Architecting the Enterprise to Leverage a Confluence of Emerging Technologies

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Yu & Lapouchnian ACET workshop at CASCON 2013

Yu & Lapouchnian ACET workshop at CASCON 2013

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  • 1. Architecting the Enterprise to Leverage a Confluence of Emerging Technologies Eric Yu & Alexei Lapouchnian Faculty of Information and Department of Computer Science University of Toronto First Int’l Workshop on Advancement from Confluence of Emerging Technologies (ACET 2013) – at CASCON 2013, Markham, Ontario, Canada Nov 19, 2013
  • 2. A Confluence of Emergent Technologies  Mobile and social network  Low-cost sensor networks  Cloud and service-oriented computing  Big data & advance analytics  How to leverage this confluence of emerging technologies? [ACET workshop CfP, @CASCON’13] E.Yu 2
  • 3. 3
  • 4. Relentless disruptive technological advances  [Manyika Dobbs Chui 2013 McKinsey Global Inst.] E.Yu 4
  • 5. IT-enabled business trends  E.Yu [Chui Bughin 2013 Ten-IT enabled business trends for the decade ahead. McKinsey] 5
  • 6. [HBR Oct 2012] 6
  • 7. Momentous Shifts  Dramatic rise of “sense & interpret” technologies   The (even more) crucial role of data and software in organizations 7 ACET 2013, Nov 19, 2013
  • 8. BDA is revolutionizing “sense & interpret” Minutes, Hours, Days Human-scale Act Decide Strategize Interpret Visualize Data Seconds Machine-scale 8
  • 9. Previous rounds of the Digital Revolution gave us powerful “execution” technologies Act Decide Strategize Conception Weeks, months Human-scale Requirements Design Interpret Visualize Data Construction Operation Seconds Machine-scale 9
  • 10. Closing the loop Minutes, Hours, Days Human-scale Act Conception Decide Weeks, months Human-scale Requirements Strategize Design Interpret Construction Visualize Data Seconds Machine-scale Performance monitoring External environment. sensing Operation Seconds Machine-scale  Inevitable pressure for IT development/evolution/alignment to occur on same time scale as BDA/BI sense-interpret-decide-act cycle.  Increasing drive towards machine-scale 10
  • 11. Momentous shifts  Dramatic expansion of sense-&-interpret capabilities  (Newly powerful) sense-&-interpret technologies + (already powerful) execution technologies => more responsive, adaptive organizations  Adaptive loops will shift (from human-scale) towards machine-scale, (from design-time) towards run-time. 11 ACET 2013, Nov 19, 2013
  • 12. What s/w architectures and s/w engineering processes will enable much greater adaptiveness?  Legacy systems and traditional s/w engineering processes introduce many rigidities (barriers to change)  Many emerging s/w technologies enable greater flexibility and potential machine-scale adaptation          Service-oriented computing Cloud computing BPMS Process-aware IS Context-aware IS Self-adaptive software systems Personalization, customization Agent-based systems …  Software processes and software architectures are both critical for achieving enterprise adaptiveness and responsiveness  They need to be analyzed within same conceptual framework 12
  • 13. What abstractions will help us conceptualize the adaptive enterprise enabled by the confluence of emerging technologies?  current modeling techniques (e.g., BPMN) are inadequate for dealing with  ongoing change, multi-scale dynamics  global scale, enterprise-wide complexity E.Yu 13
  • 14. Illustration: telecom eTOM operations processes [Ronco 2002] 14
  • 15. Illustration: insurance IBM WebSphere Business Services Fabric industry content packs. http://www.ibm.com/developerworks/webservices/library/ws-cbsdev/ 15
  • 16. Enterprise Architecture Frameworks rely on modeling Zachman TOGAF Archimate Roles and actors Layered Architecture Business layer Client Insurant ArchiSurance Insurer External business services Customer information service Claim registration service Claims payment service Damage claiming process Registration Valuation Acceptance Payment External application services Customer administration service Claims administration service Payment service Application components and services Claim information service Customer information service Application layer CRM system Policy administration Financial application External infrastructure services Claim files service Customer files service Infrastructure zSeries mainframe Technology layer DB2 database Sun Blade iPlanet app server 21 Financial application EJBs 16
  • 17. Desirable Modeling Framework Features  Modeling of feedback loop elements – sensing, interpreting,      17 decision making, action Numerous dynamic, adaptive processes operating at different time scales and scopes, w/ different rates of change Design-time and run-time activities represented uniformly in same model Output of some process can be a design of another process Barriers to change (rigidities) – representation and analysis … ACET 2013, Nov 19, 2013
  • 18. Research Agenda Conceptual Modeling for a Complex and Dynamic World  Expressiveness  Causal relations – producing change; closed-loop adaptation  Scoping – in space, time, granularity, design-time vs. run-time, …  Architecture – stability and flexibility (vs. rigidity)  Goals and intentionality  Scenarios  Agent-orientation – localized decision making, freedom & constraints  Uncertainty, emergence, autonomy, alignment  Dynamic-static (process-product) interplay  Language, analysis and design techniques  Usage methodology and tools E.Yu  Empirical grounding and evaluation 18
  • 19. Intellectual sources  From many disciplines and areas…  Complex adaptive systems [Dooley]  Dynamic capabilities [Teece]  Organizational learning [Argyris]  Sensemaking [Weick]  Systems dynamics [Forrester] [Sterman]  Control systems theory  Adaptive software systems [Cheng]  Timeline variability in software product lines [Svahnberg Gurp Bosch]  … 19
  • 20. Illustrative example: Supply chain management 20 ACET 2013, Nov 19, 2013
  • 21. Supply Chain Management  Supply Chain Management (SCM) Definitions  SCM is the management of the flow of goods. It includes the movement and storage of raw materials, work-in-process inventory, and finished goods from point of origin to point of consumption. [Wikipedia]  SCM encompasses the planning and management of all activities involved in sourcing and procurement, conversion, and all logistics management activities. [Council of Supply Chain Management Professionals]  Management of material and information flow in a supply chain to provide the highest degree of customer satisfaction at the lowest possible cost. [BusinessDictionary.com]  SCM Components: Suppliers, distributors, transportation & logistics companies, etc. 21 ACET 2013, Nov 19, 2013
  • 22. SCM Characteristics  Extended Enterprise  Suppliers, Distributors, Transport, Logistics, etc.  Each company focuses on its core competencies  Goal: Collection of best-in-class partners  Growing Importance due to  Competition, globalization, outsourcing, etc.  Growing Complexity  Extended geography, reduced control, offshoring, shorter product lifecycles  Desired Characteristics  Reliability, responsiveness, flexibility, minimal cost, customer satisfaction 22 ACET 2013, Nov 19, 2013
  • 23. Emerging Technologies for SCM  Sensor Networks  Track location, temperature, humidity, light exposure  Transmit info in real-time  Increase in sensing granularity (e.g., container → pallet)  Everything-as-a-Service  Dynamically recruit partners, assemble supply networks  Easily replace suppliers and other partners  Affordable per-use payments vs. acquisition of capacity  Ability to rent out excess capacity  Big Data Analytics  Real-time visibility into the supply chain performance  Ability to deal with the ever-growing data stream 23 ACET 2013, Nov 19, 2013
  • 24. Multiple Levels of SCM Processes  Process A – Produce Sourcing & Delivery 24 ACET 2013, Nov 19, 2013
  • 25. Multiple Levels of SCM Processes  Process A – Produce Sourcing & Delivery  Limited variability for customization and to handle breakdowns, emergencies Limited Variability 25 ACET 2013, Nov 19, 2013
  • 26. Multiple Levels of SCM Processes  Process A – Produce Sourcing & Delivery  Limited variability for customization and to handle breakdowns, emergencies  Fixed context, boundary from higher-level processes Context Limited Variability 26 ACET 2013, Nov 19, 2013
  • 27. Multiple Levels of SCM Processes  Process B – Monitors, Analyzes, and Redesigns produce delivery Process A  Monitors multiple instances of A, periodically redesigns it  Improves effectiveness/efficiency of Process A  Provides context/boundary for A 27 ACET 2013, Nov 19, 2013
  • 28. Multiple Levels of SCM Processes  Process C – improves supply chain across many categories of goods for a distributor company  Controls B (and similar processes for other product categories) based on:  Its current performance  Available budget  Relative priority of the produce delivery process  Sets context for Process B  E.g., budget limitations 28 ACET 2013, Nov 19, 2013
  • 29. Multiple Levels of SCM Processes  Process C – improves supply chain across many categories of goods for a distributor company 29 ACET 2013, Nov 19, 2013
  • 30. Handling Change – 1  New way of supplying produce. Requirements:  Real-time shipment tracking  Fine-grained prediction of demand  Using traditional technologies:  Manual/sensor-based coarse-grained tracking  In-house BI implementation  Requires: time, money, training, managerial approval  Potential barriers to change 30 ACET 2013, Nov 19, 2013
  • 31. Handling Change – 2  Can this change be handled in Process A?  I.e., Implement the new solution at runtime – per process instance  Infeasible due to  Long implementation time and prohibitive cost  Required high-level manager approval  Fixed, limited variability in Process A  Can this change be handled in B?  Implementation time – OK  High-level manager approval – OK  Cost increase – remains a change barrier  Budget for produce delivery is set in Process C.  Change must be handled in Process C! 31 ACET 2013, Nov 19, 2013
  • 32. Handling Change – 3  Emerging technologies  Sensor Networks  More affordable, higher-granularity, network-connected  Cloud-based business analytics  Significantly cheaper, more flexible than in-house solutions  Internet-based/cloud supply chain collaboration  Increased variability: dynamically recruit/change supply chain partners for improvement/recovery from failures  Implementing these will lead to:  Likely – ability to handle this change in Process B  Avoids drastic budget increase  Potentially – ability to handle it within Process A, at runtime 32 ACET 2013, Nov 19, 2013
  • 33. Conceptual Modeling for a Complex and Dynamic World Recent and ongoing work  From BI Insights to Actions: Closing the Sense-and-Respond Loop in Adaptive Enterprises  Soroosh Nalchigar & E.Yu [PoEM’13]  Adapting to Uncertain & Evolving Requirements: the Case of Business-Driven BI  E.Yu, Alexei Lapouchnian, Stephanie Deng [RCIS’13]  System Dynamics & Intentional Modeling – Evolution of a Software Organization  with Mahsa Sadi  Analyzing Architectural Rigidity using Dynamic Capabilities Theory  with Muhammad Danesh  The Business Intelligence Model  E.Yu John Mylopoulos, Daniele Barone, Jennifer Horkoff, Lei Jiang, Daniel Amyot, Alex Borgida, E.Yu … [PoEM’10] … [SySoM’13] 33
  • 34. Questions? 34 ACET 2013, Nov 19, 2013