As business analysts, one of our primary efforts goes into discovering requirements. Wouldn’t it be a great proposition to come up with possible requirements only by looking at the key terms in the domain? Then, of course, they need to be verified with the stakeholders that the requirements are worth developing.
We can do the same using the technique, Concept model
A lot of people have a lot of doubt about the concept model and the Glossary data model. These techniques are interconnected, but they are slightly different as well. So maybe in some other blog, we would explain the linkages between glossary, concept model, and data model and try to be clear about the three modeling techniques we have. But before that, let us talk about this particular technique and apply it to our project context.
Concept Modeling technique models key concepts in business vocabulary, usually starting with a glossary. The concept model for Adaptive’s BA learning Platform, SuXeed, is shown below:
A glossary ensures a common understanding of words, phrases, terms used amongst stakeholders, not to understand the relationship between concepts. In a glossary, the key terms are only defined (i.e., Need: A problem or opportunity to be addressed).
Concept models are effective in:
- Organizing, managing, and communicating core knowledge,
- Capture large numbers of business rules,
- Not technical like data models,
- Regulatory or compliance needs.
According to BABoK V3.0, “A concept model is used to organize the business vocabulary needed to consistently and thoroughly communicate the knowledge of a domain.”
Concept models typically start with a glossary. It emphasizes on rich vocabulary and calls for identifying the appropriate set of terms to be used in business communications. It is represented by means of relationships.
This is certainly a great way to organize, manage and communicate meanings precisely and unambiguously to stakeholders in a business-friendly manner. This would also be a welcome change for stakeholders looking for a change from the technical nature associated with data models, class diagrams, etc. However, this technique calls for the ability to think abstractly and non-procedurally and may need some tool support for proper implementation.
Concept models are different from data models. Concept models support the expression of natural language statements. Concept models are not intended to unify, codify, and simplify data.
Noun concepts – Entities or objects of interest, e.g., “Customer,” “Order,” etc.
Verb concepts – Actions, such as “Create” and “Update.”
This would form a sentence like “Create Customer,” “Update Order.”
Strengths
- Makes precise communication.
- Independent of data design biases.
- It helps in reducing ambiguity.
Limitations
- Requires abstract thinking skills.
- Need tool support for strict implementation.
Worked out Example:
Let us learn the concept model by means of an example. Governance, Risk, and Compliance (GRC) management system is developed for the IT and ITES domain. The primary objective of the GRC management system is to help companies implement Governance, Quality, and Information Security Management Systems in an integrated manner. It has various features, one of which is planning and tracking projects and programs using standards such as CMMI, ISO 9001, ISO 27001, etc.
Let us look at the concept model for the schedule management module of Governance, Risk, and Compliance management.
Concept models play around with noun and verb concepts. As we can see, Governance, Risk, and Compliance (GRC) management schedule management module deals with 4 major concepts – PM, Schedule, Schedule repository, and Schedule history. These are called noun concepts. As for that, which connects the noun concepts with one another is referred to as verb concepts as it depicts some form of action. For instance, ‘views’, ‘creates’, ‘stores’ etc. are verb concepts.
Now, how can we make sense out of this representation?
If we were to read a concept model, it would be something like this – a PM creates schedules, the schedule is stored in a schedule repository, PM views schedule history, etc.
Each of the 4 concepts works together to understand the type of information that is elicited, analyzed, or managed within Governance, Risk, and Compliance management-schedule management.
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