A Knowledge-Centric Approach for Complex Systems Chris R. Powell 1/29/2015
Dr. Chris R. Powell, MBA 31 years experience in systems, hardware, and software engineering 17 years in commercial development IBM, Supercomputer Systems, Inc., Network Systems Corp., StorageTek, Sequent Computer Systems, and several start-ups Network, I/O, Subsystem, CPU, Interoperability Operating System, Subsystems, NetComm Stack Secure Systems Engineering 14 years in Federal Government consulting Depts of Defense, Treasury, Justice, Energy, Homeland Security, Commerce System of Systems Engineering, Software Engineering, Software Reliability, Systems, Interoperability, System Assurance, Security Engineering Research Technical Systems Management, Philosophy of Knowledge, Innovation Organizational and individual dynamics involved in complex decisionmaking and engineering especially focused on tacit knowledge. Goal is to improve frequency and magnitude of success with complex investment. Chris.powell@engilitycorp.com (715) 379-9696 (cell)
SoS Problems and Solutions Basic Problem in System Acquisition New Thing: Looking at Complex Systems as Socio-Technical Solution: Knowledge-Centric Approach New SE/PM V, s, Management Complex Systems Engineering Framework (CSEF)
Basic Systems Acquisition Problem Tension Between Complexity & Speed Increasing system complexity Distributed users Distributed data Distributed computation More analytic More synthetic (data information knowledge) Increasing acquisition speed Years to months weeks days Reconcile complexity, identify solution, and achieve rapid fielding of continuously upgradeable system
Bringing All Of Our Friends Our SoS gunfights now require all on deck: Need Force Multiplier
What is a Complex System? Bar-Yam, Yaneer, Engineering complex systems: multiscale analysis and evolutionary engineering, in Braha, Dan, Ali A. Minai, and Yaneer Bar-Yam. Complex Engineered Systems. Cambridge, Massachusetts: Springer, 2006 [Bar-Yam 2006] Complex dynamic, emergent. Complicated many moving parts.
Basic Solution Approach: New SE/PM V Characterize Systems as Socio-Technical SE PM s Recognize Complexity Create Framework Separate Needs & Requirements Re-interpret SE & PM as knowledge-centric, to address social and technical aspects
Characterize Systems as Socio-Technical Systems Technical system system-as-created Analytic - problem decomposition Tradition of Natural Science: Quantitative, Objective Responsive to requirements through Explicit and Embedded knowledge Social system system-as-intended, systemas-used Synthetic socially-constructed, emergent Requires Social Science: Qualitative, Subjective Focuses on Felt needs, Tacit knowledge
Typical System Problem Today System & Software Engineering (1 SOW section): Design & Development Development IT Service Management Implementation Enterprise Application/Services Web Application Design & Development Human/Computer Interaction System/Software Integration ing & Simulation Information (Knowledge) Management Services Engineering & Technical Documentation Legacy System and Data Migration Development Toolkit Support Customers want it all better services across more complex business model with advanced technologies: Requires complete social and technical approach
Solution Factor: Knowledge-Centric Approach Notion: Expedite time-consuming acquisition steps by providing and ensuring the following, starting early in the lifecycle: Rigorous recording of assumptions, parameters, constraints, and other information through models, attributes, and metadata Rigorous correspondence of artifacts across lifecycle steps/phases/etc. through common program taxonomy and ontology (e.g., model framework and metadata) Quick, comprehensive testability of assumptions through simulation Simultaneous, early, and ongoing consideration of engineering and program design issues to ensure risk prevention
How to Implement a Knowledge-Centric Approach? New acquisition model -driven SE & PM approach Visualization of dynamic, multiple system dimensions in context (social and technical) Modular, component-oriented design to enable system portability, extensibility, and address dynamic requirements Need to involve multiple COI/COP throughout system lifecycle continuous dialog Need to enable system adaptability and flexibility to a series of unknown (and perhaps unknowable) and new requirements Systems Engineering & PM approach based on continuous modeling can address these factors simultaneously
Separate Needs vs. Requirements Felt Need Tacit Knowledge - Mindset Stated Need Explicit How much feedback, verification, and assurance activity is there to ensure that requirements as felt are actually implemented? Very little. Also, is any such activity structural? No. Manifested Requirement IT IS Explicit Embedded Realized Requirement Complete System System As Used
Need for Framework Mission Drivers Potential New or ChangedMission Capabilities Potential Mission Process Changes Potential Mission Performance Changes Potential Mission Data Changes Potential Changes in Collaboration or Interoperability Operational Impacts Personnel Impacts Training Impacts Support Impacts Infrastructure Impacts Changes to what gets done Changes to who is involved Changes to where things get done Changes to when things get done Changes to how things get done Changes to which information is used qualifies and quantifies impacts and implications of system changes incorporated and desired in response to changing mission drivers Related System Impacts Potential problem increasing system complexity can make characterizing these difficult or impossible up front. and modeling ensure adequate capability to respond to unknown unknowns.
Develop Framework Mission Drivers Decision to Change As-Is Mission System As-Is System of Interest To-Be System of Interest Or As-Is SoS of Interest Virtual Collaborative Acknowledged Directed To-Be SoS of Interest System 1 System 2 System n Quality Attributes Stakeholders Rationale Concerns Viewpoints Changes Correspondence Views Views Views views, artifacts, & models are then used to characterize and profile system prior to design, enabling system success through risk prevention. Artifacts Artifacts Artifacts
Perform ing Correspondence Rigorous Identification & Evaluation of Assumptions and Constraints Pursue Early & Explicit Coupling of System Attributes, Aspects, and Factors Identification of Metadata and Context Establish Mutual Team Understanding and Shared Decision Making Identify Impacts and Implications Establish Adaptability and Flexibility to Handle Unknown and Emergent Properties These modeling processes characterize and explore a system in human-friendly and knowledge-surfacing terms which enable system success. Usage & Decision ing Concept Refinement ing Operational Vignette ing Technical ing Interface Specification & ing Technology ing Prototype ing Emergent Properties ing Testability ing Program ing Requirements ing Financial Scenarios & Sensitivity Analysis EVM Criteria ing & Analysis IMS/IMP ing Risk ing & Prevention
Comprehensive SE Framework Ongoing and reinforcing technical review External and internal red teaming and assessment Peer review process Technical and mission rigor Systems Lifecycle Management Mission & Development Processes Systems Solution and Usage User Feedback and Study Data Analytics and High Performance Computing Risk Mitigation Trade Space Mission Drivers Mission Goals Metrics Early Systems Engineering Reliability, Availability, and Maintainability Development Planning, M&S Technology Development & Risk Reduction AoA, TRA/CTE Assessment Architect solution based on quality attribute analysis Balance best practices and need for innovation
CSEF and S&T/SE Integration Several dynamics are continuously at work in CSEF: Inner cycle operates to identify and resolve S&T research imperatives and SE concerns in response to ongoing risk mitigation trades Invention and innovation progress upwards and the to the right, seeking ongoing maximization of technical and programmatic criteria based on R&D and SE Risk mitigation trade space accepts and resolves risk on an ongoing basis CSEF continuously facilitates the entry and maturation of projects on the Rogers Innovation curve The CSEF concept strongly connects innovator, early adopter, early maturity and late maturity phases This connection continuously identifies new candidates on the lower left of the curve, and matures technology for appropriate insertion into mission processes Feedback into S&T and R&D is structured and ongoing through technical interchange, to ensure prioritization of research agenda and meaningful technical roadmapping Continuous innovation matures and releases new and complex technology to the mission community in a timely, risk-reduced way Continuous invention means the R&D community is continuously engaged to form and satisfy a research agenda based on evolving and dynamic mission requirements
Conclusion: Re-envisioning SE/PM as KM through CSEF Maximize involvement of agency in programs to prevent risk Leverage expertise and build more reach-back to previous success SE/PM Research Agenda needed Management concepts Technical concepts Manage programs as socio-technical systems Focus on knowledge discovery, creation, structure, and use Focus on human capital Evolve acquisition incentives to value contractor knowledge
Dr. Chris R. Powell Chris.powell@engilitycorp.com (715) 379-9696 (cell)