The need for flexible and adaptive IT is ever more pressing as enterprises compete in global digital economies and ecosystems. To enable flexibility and adaptability of IT, one requires tools and techniques that enable co-design of IT and business. Hence, this research builds on the strategic management literature, particularly the research on dynamic capabilities, to propose a socio-technical modeling framework for designing enterprise capabilities. An agent-oriented modeling framework for understanding social and technical requirements when designing enterprise capabilities is proposed by building on conceptual modeling practices and techniques. An overview of the research design consisting of objectives, questions, and methodology is presented in this paper.
The challenge of dynamic and evolving requirements faced by enterprise IT is twofold,
the need for (1) adaptable and reconfigurable software services/systems that can adjust
to changes [1], and (2) a flexible organization that can develop, support and leverage
such systems/services [
This research started with the question of “how to architect flexible IT to enable
adaptive enterprises”. The first step in answering the question was to understand what
kinds of flexibilities are needed to design adaptive enterprises, i.e., answer the question
of “flexibility towards what”. An investigation into the literature revealed that enabling
business and enterprise evolution in response to environment dynamism is the primary
concern of flexibility [
The above answer provoked an investigation into the strategic management literature. The flexibility aspect of the research motivation narrows down the scope of the investigation to inside-out views in strategic management which directed us to the Dynamic Capability View (DCV) of the firm.
Capabilities in DCV are defined as an organization’s ability to appropriately
assemble, adapt, integrate, reconfigure and deploy valued resources, usually, in
combination or co-presence [
Fig. 1 depicts the described journey from the initial motivating research question around IT flexibility to the refined question that enterprises are dealing with on a day to day basis. Therefore, the research objective is defined as enabling enterprises, particularly managers and architects within enterprises, to answer the question of “How to design for social and technical flexibility that enables creation, management and evolution of Enterprise Capabilities?”.
Conceptual modelers and IS designers have raised the abstraction level of the
design artifacts to better understand enterprise context and design higher quality
information systems [1]. For example, concepts such as value [
To enable the design of flexible enterprise capabilities, the ability to perform analysis and answer the questions presented in Table 1, is necessary. In this research, a conceptual modeling approach is adopted to develop a framework consisting of modeling constructs, methods, and tools that intend to answer the analysis questions of Table 1.
The choice of using conceptual modeling practices is supported by the success of the
IS community in a) developing conduits that can represent and analyze technical,
business and organizational context [
The above questions that elaborate the research objectives trigger the following research questions as presented in Table 2.
of enterprise capabilities for modeling and analyzing competitiveness? How does the concept relate to other concepts within the enterprise such as services, processes and resources? How can one represent and analyze the formation of enterprise capabilities to enable answering the questions of Table 1?
Design Science Research (DSR) has become a prominent research method in both IS
engineering and IS management communities [
This thesis has adopted the DSR methodology. Throughout the research, a few rounds of DSR design cycles with feedback received from both academia and industry case studies are conducted. As an example, feedback from academia suggested the need for a holistic understanding of the notion of capability and how it is related to other modeling constructs and concepts. This feedback triggered a new design cycle. In the interest of space more in depth discussion of the design cycles are not presented in this paper, instead, we focus on elaborating the outcomes of the design iterations. 4
A modeling framework consisting of ten components as laid out in Fig. 3 is proposed in response to discussed research questions. The first component is the conceptual foundation serving as the main theoretical contribution of the thesis. It builds on an in-depth review of concepts from literature and proposes an integrated meta-model for enterprise capability and its relationships. The second component of the framework focuses on the i* based instantiation of the meta-model. The third and fourth components are practical guidelines for using and instantiating the modeling framework in the context of an enterprise. Each component is developed as part of a case study.
The next five components of the framework are analysis techniques that help decision makers investigate and answer what-if questions. The last component as depicted at the top of Fig. 3 is an overarching view and categorization of all decisions that must be made throughout the lifecycle of a capability.
In Table 3, the components are described with a specification of their purpose and contributions to answering the research questions. The last column of Table 3 focuses on the feedbacks or triggers that initiated the development of the component. The order of the components presented in the table do not describe the sequence in which they were developed.
prise Capabilities & how are they different? A socio-technical approach that enables reasoning on capability formation is needed 4 5 8 9
Alternative Kinds & Reasoning Guidelines
Modeling Approach Bottom-Up Modeling Approach Constructs Methods Constructs Method
Instantiations in DSR are used to demonstrate the usage of an approach and validate the contribution of the research. In Table 4, the series of instantiations, their purpose, and publication venues are presented. The final item in the table refers to an ongoing case study in evaluating the usage of the framework.
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satisfaction of persona requirements o identification of tool and platform bias o identify and propose alternatives for shortcomings
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In the remainder of this section a brief overview of the components of the framework is presented. 4.1
The integrated meta-model for the modeling framework is based on different conceptual viewpoints coordinated through the notion of enterprise capabilities as outlined in Fig. 4. The views enable describing what forms a capability, how it relates to other enterprise concepts and how one can determine the value of the capability in the ecosystem. Enterprise capabilities (EC) are defined as intentional combination of firmspecific assets, organizational routines (business processes), and human knowledge (skillset/know-how) that take advantage of complementary relations and are created and evolved overtime through social collaboration and learning. Examples of enterprise capabilities we have investigated as part of our instantiations are “Enterprise IT Risk Management”, “Customer Interaction Management”, “Business Process Management”, “Social Media Analytics”, and “Integrated Information Provisioning”.
The proposed meta-model represents the confluence of the results from two domains of strategic management and information systems engineering. It serves as the keystone of a socio-technical approach for developing information systems and has been validated in more than three case studies. Because of such validations, the meta-model has been extended particularly in the social view as presented later in Fig. 9. 4.2
Building on the variety of research efforts on using capabilities, a capability modeling practice is proposed consisting of six maturity stages as presented in Fig. 5. The initial stage is to use capabilities as blueprints for communicating investment priorities. At stages two and three the focus is on enabling representation of capability formation and its alternative evolution paths. At stages four and five, the capability concept is used to reorganize the enterprise and enable design for flexibility, while exploring different configurations of roles and responsibilities. At stage six in response to demands of ecosystems, the capability concept is used to enable re-design and re-alignment of the enterprise and its service propositions.
For each of the stages, a set of questions are identified that will guide a) researchers in developing methods and techniques for reasoning and decision making, and b) practitioners in selecting appropriate methods and performing required analysis for capability design.
This component consists of three parts a) justification of applying an agent-oriented modeling paradigm, b) guidelines to model and reason on different aspects of capability formation, and c) the formal specification that enables instantiating the meta-model using the i* framework. Without these key components, the analysis techniques that help decision makers and designers will not be applicable.
There are five characteristics evident in the definition of EC as reviewed in section 4.1.
(1) ECs are intentionally built and evolved in accordance with enterprise strategy while
striving for survival and relevance at enterprise scale [
An agent-oriented modeling approach is adopted to model and represent enterprise capabilities and its characteristics. To this end, in this research ECs are represented as specialized i* actors. The ability of the i* framework to represent goals, means-ends, quality attributes, contributions, and tradeoffs are beneficial in capturing the intentionality and internal structure of capabilities. The i* dependencies and actor associations empower understanding of the social and complementary aspects of ECs. An example of a capability represented with the i* language is presented in Fig. 6. This figure illustrates how goals, resource, business processes, capabilities, and their relationships are instantiated using i*.
Fig. 7 demonstrates the social context in which a capability is built in. The figure focuses on instantiating the relationships among social actors and capabilities while capturing different desires and norms of teams within the organization.
This part of the component focuses on guidelines for modeling and reasoning on the formation of capabilities that will empower understanding of (1) why a capability is needed, (2) how it is achieved, (3) how it fits within the organizational and social setting of the enterprise, and (4) what relationships are required for its success. Addressing these requirements satisfy the second maturity stage presented in Fig. 5.
The guidelines enable a) explication of choices for coupling enterprise-specific resources and processes that differentiate emerging quality attributes, b) expression of the social and organizational setting to empower analyzing the influences and interests of multiple stakeholders, and c) representation of interdependent networks of capabilities to enable orchestration of design choices among capabilities, information systems and organizational structure(s). In Fig. 8, an example of complementary relationships among capabilities and their impact on alternative are presented.
The third part of this component focuses on a formal description of the extended i* language. A set of guidelines accompany the meta-model presented in Fig. 9 to enable instantiating ECs. The details of the guidelines to perform the instantiation are left for future publications. 4.4
Supporting analysis techniques are required to understand consequences of decisions
about ECs. An in-depth review of each of the analysis techniques is beyond the scope
of this paper, but a brief overview of each one is discussed:
1. Base i* Qualitative Evaluations: Uses i*to analyze and infer the degree of which
intentions are satisfied within and beyond the boundary of an actor.
2. Reasoning on Alternatives [
Ongoing activities to finalize the proposed framework are outlined as follows: • Organizing findings from case studies into playbooks that serve as “Top-Down Guidelines & Methods” and “Bottom-Up Guidelines & Methods” to facilitate the modeling activity. • Finalizing an ongoing case study which demonstrates the ability of the framework to appropriately navigate from high-level capabilities and drill down into the analysis as necessary. • Applying minor changes and updates received from feedbacks of the DSR design cycle for the causal modeling technique.
The following components are planned for future iterations of the framework beyond this thesis as outlined in dark color and white text in Fig. 10. The two new components on the right intend to enable integration of other researchers’ analysis techniques and design patterns into the proposed modeling framework with tool support. The three analysis techniques at the top focus on the external relationships of ECs and how one should evaluate their value. The two components in the lower part of the figure focus on conceptual and practical aspects of modeling enterprise structure. The added component on the left focuses on decisions on bundling service propositions into platforms.