Business Rules Solutions: Introducing Business Knowledge Blueprints: Achieving Shared Understanding Using Concept Models

Extracted from Business Knowledge Blueprints: Enabling Your Data to Speak the Language of the Business, by Ronald G. Ross, 2020.

In the computer age, we’ve limped along literally for a human lifetime without blueprints for business knowledge and the vocabulary used to communicate it. How well is that working out?

If you have any doubt, do a quick internet search on all the problems associated with ‘data quality’ and their costs. Or look at the still dismal success rates of IT projects. Or consider the continuing frustrations of business process professionals in eliminating silos.

A business knowledge blueprint, whose core component is a concept model, permits you to deeply analyze your concepts, your vocabulary, and your business knowledge. In this month’s column, Ron explains all the critical reasons you need that blueprint.

fig. 1

I recently ran across a cute cartoon aptly entitled Lexical Ambiguity. It shows two barber shops side-by-side, both named Animal Barber. In one, a human is brushing a poodle. The sign on the front door says “Open”. In the other, a poodle is cutting the hair of a human. The sign on the front door says “Woof”. Of course – animal barbers!

Common sense allows us to reject the Woof interpretation immediately. Funny, but highly improbable. But what if you were an alien from another planet and knew nothing at all about earth’s animal kingdom? Not so obvious then.

With respect to business knowledge, we often find ourselves almost like aliens – woefully underequipped. And if it’s difficult for us, think about our customers and suppliers and other partners. Think about new hires, or staff switching to new roles. How long is too long to come up to speed?

If you’re a government organization, think about the service providers who must interpret and implement your policies. What are you doing to ensure your intent is properly divined and deployed? Get the knowledge wrong, and the solution will never be right. Actually, that challenge applies to all industry sectors in every business communication you write.

Even when you think you know some business knowledge pretty well, it’s hard to communicate clearly and consistently. It’s virtually impossible to hold it all in your head. There’s just too much. And what about retaining it when key staff leaves your company?

Now think about our machines. They are aliens! Maybe humans are genetically hardwired for natural language and textual knowledge, but our machines most definitely are not. They have zero genetic endowment to fall back on.

If you think machines can bootstrap themselves all the way to human capability for textual knowledge without our help, you’ve been badly duped by the hype. Self-driving cars navigating roads and avoiding obstacles? Yes. Flying drones? Yes. Machines disambiguating and deeply understanding contracts and tax code? No, at least not without our help. Concepts and language are hard.

A business knowledge blueprint, whose core component is a concept model, aims squarely at eliminating lexical ambiguity. It permits you to deeply analyze your concepts, your vocabulary, and your business knowledge. It will enable you to communicate virtually anything with business clarity.

That capability will also serve you well in designing data. The message with respect to data is quite simple. Putting data haphazardly into generalized buckets with loose labels impoverishes it. It forfeits quality, precision and reusability. To make data potent you must put it in exacting buckets with highly accurate terms and definitions based on a concept model. Only potent data proves trustworthy, sharable and manageable.

Perhaps you are looking for a means to engineer extreme product agility. Fast, scalable reconfiguration requires highly granular, business-based blueprints. Or maybe you’re plagued by functional silos in your organization. Creating a concept model establishes trust and common ground across entire value chains. Maybe you’ve realized business knowledge needs to be central to the payload of your business processes. Concept models address all these challenges.

Perhaps you’re seeking a long-term architecture to ensure platform independence. (By long-term I mean more than a decade.) Perhaps you are looking for a business-friendly means to drive projects using graph databases and ontology development using RDF, OWL and companion tools. Concept models.

Or maybe you’re simply frustrated that your software staff simply doesn’t speak ‘business’ adequately (or that your business staff has become too comfortable speaking IT-ishly). Want to improve the quality of business communication across the board? Concept models.

A concept model is your ticket to a Knowledge-Age solution for any and all the challenges above. It’s the common denominator. Put simply, it’s how you achieve shared understanding.

Welcome to concept models!

PDF Version

Ron Ross

Ron Ross

Ronald G. Ross is Co-Founder and Principal of Business Rule Solutions, LLC ( BRS provides workshops, consulting services, publications, and methodology supporting business analysis, business rules, business vocabulary, and rule management. His popular public seminars on business rules and business analysis, the first on business rules (starting in 1996) and the longest-running in the industry, are given through AttainingEdge ( At BRS, Mr. Ross co-develops Proteus®, its landmark business analysis and business rules methodology, which features numerous innovative techniques including the popular RuleSpeak® (available free through These are the latest offerings in a 30-year career that has consistently featured creative, business-driven solutions. Mr. Ross also serves as Executive Editor of and its flagship on-line publication, Business Rules Journal. He is a regular columnist for the Journal’s Commentary section which also features John Zachman, Chris Date, Terry Halpin, and Roger Burlton., hosted and sponsored by BRS, is a vertical community for professionals working with business rules and related areas. Mr. Ross was formerly Editor of the Data Base Newsletter from 1977 to 1998.


Leave a Reply

Your email address will not be published. Required fields are marked *