Process modeling is the movement of one nature, which are generalized into a prototype. Thus, this term describes development at the level of type. The same process simulation is used repeatedly for application development. A large number of copies is of fundamental importance. One possible use of movement is to prescribe how everything should or could be done. Process modeling is an approximate expectation of how the application will look. The course itself is determined during the actual development of the system.
Modeling goals
Firstly, it is necessary in order to track what actually happens during work. It is necessary to take the point of view of an external observer who looks at how the process is carried out. The next step is to identify the improvements that need to be made in order to increase efficiency or effectiveness.
Prescribing
Identify the desired processes and how they should or could be performed.
Rules, guidelines, and cognitive behaviors must be established that, if followed, will lead to desired performance. They can range from strict enforcement to flexible leadership.
Explanatory
Provide explanations regarding the validity of the processes. It is necessary to study and evaluate several possible lines of action based on rational arguments.
Establish a clear link between the processes and the requirements that the cognitive model must meet. Preliminary determines the points at which data can be extracted for reporting.
goal
From a theoretical point of view, process modeling explains the key concepts needed to describe what happens during development. From an operational point of view, meta-processes are aimed at providing recommendations for methodological engineers and application developers.
Business process modeling activities typically involve the need to modify or identify problems that need to be fixed. This transformation may require IT involvement. Although this is a common reason for the need for business modeling. Change management programs are desirable for putting processes into practice.
With the development of technology from major platform suppliers, the concept of business processes becomes fully feasible (and capable of two-way design). She is approaching reality every day. Supported technologies include a unified language, model-based architecture, and service-oriented development.
The concept of modeling addresses aspects of the processes of corporate business architecture, which leads to the creation of a comprehensive application. Interconnections in the context of other enterprise systems, data, organizational structure, strategies, etc., create greater opportunities for analysis and planning of changes. One real-life example is corporate mergers and acquisitions. A detailed understanding of the processes in both companies allows management to identify redundancies, which leads to a smoother merger.
The concept of modeling has always been a key aspect of business process reengineering and continuous improvement approaches that can be seen in Six Sigma.
Classification
There are five types of coverage in which the term process model has been defined differently:
- Activity-oriented: a related set of activities carried out for a specific product determination result. A set of partially ordered steps designed to achieve a simulation goal.
- Product orientation: a series of actions that lead to the fact that sensitive transformations help to achieve the desired result.
- Decision-oriented: A set of related decisions established to define a product.
- Focus on strategy: allows you to create models that represent multi-purpose processes, and plan all sorts of ways to develop a product based on intention and strategy.
Alignment
Processes can be of different types. These definitions correspond to various methods of process simulation. So:
- Strategic. They are designed to explore alternative ways to do something and develop a plan. Often creative and require human cooperation. Thus, the creation of alternatives and the selection of them are very important activities.
- Tactical processes. This is help to achieve the plan. They care more about the tactics that will be adopted for the actual execution of tasks than about development.
Granularity
The detail refers to the level of detail of the process model and affects the type of guidance, explanation and follow-up that can be provided. Rough concretization limits them to a rather narrow level, while fine granularity provides a more detailed possibility. The nature of the detail required depends on the particular situation.
The project manager, customer representative, senior or middle management needs a rather rough description of the process, because they want to get an idea of the time, budget and resource planning for their decisions. In contrast, software developers, users, testers, and analysts will prefer a detailed process model where each item can provide them with instructions and important execution dependencies.
While there are notations for fine-grained patterns, most traditional processes are crude descriptions. Models should provide a wide range of detail.
In flexibility
This is another process modeling method. It was found that although these models are prescriptive in nature, deviations are possible. That is why the basis for adoption has evolved in such a way that the methods of developing systems are consistent with specific organizational situations and thereby increase their usefulness.
A process approach to managing business process modeling can be organized in a range of flexibility from “low” to “high”. At the “lower” end of this spectrum are hard methods. Whereas the “top” is a modular design. Hard methods are completely predetermined and leave little room for adaptation to an existing situation. Modular systems, on the other hand, can be modified and supplemented to fit a specific strategy.
Finally, the selection and adjustment of the method allows each project to create methods from different approaches and customize them according to needs.
Quality methods
In most existing structures designed to understand properties, the line between the nature of modeling and their application is not drawn. This report will focus both on the quality of process modeling methods and on models to clearly distinguish between them. Various structures have been developed to help in understanding the properties. This structure also has the advantages of providing a uniform and formal description of the model element within the framework of one or different types using the same modeling methods. In short, this can make an assessment of both product quality and process as defined previously.
Properties that relate to business process modeling methods:
- Expressiveness: the degree to which this technique is capable of designating prototypes of any number and types of applications.
- Arbitrariness: degree of freedom when modeling the same zone.
- Suitability: the level at which this technique is specifically adapted to a specific application area.
- Understanding: the ease with which participants understand how everything works.
- Consistency: the degree to which the individual submodels of the modeling method are a single entity.
- Completeness: the level at which all the necessary concepts of the subject area are presented in the prototype.
- Efficiency: The degree to which the modeling process uses resources such as time and people.
It is argued that a structural assessment for the DEMO modeling techniques revealed Q-ME deficiencies. One of them is that it does not include a quantifiable metric for expressing the quality of business modeling techniques, which makes it difficult to compare the properties of various techniques in the overall ranking.
There is also a systematic approach to measuring the nature of products, known as the complexity metric, proposed by Rossi (1996). Metamodel methods are used as the basis for calculating these parameters. Compared to the system proposed by Krogstie, measurement is more focused on the technical level, rather than on a separate model.
Authors (Cardoso, Mendling, Neuman, and Reijers, 2006) used complexity metrics to measure the simplicity and comprehensibility of a design. This is confirmed by more recent studies by Medling. He argued that without the use of quality metrics, a simple process can be modeled in a complex and inappropriate way. This, in turn, leads to a decrease in comprehensibility, an increase in the cost of servicing and, possibly, to an ineffective implementation of the process under consideration.
Model quality
The earliest developments reflected the dynamics of the process with a practical option obtained by implementing in terms of relevant concepts, available technologies, specific environments, constraints, and so on.
A huge amount of research was conducted on the quality of the models, but less attention was paid to the work itself. These questions cannot be comprehensively assessed, but in practice there are four main guidelines for this. It:
- downward quality structures;
- ascending metrics;
- empirical reviews;
- pragmatic recommendations.
Hommes said that all the basic characteristics of the quality of models can be divided into 2 groups according to their correctness and usefulness. Correctness varies from the conformity of the layout to the phenomenon, which is modeled by its syntactic rules. Modeling is also independent of the goal.
Taking into account that utility can be regarded as a model, Homms also draws an additional distinction between internal correctness (empirical, syntactic and semantic quality) and external (reliability).
In addition, a broader approach should be based on semiotics, rather than linguistics, as Krogsti did using a top-down system known as SEQUAL. It defines several aspects of quality, based on the relationships between the model, externalization of knowledge, field, modeling language and learning activities.
However, this structure does not provide methods for determining various quality levels, but is widely used for business processes in empirical tests. According to previous studies conducted by Moody using a conceptual model, new levels of quality were identified.
Three developments
- Syntactic: evaluates the degree to which the model complies with the grammatical rules of the modeling language used.
- Semantic: Find out if the application meets the user's requirements exactly.
- Pragmatic: clarifies whether the model can be sufficiently understood by all parties involved in the modeling process. That is, it should allow interpreters to use it to satisfy their needs.
As a result of the study, it was noted that the quality system was easy to use and useful for evaluating process models, however, it has limitations in terms of reliability and makes it difficult to identify defects. They led to the refinement of the structure through a subsequent study by Krogstie.
Three more quality aspects
- Physical: whether the external model is constant and accessible to its audience for understanding.
- Empirical: Whether the application is modeled in accordance with established rules regarding a given language.
- Social: Find out if there are agreements between stakeholders in the field of modeling.
So, we examined the category of process modeling. Dismantled the methods and steps known today.