What Is Conceptual Modeling? Conceptual Modeling In A Nutshell

Conceptual modeling is the process of developing an abstract model or graphical representation using real-world concepts or ideas. During conceptual modeling, various assumptions are made regarding how the system functions. Conceptual models also illustrate the dominant processes in a system and how they are linked. These processes may include factors known to drive change in the system, or they may encompass the consequences of change in the factors themselves.

Understanding conceptual modeling

To understand and manage complex natural systems, simplifying assumptions must sometimes be made. This is achieved by portraying the system as a conceptual model based on the collective knowledge, experience, and perspectives of each.

In business, conceptual modeling is used to document definitions and communicate the precise meaning of terms to stakeholders. The process can best be described as a semantic representation of the nouns that are important for an organization or domain. This makes conceptual modeling especially useful in knowledge-intensive projects where subtle distinctions need to be made during communications. Indeed, conceptual models are devoid of technical biases and data models and should represent the language of an organization

Conceptual models also help stakeholders better understand a situation and are used as a starting point in participatory or collaborative modeling. In this case, various stakeholder groups establish a common language that encourages innovative planning, evaluation, and collaborative decision-making.

Due to an increasingly broad and complex spectrum of abstract concepts, conceptual modeling can be used for many different projects across a similarly diverse number of fields. In software development, conceptual modeling tends to be used as a form of data modeling to represent abstract business entities and their relationships. The approach is also used in visual design, rapid application development, hotel reservation systems, online shopping applications, information systems development, and enterprise resource planning (ERP) systems.

Common conceptual modeling techniques

Below are some of the most commonly used conceptual modeling techniques:

  1. Data flow modeling (DFM) – a basic technique where the elements of a system are graphically represented by data flow. Instead of illustrating complex system details, DFM gives context to major system functions.
  2. Event-driven process chain (EPC) – a technique primarily used to improve business process flows. An EPC is comprised of events that define what state a process is in or the rules by which it operates. To progress through events, a function or active event must be executed. This technique is commonly seen in resource planning, logistics, and process improvement.
  3. Entity relationship modeling (ERM) – this modeling technique is typically seen in software systems. Here, database models and information systems are represented by entity-relationship diagrams, with entities denoting functions, objects, or events.
  4. Petri nets – a conceptual modeling technique for the description of distributed systems using exact mathematical definitions of execution semantics. Petri nets offer a graphical notation for stepwise processes that include iteration, choice, and concurrent execution.

Limitations of conceptual modeling

Conceptual modeling is based on abstract conceptual models that are only as useful as the business makes them.

With that in mind, here are a few caveats to conceptual modeling:

  • Time-intensive – improper modeling of entities or relationships can cause time wastage and potential sunk costs. This usually occurs when development and planning have lost sight of the original problem or objective.
  • System clashes – there is always the potential to create clashes between the various components of an abstract system. In the context of conceptual modeling, this may occur when design and coding assumptions clash after deployment.
  • Scaling challenges – while conceptual modeling can certainly be used for larger applications, there are risks associated with developing and maintaining conceptual models in complex projects. This is because the number of potential clashes grows exponentially as the size of the system increases. 

Key takeaways:

  • Conceptual modeling is the process of developing an abstract model or graphical representation using real-world concepts or ideas. The approach is used in visual design, hotel reservation systems, online shopping applications, and enterprise resource planning (ERP) systems, among many other applications.
  • Conceptual modeling techniques include data flow modeling, event-driven process chains, entity relationship modeling, and Petri nets.
  • Conceptual modeling does have some limitations. For one, the improper modeling of entities and relationships can result in sunk costs. There is also the constant threat of system clashes, particularly as the size and complexity of the system increases.

Connected Business Concepts

Contextual inquiry is a research method based on user-centered design (USD) and is part of the contextual design methodology. Contextual inquiry as a research method does not involve setting people certain tasks. Instead, users are observed while they work in their own environments. The context of these environments typically encompasses the home, office, or somewhere else entirely.
Convergent thinking occurs when the solution to a problem can be found by applying established rules and logical reasoning. The term convergent thinking was first described by American psychologist Joy Paul Guilford in 1950. The process of convergent thinking involves finding the single best solution to a problem or question amongst many possibilities. 
Divergent thinking is a thought process or method used to generate creative ideas by exploring multiple possible solutions to a problem. Divergent thinking is an unstructured problem-solving method where participants are encouraged to develop many innovative ideas or solutions to a given problem. These ideas are generated and explored in a relatively short space of time. 
First-principles thinking – sometimes called reasoning from first principles – is used to reverse-engineer complex problems and encourage creativity. It involves breaking down problems into basic elements and reassembling them from the ground up. Elon Musk is among the strongest proponents of this way of thinking.
The ladder of inference is a conscious or subconscious thinking process where an individual moves from a fact to a decision or action. The ladder of inference was created by academic Chris Argyris to illustrate how people form and then use mental models to make decisions.
The Six Thinking Hats model was created by psychologist Edward de Bono in 1986, who noted that personality type was a key driver of how people approached problem-solving. For example, optimists view situations differently from pessimists. Analytical individuals may generate ideas that a more emotional person would not, and vice versa.
Second-order thinking is a means of assessing the implications of our decisions by considering future consequences. Second-order thinking is a mental model that considers all future possibilities. It encourages individuals to think outside of the box so that they can prepare for every and eventuality. It also discourages the tendency for individuals to default to the most obvious choice.
Lateral thinking is a business strategy that involves approaching a problem from a different direction. The strategy attempts to remove traditionally formulaic and routine approaches to problem-solving by advocating creative thinking, therefore finding unconventional ways to solve a known problem. This sort of non-linear approach to problem-solving, can at times, create a big impact.
Moonshot thinking is an approach to innovation, and it can be applied to business or any other discipline where you target at least 10X goals. That shifts the mindset, and it empowers a team of people to look for unconventional solutions, thus starting from first principles, by leveraging on fast-paced experimentation.
Tim Brown, Executive Chair of IDEO, defined design thinking as “a human-centered approach to innovation that draws from the designer’s toolkit to integrate the needs of people, the possibilities of technology, and the requirements for business success.” Therefore, desirability, feasibility, and viability are balanced to solve critical problems.
The CATWOE analysis is a problem-solving strategy that asks businesses to look at an issue from six different perspectives. The CATWOE analysis is an in-depth and holistic approach to problem-solving because it enables businesses to consider all perspectives. This often forces management out of habitual ways of thinking that would otherwise hinder growth and profitability. Most importantly, the CATWOE analysis allows businesses to combine multiple perspectives into a single, unifying solution.

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