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Grapes & Chickens: Building the Models That Support Everything

Since entering this profession (information management), I have been amused by the expression “comparing apples and oranges,” which is used to communicate a vast chasm of difference between two items. A typical use of this idiom includes “Comparing a train ride to riding a bicycle is ridiculous, an apples-and-oranges comparison.”

Why am I so amused? Because apples and oranges are both fruit, that’s why. They are, absent any other influential context, essentially the same thing. They are grown in orchards, sold next to each other in stores, purchased for the same price, eaten raw, turned into juice, filled with natural sugar and seeds, and so on. I even use them when teaching basic taxonomy.

The idiom is based on the idea that the distinctions between these two items is too strong to enable a reasonable comparison. For example, it would be unfair to measure the tartness or freshness of an apple using an “orange-based standard.” This is true, of course, but it is even harder to compare an apple with a hockey stick, a prime minister, an emotional outburst, or a philosophical approach to understanding the world.

The is-ness of an item must be singularly defined, assigned, and understood when designing an information system to support it. An item’s is-ness defines how it must be modeled (its schema), which controls how it is described, Are webinars the same as documents? Are tweets like emails? Hammers like nails? Customers like each other? Until you are clear on how and why different items are different -- or the same -- you really shouldn’t be designing their containing knowledge systems.

Here’s a joke my kids taught me. What’s the difference between a chicken and a grape? The answer: They’re both purple, except for the chicken.

Modeling is at the core of every data-driven application, from the analysis of big data to the Internet of Things, from sales to research, people and places and things. Designing the right model can open the door to apples-and-orange comparisons, just as it can make them impossible.

For a look into how we use customer data models, product data models, content models, and knowledge architecture to create a framework for unified commerce download our whitepaper: Attribute-Driven Framework for Unified Commerce

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How to Design Omni-Channel IVAs That Humans Love To Use

During our webinar, "Omni-channel Virtual Assistants - The Next Frontier in Voice and Text for Customer Service guest speaker Chris Featherstone, who leads business development for AI and speech recognition services at Amazon Web Services (AWS) and Seth Earley, CEO of Earley Information Systems (EIS) discussed ways to design omni-channel virtual assistants to optimize their use across voice and text. When supported by an appropriate information architecture and designed with a deep understanding of the customer, virtual assistants can access enterprise knowledge efficiently, saving time and money. The key to success is to structure the underlying information so it can be retrieved and used by any channel, including humans, to deliver the responses that customers need. Here's a recap of the conversation.