Modeling Application Landscapes as Dynamic Systems Master’s Thesis | SS2013 Supervisor: Prof. Dr. Florian Matthes Advisor: Alexander W. Schneider, M.Sc. Author: Maximilian Burger, B.Sc. Master's Thesis - Maximilian Burger September 17, 2018

1. Motivation: the importance of behavior Not an analogy 1:1 to ALs but similar problem -> system theory We know the structure of a cell, its parts and the individual roles of the parts Cells are open systems with interaction at the border with the environment, including other cells We also know the structure of the plant with the interplay of the different cells But the behavior is also important to understand the outcome of changes e.g. What happens, if the sun starts to shine? does it lean towards it, does it grow, does it do photosynthesis or die because of lack of water? Models of ALs have no behavioral aspects so far – only the structure. Sophisticated approaches may reach the “middle” level, where interplays, roles etc. are depicted correctly. Still it is a snapshot (as-is or to-be) and not seen over time And what if the requirements, environment, the structure changes – how will it behave and how can management be supported? Therefore, first the definition of behavior in system theory -> next slide Master's Thesis - Maximilian Burger September 17, 2018

2. Behavior in system theory Each individual is thought of as consisting of a structure or complex of individuals of the order immediately below it: atoms are an arrangement of protons and electrons, molecules of atoms, cells of molecules, plants, mammals and men of cells, social organizations of men. The "behavior” of each individual is "explained" by the structure and arrangement of the lower individuals of which it is composed, or by certain principles of equilibrium or homeostasis according to which certain "states" of the individual are "preferred." Behavior is described in terms of the restoration of these preferred states when they are disturbed by changes in the environment. -> behavior is driven by the environment of the system and its changes Boulding (1956) Master's Thesis - Maximilian Burger September 17, 2018

3. Understanding the environment of the AL variability normal state scarce resources location • language spoken Competition stock market crash elections raw materials workers corporate form enterprise policy Organization immediate regulations external server crash knowledge budget Application Landscape new business model switch to SOA work locations • operating systems • administrator • steering committee diversity of services and goods on the market competitors Not sufficient to say positive or negative influence. General model of the environment in system theory: Bossel and classification into 6 dimensions Problem: Behavior still not explainable but now we can differentiate -> orientor theory incomes globalization • suppliers • lawyers change other systems variety Master's Thesis - Maximilian Burger September 17, 2018

3. Understanding the environment of the AL Normal State Variability Scarce Resources Existence Security Effectiveness Adaptivity Freedom Orientor theory: introduction of one orientor per environmental influence interplay: opposing orientors Regard Change Variety Other Systems Master's Thesis - Maximilian Burger September 17, 2018

3. Understanding the environment of the AL Existence Security Effectiveness minimum level increased level minimum satisfaction remaining flexibility minimum satisfaction to remain viable increase in one orientor may lead to decrease of opposite. Max increased: 3 Adaptivity Freedom Regard Master's Thesis - Maximilian Burger September 17, 2018

4. System of systems approach for ALs Possible breakdown of an application landscape by: • business processes, • organizational units, • functional areas, • technology stacks, • plants, • countries, • products, • markets, • distribution channels. minimum level increased level Plant 1 Plant 2 Plant 3 Plant n Overall Environment Overall Orientor Manifestation Existence Security Regard Freedom Adaptivity Effectiveness System theory: subsystems exhibit self-organization and non-linearity -> Not possible to manage a system by one hand of god. -> Manage in the system -> provide the best possible conditions (example IT organizations) -> guidance and allow self-organization (example EA principles) Master's Thesis - Maximilian Burger September 17, 2018

5. Applying orientor theory I: IT organization BU n BU 2 BU 1 CEO BU n BU 2 BU 1 CEO IT BU n BU 2 BU 1 CEO IT GB Centralized IT Organization Decentralized IT Organization Federal IT Organization Master's Thesis - Maximilian Burger September 17, 2018

5. Applying orientor theory II: EA principles Guidance for subsystems: two examples of TOGAF EA principles: Responsive Change Management Changes to the enterprise information environment are implemented in a timely manner. Common Use Applications Development of applications used across the enterprise is preferred over the development of similar or duplicative applications which are only provided to a particular organization. Responsive Change Management: Realizing the need to change and implement solutions in a timely manner, daily routines should not be interrupted. Transitions shall occur swiftly and have minimal effects on the usual business. Common Use Applications Less redundancy. Subsystems should not develop applications on their own if the whole system, or enterprise, may need or depend on the same functionality. -> standardized processes, less conflicting data, less development costs, less costs of change Master's Thesis - Maximilian Burger September 17, 2018

5. Applying orientor theory II: EA principles Existence Effectiveness Freedom Business Continuity Common Use Applications Data is Shared Business Continuity Responsive Change Management Common Use Applications IT Responsibility Technology Independence Technology Independence IT Responsibility Compliance with Law Compliance with Law Data is Shared Overall Orientor Satisfaction Responsive Change Management Technology Independence Compliance with Law IT Responsibility Data is Shared Compliance with Law Common Use Applications Business Continuity 7 exemplary principles mapped to orientors -> clustering and applying principles to subsystems, not to the whole system. Go back to slide 7 (SoS) and show, that „plant 2“ and „plant n“ may need the same principles while 1 and 3 are different. Technology Independence Data is Shared Responsive Change Management Responsive Change Management Regard Adaptivity Security Master's Thesis - Maximilian Burger September 17, 2018

6. Summary Examination of application landscapes’ dynamics with system theory approach. Compare existing behavioral models. Describe environmental influences and introduce orientor theory to application landscapes. Outline system capabilities for orientor satisfaction. Use system of systems approach together with complex adaptive systems to break down structure and increase manageability. Examples of applying orientor theory: aggregate orientor stars of subsystems to determine best possible conditions, determine effects on orientors and interplay when applying measures and controls to manage in the system. Provide a base and motivations for further research. Compare existing behavioral models (causal loop diagrams, stock and flow diagrams, UML activity diagram) Describe system capabilities for orientor satisfaction (e.g. business analytics for regard of other systems, knowledge management for effectiveness) Aggregate orientor stars of subsystems to determine best possible conditions (exemplary with forms of IT organization) Determine effects on orientors and interplay when applying measures and controls to manage in the system (exemplary with EA principles) Provide a base and motivations for further research (clustering inner core with security outer core with freedom, other examples of use, introduce KPIs and maturity models to determine orientor satisfaction, practical use, evaluation) Master's Thesis - Maximilian Burger September 17, 2018

References Boulding, K. E. (1956). General systems theory—the skeleton of science. Management science, 2(3), 197–208. Bossel, H. (1994). Modeling and simulation. AK Peters Wellesley, MA. Buckl, S. (2011). Developing Organization-Specific Enterprise Architecture Management Functions Using a Method Base. PhD Thesis, Technische Universität München. Hevner, A.R. (2007): A three cycle view of design science research. In: Scandinavian Journal of Information Systems, Vol. 19 (2007) No. 2. Hevner, A.R.; March, S.T.; Park, J.; Ram, S. (2004): Design science in information systems research. In: Mis Quarterly, Vol. 28 (2004) No. 1, pp. 75-105. Offermann, P.; Levina, O.; Schönherr, M.; Bub, U. (2009): Outline of a design science research process. In: Proceedings of the 4th International Conference on Design Science Research in Information Systems and Technology (DESRIST '09). ACM, New York, NY, USA, Article 7, pp. 1-11. Lankhorst, M. (2005). Enterprise architecture at work: modelling, communication and analysis. Springer. Kandjani, H., Bernus, P., & Nielsen, S. (2013). Enterprise architecture cybernetics and the edge of chaos: Sustaining enterprises as complex systems in complex business environments. In 46th hawaii international conference on system sciences (HICSS 2013)(p. 3858–3867). Master's Thesis - Maximilian Burger September 17, 2018

Backup Master's Thesis - Maximilian Burger September 17, 2018

6. Summary Examination of application landscapes’ dynamics with system theory approach Compare existing behavioral models (causal loop diagrams, stock and flow diagrams, UML activity diagram) Describe environmental influences and introduce orientor theory to ALs with several levels Use system of systems approach together with complex adaptive systems to break down structure and increase manageability Describe system capabilities for orientor satisfaction (e.g. business analytics for regard of other systems, knowledge management for effectiveness) Aggregate orientor stars of subsystems to determine best possible conditions (exemplary with forms of IT organization) Determine effects on orientors and interplay when applying measures and controls to manage in the system (exemplary with EA principles) Provide a base and motivations for further research Master's Thesis - Maximilian Burger September 17, 2018

Thesis Research Questions: RQ 1: Does understanding the application landscape’s dynamics increase its manageability? RQ 2: Where and to which degree is the application landscape’s behavior influenceable? RQ 3: Which means are applicable to model dynamics of and within application landscapes? Methodology: Design Science Outcomes: Examine existing behavioral models; Develop a model to describe environmental influences; Show applicability with examples of use; Provide a base and motivations for further research. Scope: Environmental change and software / EA evolution have an impact on behavior but are not meant by the term dynamics in this context. Dynamics and behavior can be found in the whole EA, but this thesis is about application landscapes only. Master's Thesis - Maximilian Burger September 17, 2018

7. Future work Increase measurability of orientor theory: change scale from ordinal to ratio scale, introduce (existing) indicators and maturity models and map to orientors, determine system capabilities and use existing measures (e.g. ITIL compliance). Further examine divisability (system of system approach) and seek the most suitable level of breaking down the AL into subsystems to measure orientor satisfaction and apply controls, the practicality of applying different measures on different levels, the possibility to cluster subsystems (e.g. inner core with increased security). Combine with less abstract models on behavior such as Causal Loop Diagrams, Stock and Flow Diagrams. futher future work: use orientor theory in practice and evaluate with firms apply orientor theory to the whole EA Master's Thesis - Maximilian Burger September 17, 2018

Layers from EA Structure to IT Success KPIs KPIs Goals Implies Implies Alignment Business Process Support Business Process Support Implies Induce Implies Behavior System Dynamics System Dynamics Impacts Impacts Structure Static AL Architecture Static AL Architecture Changes as-is to-be t Master's Thesis - Maximilian Burger September 17, 2018

Capabilities to determine orientor satisfaction Existence Security Effectiveness Monitoring ITSM ITIL IT Operations Risk management Optimized CPU Redundancy PPM Continuity management Knowledge management Skilled employees Project management Flexible structures Diversity of workforce Open culture Expandability Decoupling Modularity Diversity of workforce Decentralized decisions Data storage Analytics Monitoring Sensors Adaptivity Freedom Regard Master's Thesis - Maximilian Burger September 17, 2018

Understanding the environment of the AL variability normal state scarce resources location • language spoken • attitudes social and economic background political and legal environment Competition stock market crash jump in oil price unexpected competitor elections laws water electricity raw materials loans workers corporate form enterprise policy security • building associates • size Organization immediate regulations string of layoffs external server crash customer data loss knowledge time budget Application Landscape new business model switch to SOA outsourcing inventions M&A employee’s different skills and personalities ways of processing locations of work • devices • OS various sources of materials and energy competitors customers diversity of services and goods on the market • marketing IT management user • administrator server • steering committee incomes living conditions geographical distribution globalization suppliers • competitors • bankers • customers • city officials • lawyers change other systems variety Master's Thesis - Maximilian Burger September 17, 2018

Further definitions Enterprise Architecture (EA) is a coherent whole of principles, methods, and models that are used in the design and realization of an enterprise’s organizational structure, business processes, information systems, and infrastructure. (Lankhorst 2005) EA management (EAM) is a continuous management function seeking to improve the alignment of business and IT and to guide the managed evolution of an organization. Based on a holistic perspective on the organization the EA management function is concerned with the management, i.e., the documentation, analysis, planning, and enactment, of the EA. (Buckl 2011) A system consists of a boundary delineating the environment from the system parts, an interface defining the interaction and behavior of the system and an inside setup with the structure, states and state transitions. (Broy 2012) • a system boundary, defining what is part of the system itself and what is outside of the system • an interface (determined by the system boundary), defining the kinds of interaction between the system and the environment is possible (static/syntactic interface) the behavior of the system seen from outside (interface behavior, dynamic interface, interaction view) • an inside setup consisting of the structure and division in subsystems (architecture) the states and state transitions (state view). • The interaction and state views are build upon a data model. • Views can be documented by means of feasible models. Master's Thesis - Maximilian Burger September 17, 2018

Classification of Systems wwwmatthes.in.tum.de Classification of Systems © sebis Adopted from GablerVerlag (2013) Master's Thesis - Maximilian Burger September 17, 2018 070726-sebis-Lehrstuhl-SoftwareCartography-SAP

Co-evolving System Path Kandjani et al. (2013) Master's Thesis - Maximilian Burger September 17, 2018

Other diagrams on behavior: UML activity diagram wwwmatthes.in.tum.de Other diagrams on behavior: UML activity diagram © sebis Master's Thesis - Maximilian Burger September 17, 2018 070726-sebis-Lehrstuhl-SoftwareCartography-SAP

Other diagrams on behavior: Causal Loop Diagram wwwmatthes.in.tum.de Other diagrams on behavior: Causal Loop Diagram © sebis Master's Thesis - Maximilian Burger September 17, 2018 070726-sebis-Lehrstuhl-SoftwareCartography-SAP

Design Science Research wwwmatthes.in.tum.de Research Methodology © sebis Environment (Application Domain) People Organizational Systems Technical Systems Problems & Opportunities Design Science Research Knowledge Base (Foundations) Scientific Theories & Methods Experience & Expertise Meta-Artifacts (Design Products & Design Processes) Build Design Artifacts & Processes Evaluate Relevance Cycle Requirements Field Testing Design Cycle Rigor Cycle Grounding Additions to KB Own illustration, based on Hevner (2007) Master's Thesis - Maximilian Burger September 17, 2018 070726-sebis-Lehrstuhl-SoftwareCartography-SAP

Research Methodology wwwmatthes.in.tum.de © sebis Hevner et al. (2004) Master's Thesis - Maximilian Burger September 17, 2018 070726-sebis-Lehrstuhl-SoftwareCartography-SAP

Determining Orientor Satisfaction for IT Organization: Centralized Master's Thesis - Maximilian Burger September 17, 2018

Determining Orientor Satisfaction for IT Organization: Decentralized Master's Thesis - Maximilian Burger September 17, 2018

Determining Orientor Satisfaction for IT Organization: Federal Master's Thesis - Maximilian Burger September 17, 2018

Backup from inaugural presentation Master's Thesis - Maximilian Burger September 17, 2018

Complexity Surplus Master's Thesis - Maximilian Burger September 17, 2018

Possible Components of the Model Elements Application Business Process Person Project User Owner Developer Other Stakeholder Links supports is viable to uses communicate needs coordination with .. about .. develops excludes includes waits for authorizes depends on States Application Project running, maintenance, expiring, defect, deprecated Business Process Person initiated, started, declined, finished initiated, supported, deprecated owning, developing, using, rejecting Eine Person kann z.B. durch Vererbung spezifiziert werden oder durch den Status, oder durch entsprechende Beziehungen (Links) Functions create (element) activate (element) assign (element, state) passivate (element) link (element1, element2, link) assert (element, state) delete (element) unlink (element1, element2, link) change (element, state) Master's Thesis - Maximilian Burger September 17, 2018

Research Schedule Problem identification Solution design Evaluation Thesis & Review Problem Model design Relevance Model Applic. Methodology Grounding Th. Rigor Cycle Presentation Evaluation Inaugural presentation Final presentation Introduction Theory and Concepts Least c,u Model Future Work Related Work Possible Models Results & Evaluation Research Questions Benefits & Limitations Methodology Use Cases Conclusion Proceeding Artifact / Thesis Presentation Own illustration, based on Offermann et al. (2009) Master's Thesis - Maximilian Burger September 17, 2018