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Knowledge
tips
The organization of the human knowledge has helped us advance our understanding of the universe. While building the understanding of the universe we find that knowledge categorization and simplification will help us access information quickly and identify important relationships and patterns.
Categorization and knowledge modeling are key elements to view, query and analyze our business.
A knowledge model widely used is the use of taxonomies. Scientists use organization as a tool to arrange components into systems and parts into patterns.
They are in fact the only way we can make sense of data and information that enters our business daily from many different sources, i.e. news feeds, media files, emails, pdf files, and of course data from our own business systems. It will let us see patterns that we would not recognize without knowledge models.
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Categorization is the most primitive knowledge model. It allows humans and living species to label and acts accordingly. i.e., food or not, poison or not, essential or non-essential, threat or safe. In business we categorize by customer groups, product categories, competitive threats, profitability categories, market segments, HR requirements, regulatory requirements, opportunities, …. Knowledge modeling becomes essential to make sense of all this data and information.
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Categorization is essential to retrieve information
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Categorization allows us to infer the characteristics of the classified information quickly.
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Categorization allows seeing relations between things.
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Categorization is vital to transmitting knowledge (as categories of objects such as corrugated board vs folding carton board, vs paper grades)
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Categorization starts with a set of data. Therefore, new data can use the current categorization or reveal the need to modify the current one.
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Proper categorization helps to define the business processes and the rules that apply at different steps—assisting in the consistency and standardization of tasks.
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Because categorization puts your mind in a conceptual frame, it helps you easily to make connections between things and see “the big picture”.
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Once different categorizations are defined, you can go back and refer to your information in other systems, such as in text, email, books, websites, news, reports, etc. and link such data to your knowledge model. The perspective changes. The context changes.
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Knowledge models provide you with a 360°-degree view of your employees, customers, products, etc., by unifying structured and unstructured data and connecting data silos through harmonized metadata.
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Check your data. Start with what you have. Are you getting the answers you need? What “blanks” can you not fill in?
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Build your categorization and knowledge model with the subject matter experts through your company. You can start with industry-specific models and available taxonomies.
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If feasible, using artificial intelligence and machine learning assists you in building your knowledge models.
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Remember, categorizations are an expression of knowledge organization; they are dynamic, so workflows can help to keep the models up to date.
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These workflows should also allow participation. Empiric observations can also be part of the model, new business objects of interest: as with humans, a theory can end up being a significant discovery.
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A well-constructed knowledge model will relate people to their interests and needs. For example, how customers relate to your business associates and your products. Better yet, how your customers experience relates to other potential customers discovering your product and service offering .
Categorization offers you a tremendous competitive advantage by providing Speed, Relevance, Consistency, Focus, and Deductive capacities through the vast data and information you have. It keeps you focused on the relevant information you need and shines the light brightly at concepts and categories that are outdated.
The use of this conceptual knowledge model is expressed in a Knowledge Graph (KG). A KG can be used to overlay your data, without change or duplication, to see your data from other perspectives.
They bring the possibility to relate and see your data in ways beyond the limitations of your systems by enriching consolidation, reporting, search, matching, recommendation, identification of niches and trends.
Your knowledge model journey can start from answering the question, what do we use corrugated board for? Later the use of machine learning and semantic technologies help you to find these concepts throughout your data.