=Paper=
{{Paper
|id=Vol-2097/paper8
|storemode=property
|title=Relaxing Modeling Criteria to Produce Genuinely Flexible, Controllable, and Usable
Enterprise Modeling Methods
|pdfUrl=https://ceur-ws.org/Vol-2097/paper8.pdf
|volume=Vol-2097
|authors=Dominik Bork,Steven Alter
|dblpUrl=https://dblp.org/rec/conf/emisa/BorkA18
}}
==Relaxing Modeling Criteria to Produce Genuinely Flexible, Controllable, and Usable
Enterprise Modeling Methods==
https://ceur-ws.org/Vol-2097/paper8.pdf
Relaxing Modeling Criteria to Produce Genuinely Flexible,
Controllable, and Usable Enterprise Modeling Methods
Dominik Bork1 and Steven Alter2
Abstract: Enterprise modeling (EM) applies abstraction in creating simplified representations
of complex realities. Unfortunately, both the realities and the task of creating valid conceptual
representations bring daunting challenges. Complexity is increasing, e.g. the transition of conventional
production towards product-service systems operating in heterogeneous enterprise ecosystems.
Simultaneously, modeling methods and tools tend to be formal and inflexible, and often are designed
for automated model processing rather than for helping business professionals understand business
situations. The result is the current, unsatisfying state of enterprise modeling, in which models can be
developed and used directly only by modeling experts and are largely impenetrable to non-experts.
This paper presents a set of principles that suggest directions for progress toward genuinely flexible,
controllable, and usable enterprise models. The principles accept the relaxation of some expectations
about enterprise modeling while trying to maintain rigor and completeness in models.
Keywords: Enterprise Modeling; Modeling Principles; Modeling Methods
1 Mismatch between Modeling Capabilities and Modeling Goals
Attention to rigor and completeness is a central tenet of systems analysis and design
(SA&D), requirements engineering, enterprise modeling, and conceptual modeling in
general. For example, Bork and Fill [BF14, p. 3400] speak of representing “static and
dynamic phenomena of systems prior to their implementation,” which typically requires
formal models that are precise and complete. A long term vision of translating directly
and automatically from conceptual models and requirements specifications to executable
code has driven passionate IS research debates focusing on the completeness and general
adequacy of ontologies, metamodels, and reference models.
The benefits of enterprise models often come at the cost of complexity and inflexibility due
to formalization and rigor needs of modeling methods and supporting tools. In contrast,
domain experts often perceive the business in imprecise ways and may or may not have the
expertise to capture their knowledge in a conceptual model. Furthermore, modeling tools
sometimes constrain intuitive specification of externalized knowledge by forcing users to
express themselves in modeling languages that are unfamiliar or difficult to use.
1 University of Vienna, Research Group Knowledge Engineering, Waehringer Street 29, 1090 Vienna, Austria
dominik.bork@univie.ac.at
2 School of Management, University of San Francisco, San Francisco, USA, alter@usfca.edu
47 Dominik Bork and Steven Alter
A position paper by Sandkuhl et al. [Sa18] encourages transforming EM from an elite
discipline performed by experts towards a vision of "modeling for the masses". An important
element of their future research agenda is Softened Requirements to Completeness, Coherence
and Rigor. This paper builds on that goal by proposing a set of principles that might be
incorporated in an EM approach for creating genuinely flexible, controllable, and usable
models. Application of those principles probably would require softening some criteria for
model quality that the EM community takes for granted. The question at hand is whether the
proposed principles would generate desired benefits without sacrificing important values
and goals of the EM community.
2 Principles for Relaxed Enterprise Modeling
Our proposed EM principles aim at a compromise between important but divergent
approaches to EM. Emphasizing rigor and correctness of models and modeling methods,
Karagiannis and Kühn [KK02] say that the foundations of formal modeling include the
modeling language (comprising its semantics, syntax, and notation), modeling procedure,
and mechanisms & algorithms. In contrast, Sandkuhl et al. [Sa18] argue for democratizing
EM and seem willing to accomplish that through approaches such as consolidating semi-
formal models produced by business professionals. This paper’s compromise between those
two directions maintains the idea of rigorous modeling but proposes principles that relax
or even omit some built-in assumptions of current EM methods. We may find that most
principles can co-exist while some of them prove mutually contradictory in practice.
Tab. 1: Principles for Relaxed Enterprise Modeling
Principle Rationale
Abstraction Models are abstractions of other things and therefore are not equivalent
to those things. The structure and behavior of a model is not equivalent
to the structure and behavior of whatever is being modeled. Increasing
the level of detail and precision in a model will not generate something
that is equivalent to whatever is being modeled.
Priorities Details of models should be driven by the content being represented
and the purposes of the model’s users. Details of models should not be
driven by a need to satisfy the requirements of a modeling technique or
metamodel or by the expectations or preferences of the EM community.
Usability Principles
Controll- Users should be able to control a model and view it from different
ability perspectives and at different levels of detail. Different users might have
quite different goals ranging from attaining a basic understanding of a
business situation through using simulation or other automated methods
to predict how a system will behave.
Continued on next page
Relaxing Modeling Criteria for Enterprise Modeling 48
Tab. 1 – Continued from previous page
Principle Rationale
Zoomability As with online maps, it should be possible to visualize and explore the
entire system under study and any part of it by changing the focus and
level of detail, e.g., from highly aggregated to highly detailed. Using
different zoom levels to slide between different levels of detail enables
interactive exploration of models.
Cognitive Modeling methods, notations, and tools should not impose extraneous
manage- cognitive load [Sw94]. Modeling tools should help modelers focus on
ability the content that they are concerned with and should minimize additional
attention required to understand or use tools or notations for representing
and displaying that content.
Content Principles
Minimum One of Cherns’ [Ch87] sociotechnical principles says that designers and
critical modelers should specify only what is necessary and should not specify
specifica- unnecessary details. In a broader sense, over-specification is futile because
tion the frequent occurrence of noncompliance and workarounds [Al14].
Design Another of Cherns’ sociotechnical principles says that the design of
incomple- a sociotechnical system is always incomplete because sociotechnical
tion systems (including processes, participants, goals, etc.) typically adapt in
response to changes in the environment that surrounds it.
Complete- Simulation and code generation require complete models. Incomplete mod-
ness linked els are adequate for representing vague or incomplete information [GP18],
to purpose or for supporting communication among stakeholders.
Precision Some aspects of a model or modeling language can be very precise while
linked to other aspects can be relatively vague. E.g., an imprecise model of a
purpose business process may be useful before filling in all intermediate events
and task types.
Modeling Principles
Domain A model’s domain should be specified clearly. The domain of many
specificity models is somewhat unclear. For example, some models do not include
the characteristics of human participants who produce a system’s output.
Semantic Concepts in a model or modeling language should be defined clearly. That
clarity might seem obvious until one looks at models of service in which the
concept of ’service’ itself is not defined clearly.
Adaptable In contrast to established beliefs, it is possible for a model to be useful
syntax even if it does not have a formal syntax. In co-evolutionary contexts,
syntactic concepts can be defined while modeling [CA13, WSG17].
Flexible In certain scenarios, it is important for modelers to introduce specific
notation notations while modeling [Bu18].
Continued on next page
49 Dominik Bork and Steven Alter
Tab. 1 – Continued from previous page
Principle Rationale
Imprecise Imprecision is almost inevitable when typical domain experts create
semantics conceptual models. Models should not try to be more precise than domain
experts’ imprecise knowledge about the system under study [GP18].
Flexible It is possible to produce useful models without using a structured modeling
modeling procedure. Just as one might fill out a jigsaw puzzle by moving from the
procedures outside toward the center, it might also be possible to fill out the puzzle
from the center to the outside.
Flexible Controlled flexibility should be reflected in modeling tools, which should
Tooling adapt to a user’s objectives. Rigorously specified fixed metamodels and
metamodel constraints are needed in some cases. In other cases, modelers’
creativity and intuitions call for bypassing or augmenting fixed structures.
Modularity Models should consist of modules whose interactions and internal ele-
ments can be named and described separately. Modularity makes it easier
to describe the structure of a model and to set up the structure of a model
before filling in the details.
Module- In a modular structure, concepts that are relevant to one module might
specific not be relevant to another module. Therefore it should be possible for
semantics different modules to have different semantics.
Module- In a modular structure, any syntax that might be relevant to one module
specific might not be relevant to another module. Therefore it should be possible
syntax for different modules to be modeled using different syntax.
Optional Modules are encapsulated but visibility to other modules or to users is
trans- optional, and ranges from glass box to black box.
parency
3 Concluding Remarks
Research in conceptual modeling and EM focuses primarily on the precise and unambiguous
representation of all relevant aspects of a system under study. Construction of these models
is supported by modeling tools and methods that are not well suited to be used by domain
experts and other stakeholders who lack modeling expertise. Thus, despite the wide adoption
of EM and its strong contribution to the analysis and design of complex systems, its rigor
and formality present obstacles to theory-driven and creativity-employing techniques of the
IS discipline.
Each principle proposed by this paper presents a research challenge along a path toward
enabling people who are not EM experts to participate fully in EM. Each principle can
be used in describing or evaluating existing EM methods and in thinking about new EM
methods, especially methods that might apply IS theories such as work system theory or
Relaxing Modeling Criteria for Enterprise Modeling 50
design thinking. Those and other practical approaches bring some degree of rigor while
calling for relaxation of modeling constraints related to syntax, semantics, and notation that
are built into existing EM methods and tools.
We intend to investigate practicalities of these principles in future research. We hope to
focus special attention on tool-related implications of these principles within an overarching
goal of maintaining a reasonable degree of rigor and formality while also allowing domain
experts and other stakeholders to participate more fully in enterprise modeling.
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