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

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!

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