from a Practitioner: “We have based our whole business rules analysis practice on the methodology and techniques developed by the Business Rules Solution team. This book is an integral part of our practice. It’s an easy to read, useful guide with real life examples – we use it daily and couldn’t do without it!” – Michelle Murray, Inland Revenue Department NZ
New in this Edition: How Business Architecture corresponds with your projects and requirements work. Developing a Concept Model and how it will help you. How business rules align with the new terminology in the recently released IIBA® BABOK® Guide version 3.
OMG released version 1.3 of SBVR (Semantics of Business Vocabulary and Business Rules) last month – comprehensively reorganized for approachability, but not changed. 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.
Professionals should always focus on business solutions first, then and only then on designing systems. Not just lip service, I mean applying the power techniques of true business architecture. The first two of these techniques are:
The third technique is structured business vocabulary – a concept model.
The value-add companies produce today is based on rich operational business knowledge. No business solution can prove truly effective if business people (and the tools they use) are unable to communicate about that knowledge clearly. Who profits from operating in a Tower of Babel?
A concept model is about identifying the correct choice of terms to use in business communications (including statements of business rules) especially where subtle distinctions need to be made. A concept model starts with a glossary of business terms and definitions. It puts a premium on high-quality, design-independent definitions, free of data or implementation biases. It also gives structure to business vocabulary.
Essential for any true architecture is stability over time. Are the core concepts of an operational business stable over time? Yes. Did you know that?!
Do people in your company always mean the same thing when they use the same terms? Almost certainly not, right?! So ask yourself, how good are your business communications and requirements likely to be if people don’t mean the same things by the terms they use? And how good is your automation likely to be?Gurus talk about application or functional silos in organizations. I believe the problem is even more basic than that – organizations today essentially have semantic silos. Look under the covers of any broken process or poor set of requirements and you inevitably find poor communication practices. These days you don’t have the time not to define, structure and manage your business vocabulary. These days a concept model is no luxury. ~~~~~~~~~~~~~~~~~~~~~~~~~www.BRSolutions.com
I certainly understand the need for data models, and that fact they should be coordinated/integrated with process models. Who would question that these days?! But to re-engineer business decisions or knowhow-intensive business processes (or both), you need a structured business vocabulary – i.e., a concept model. The purpose of a concept model is to provide the terminology and wordings to write hundreds (or thousands) of rules coherently and consistently. Building such blueprint is not an insignificant undertaking. Yes, a concept model can be used as the basis for designing a model of the data needed to support processes, but that’s not its primary objective. Rather its purpose is to understand what the business rules and decision logic are talking about business-wise at ‘excruciating level of detail’ (to borrow a phrase from John Zachman).
A concept model involves hundreds of terms, some whose meanings are obvious, some whose meanings you think are obvious but aren’t, and some whose meanings are simply mysterious. We constantly have to caution against setting expectations too high about how much integration based on business semantics can be achieved on relatively short notice. Even though it seems like ‘defining business terms’ should be relatively easy, concept modeling is by far the hardest work we do. The problem in virtually every organization in the world today is that these business semantics have never been developed well enough (think semantic, rather than functional, silos) to take automation of logic to the next threshold – i.e., to white-collar automation. Yet that’s exactly where a great many organizations currently want (and urgently need) to go.www.BRSolutions.com
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