Design for Harmony:
An Exploration of Enterprise and Product
Architecture Tradespace Dynamics
Christopher J. Roberts, Ph.D. Student, Engineering Systems Division
Advisors: Prof. Deborah Nightingale, Dr. Donna Rhodes
Motivation / Problem Statement
Enterprise Architecting is the proactive process of designing and
evolving the desired future state of the enterprise. It encompasses
choices about the fundamental business models employed and the
strategic responses available to dynamic changes in context. Similarly,
product architectures govern the design and evolution of products.
Literature Review
Research Design
This research is conducted with an iterative concurrent
process using qualitative and quantitative methods
Literature Review,
Field Interviews,
Data Collection
1. Knowledge Capture and
Synthesis (Descriptive)
Dynamics of Innovation
Existing Theory,
Empirical Data
2. Theory Development
(Normative)
Internal
Validation
• Conceptualization of dynamic
complexity in enterprise and
product architectures
• Metrics for component dynamic
complexity to be used in
tradespace exploration modeling
• Enterprise
• Enterprise Value Stream
Mapping Analysis2
3. Computer Experiments
(Theory Evaluation)
Methods
4. Case Applications
(Prescriptive)
Findings
• Prescriptions for improved
enterprise strategic
planning and governance
Dynamic Tradespace Exploration
Enterprise and Product Architectures are Dynamically Coupled
Enterprise Architecting1 is used to provide
a data gathering and modeling framework
to capture the dynamic complexity of the
enterprise component interactions
+
Dynamic MATE4 is used to explore the
dynamic complexity of the joint enterpriseproduct architecture tradespace under
variable contextual scenarios and time scales
• Case studies & analysis
• Complexity methods
championed at the Santa Fe
Institute, including nonequilibrium statistical physics
and network & scaling theories
• Field interviews & ethnography
1
Nightingale, Deborah and Donna Rhodes. (2008). ESD.38 Enterprise
Architecting Graduate Course. MIT ESD.
2
MIT Lean Advancement Initiative. Lean.mit.edu
Sussman, Joseph et al. (2008). “The ‘CLIOS Process:’ A Users Guide.”
3
Coursework,
Research
Definition,
Literature
Review
Fall 2007
Spring 2008
Coursework, Data Gathering,
Data &
Research
Theory
Theory
Substantiation Development, Refinement,
& Proposal,
Computer
Conference
General Exams Publications
Simulations
Fall 2008
Spring 2009
Fall 2009
Computer
Simulations,
Case
Applications,
Conference
Publications
Synthesis &
Refinement,
Impact &
Outreach
Activities
Dissertation,
Journal
Publications
Spring 2010
Fall 2010
Spring 2011
• Extension of dynamic tradespace exploration to include enterprise
architecture and contextual factors
• Development of dynamic complexity metrics
Systematic Observation and Documentation
• Collection of a robust empirical dataset through case studies, field
work, probabilistic modeling and statistical analysis
• System Dynamics
Innovative modeling and analysis
• New engineering system representation and visualization schemas
Tradespace analysis allows identification of symbiotic enterpriseproduct architectures with desirable “ility” properties
4
Ross, A. (2006). "Managing Unarticulated Value: Changeability in MultiAttribute Tradespace Exploration." Doctoral dissertation, MIT ESD.
Available at seari.mit.edu
5 Santa Fe Institute. www.santafe.edu
Program Start,
Coursework,
Research
Exploration
Advancement of enterprise and product architecting core theory
• Dynamic Multi-Attribute
Tradespace Exploration
(MATE)4
• Complex, Large-scale,
Interconnected, Open, Sociotechnical (CLIOS) Process3
Timeline
Expected Contributions
Quantitative Methods
• Statistical inference from
empirical datasets
Product Planning & Acquisition Strategy
Complexity Theory
Candidate Methods
Architecting1
Product Development & Systems Architecture
Methods
The goals of this research are to develop core theory & methodology,
create a robust dataset, apply innovative modeling & analysis, and
impact the policy & practice of enterprise and product architecting in
dynamic contexts.
Qualitative Methods
Policy
Lean Enterprises & Enterprise Architecting
Analysis Techniques,
Empirical Data
External
Validation
1. What are the dominant enterprise & product variables that give
rise to dynamic coupling and emergent behavior?
2. What are the dominant contextual factors (i.e. political, market,
etc.) that influence architectural co-evolution?
3. How can the dynamic relationships between the enterpriseproduct architectures and contextual factors be managed?
Management
Engineering Systems Fundamentals & Research Publications
Product development enterprises experience dynamic coupling
between their enterprise and product architectures that leads to
emergent behaviors often manifested as “ility” properties (flexibility,
rigidity, etc.), for better or worse. Better understanding of enterpriseproduct architectural coupling and interactions with the dynamic
context in which they are embedded will allow the design of symbiotic
enterprise-product architectures that deliver sustainable stakeholder
value.
Defining Survivability
Key Questions
Technology
.
.
Impact to policy and practice
• Enable more effective
enterprise and technology
strategic planning and
governance
Christopher Roberts
cjr@mit.edu