RESEARCH OVERVIEW Methodology to Identify Opportunities for Flexible Design

Transcription

1 RESEARCH OVERVIEW Methodology to Identify Opportunities for Flexible Design Jennifer Wilds, Research Assistant October 16, 2007 Advisors: D. Hastings and R. de Neufville

2 Researcher s Background Jennifer Wilds Research Interests Design Applications for Real Options Analysis Definition of Requirements for Flexible System Flexible Systems within Department of Defense (DoD) Unmanned Systems Education 2 nd year master student, ESD 08 B.S. Aerospace Engineering (Texas A&M Univ. 02) Professional Experience Air Force Research Laboratory, Munitions Directorate Titan LinCom Corporation at NASA Johnson Space Center seari.mit.edu 2007 Massachusetts Institute of Technology 2

3 Motivation for Research If the Department of Defense is to stay prepared for the security challenges of the 21st century, we must transform not just our defense strategies, not just our military capabilities, not just the way we deter and defend but we must also transform the way we conduct our business. --Defense Secretary Donald Rumsfeld, 4 June 2003 Real Options and Flexibility paradigms can have a significant impact on systems engineering, enterprise engineering, and acquisition in the future These paradigms theoretically align well with the Joint Capability Integration Development System (JCIDS) process and spiral development The requirements process mandates quantified definitions, and decisionsmakers often have difficulty in justifying/defending requirements Rapidly changing technologies and undefined requirements for new capabilities necessitate consideration of the uncertainties in developing and defining requirements seari.mit.edu 2007 Massachusetts Institute of Technology 3

4 Research Summary Project Title: Methodology for Identifying Opportunities for Flexible Design Sponsor: Synexxus Corporation in support of US Special Operations Command (USSOCOM) Goal: Identify potential opportunities for real options within the sociotechnical system to improve the system value in response to uncertainty using the Engineering System Matrix framework Approach: Collaborative engagement using a selected USSOCOM project as a case study to test a methodology to identify opportunities of flexibility and the potential to exploit results within the DoD acquisition process seari.mit.edu 2007 Massachusetts Institute of Technology 4

5 Key Challenges in Research Identify potential opportunities for flexibility Where do we look in the system to find opportunities for flexibility? What is the significance of the level of abstraction? (System level, component level, or attribute level) How can identified options be valued to assess the value of designing flexible systems? Identify and quantify system uncertainties Operational, technical, and process uncertainties New and rapidly developing systems may not have sufficient data to accurately quantify uncertainty Identify implementation challenges associated with formal requirements process in DoD Organizational processes and bureaucratic politics How requirements are defined and documented Thesis Focus Subsidiary Issue Contextual Issue seari.mit.edu 2007 Massachusetts Institute of Technology 5

6 Research Questions Can the Engineering System Matrix framework be used to identify hotspots and coldspots in a sociotechnical system? What level of information is necessary to construct a useful Engineering System Matrix? What is a hotspot and coldspot? What is the relation to system uncertainty? What is the relation to system flexibility? Can they be used to identify valuable real options? How is sensitivity defined within the scope of this research? What is the value of identifying hotspots and coldspots? seari.mit.edu 2007 Massachusetts Institute of Technology 6

7 ESM Framework Developed by Bartolomei (2007) Sociotechnical System = Social Domain + Technical Domain Qualitative Knowledge Construction (QKC) Source: Bartolomei, 2007 seari.mit.edu 2007 Massachusetts Institute of Technology 7

8 Key Terminology Backing into the problem Flexibility is a systems ability to adapt by implementing an option. An option is the right, but not obligation, to take an action at a price. Actions can be determined by evaluating the hotspots and coldspots within a system. Hotspots are elements in the system that are very sensitive to change. Coldspots are elements in the system that are less sensitive to change. Intuitively, hotspots are potentially interesting areas in the system that may warrant further investigation. seari.mit.edu 2007 Massachusetts Institute of Technology 8

9 Formulate Real Options An Option is... A right, but not an obligation exercise only if advantageous to take some action to change system, buy or sell something, etc now, or in the future... May be indefinite, can be for a limited time for a price (the strike price). Cost of action separate from cost of option A Real Option is Real because they refer to project Contrast with financial options that are contracts Real Options are focus of interest for Design They provide flexibility for evolution of system Projects often contain option-like flexibilities Rights, not obligations (e.g.: to expand garage) Exercise only if advantageous These flexibilities are real options Source: de Neufville, 2007 seari.mit.edu 2007 Massachusetts Institute of Technology 9

10 Two Types of Real Options Those concerning projects, in contrast to financial options, they are ON projects E.g.: the option to open a mine These do not get into system design Most common in literature Those concerning design, IN projects E.g.: ways of staging satellite system These require detailed understanding of system seari.mit.edu Most interesting to system designers Financial options Options ON projects Real Options Options IN projects 2007 Massachusetts Institute of Technology These need knowledge of system Source: de Neufville, 2007

11 Proposed Method for Identifying Hotspots and Coldspots Initial Proposed Methodology 1. Construct ESM of a particular system. 2. Identify sources of uncertainty driving change. 3. Define change scenarios. 4. Identify change modes for each scenario (eg change propagation method [Suh, 2005]). 5. Calculate how change modes affect objectives for each scenario (eg sensitivity analysis [Kalligeros, 2006]). 6. Calculate the cost of change for each scenario (eg cost analysis [Suh, 2005]). 7. Identify hotspots/coldspots for each change scenario. 8. Examine hotspots/coldspots across scenarios. 9. [Formulate real options from hotspots/coldspots.] Value flexibility using Real Options Analysis Test Methodology on Case Study Data Improve Methodology Validate Methodology Initial Method Source: Bartolomei, 2007 seari.mit.edu 2007 Massachusetts Institute of Technology 11

12 Possible Dimensions of Hotspots Sensitivity Hotspots are very sensitive to changes in the functional requirements, while cold spots are insensitive to changes Konstantinos: Sensitivity DSM provides qualitative assessment of components that are insensitive to changes in functional requirements for platforming; Sensitivity DSM entry denotes the necessary change in output specifications produced by a design task, given a change in its input specifications Provides magnitude of the change Does not indicate how the change propagates through the system Change Propagation Hotspots either propagate or absorb changes in the functional requirements, while coldspots are change carriers Eckert and Clarkson: Change Propagation Index classifies each system component as change multipliers, carriers, or absorbers Provides indication of how change propagates through the system Edge counting provides no understanding of the magnitude of the change being propagated Hotspots = Combination of Magnitude and Propagation of Change seari.mit.edu 2007 Massachusetts Institute of Technology 12

13 Identified Uncertainty Endurance capability Physical Flexible Options Battery Wing & empennage design Example of Real Options: Micro Air Vehicle Empennage Wing Skins Actuator Servo Camera #2 Fuselage Ribs Flexible Design Modular battery Modular wing & empennage Value of Flexibility Single solution that can adapt to changing operational requirements Camera #1 Prop Motor Required a detailed knowledge and understanding of the system to identify the options! Figure Reference: Senseney, 2004 seari.mit.edu 2007 Massachusetts Institute of Technology 13

14 Extensions to Sociotechnical Systems Identifying and valuing options beyond the physical domain Using the methodology to determine requirements that allow acquisition of flexible system capable of adapting to future uncertainties Social Organization Culture Individuals Value Propositions Processes Rules Artifacts Infrastructure Processes Functions Physical Laws Technical Social/Political: Stakeholder Changes Social Influences Competition Laws/Policies/Regulations Physical: Resources Weather Economic: Resources Market Environment Technological: Innovation Obsolescence Other Systems Standards Figure Reference: Bartolomei, 2007 seari.mit.edu 2007 Massachusetts Institute of Technology 14

15 Anticipated Contributions Expected Outcomes: Demonstrate an application of the Engineering System Matrix framework Provide a methodology to help decide where to focus efforts to design flexible systems Broader Impact: Further the use of real options to design flexible systems capable of responding to future uncertainties Knowledge Deployment: MIT/Synexxus paper at 2008 Conference on SE Research (CSER) Future paper on technical effort Research presentation to DoD acquisitions community Case study incorporated into MIT curriculum seari.mit.edu 2007 Massachusetts Institute of Technology 15

16 Further Information Bartolomei, J. E. (2007). Qualitative Knowledge Construction for Engineering Systems: Extending the Design Structure Matrix Methodology in Scope and Procedure. Cambridge, MA. Massachusetts Institute of Technology, Engineering Systems Division. Doctoral Dissertation. Kalligeros, K. (2006). Platforms and Real Options in Large-Scale Engineering Systems. Cambridge, MA. Massachusetts Institute of Technology, Engineering Systems Division. Doctoral Dissertation. Suh, E.S. (2005). Flexible Product Platforms. Cambridge, MA. Massachusetts Institute of Technology, Engineering Systems Division. Doctoral Dissertation. Wilds, J. W., Bartolomei, J. E., de Neufville, R. and Hastings, D. (2007). Real Options In a Mini-UAV System. Hoboken, NJ. 5th Conference on Systems Engineering Research, Track 1.1: Doctoral Research in System Engineering. seari.mit.edu 2007 Massachusetts Institute of Technology 16