Systems Engineering Cost Estimation Systems Engineering Day, São José dos Campos, Brazil Dr. Ricardo Valerdi Massachusetts Institute of Technology June.

Slides:



Advertisements
Similar presentations
1 North Star Chapter of INCOSE March 10, 2005 Paul J. Frenz – General Dynamics Advanced Information Systems Some slides and data used with permission from:
Advertisements

Bath University Workshop on Estimating and Managing Through-Life-Costs Nov 081 Dr. Ricardo Valerdi Massachusetts Institute of Technology
Technology Acceptance Model. Copyright 2007 Black & Rossi, LLC All rights reserved 10/15/05 Black & Rossi, LLC, all rights reserved Who we are Technology.
Global Congress Global Leadership Vision for Project Management.
Example © 2012 Lockheed Martin Corporation. All Rights Reserved. October 2012 Proxy Estimation Costing for Systems (PECS) Reggie Cole Lockheed Martin Senior.
Towards COSYSMO 2.0 Future Directions and Priorities CSSE Annual Research Review Los Angeles, CA March 17, 2008 Garry Roedler Gan Wang Jared Fortune Ricardo.
Cocomo II Constructive Cost Model [Boehm] Sybren Deelstra.
Working Group Meeting (Outbrief) Ricardo Valerdi, Indrajeet Dixit, Garry Roedler Tuesday.
March 2002 COSYSMO: COnstructive SYStems Engineering Cost MOdel Ricardo Valerdi USC Annual Research Review March 11, 2002.
University of Southern California Center for Systems and Software Engineering USC CSSE Research Overview Barry Boehm Sue Koolmanojwong Jo Ann Lane Nupul.
University of Southern California Center for Software Engineering CSE USC COSYSMO: Constructive Systems Engineering Cost Model Barry Boehm, USC CSE Annual.
Project Risks and Feasibility Assessment Advanced Systems Analysis and Design.
11/08/06Copyright 2006, RCI1 CONIPMO Workshop Out-brief 21 st International Forum on COCOMO and Software Cost Modeling Donald J. Reifer Reifer Consultants,
COSYSMO: Constructive Systems Engineering Cost Model Ricardo Valerdi USC CSE Workshop October 25, 2001.
Some Experience With COSYSMOR At Lockheed Martin
Working Group Meeting Ricardo Valerdi Thursday October 27, 2005 Los Angeles, CA 20 th International Forum on COCOMO and Software Cost Modeling.
Extensions of COSYSMO to Represent Reuse 21 st International Forum on COCOMO and Software Cost Modeling November 9, 2006 Ricardo ValerdiJohn Gaffney Garry.
COSYSMO Reuse Extension 22 nd International Forum on COCOMO and Systems/Software Cost Modeling November 2, 2007 Ricardo ValerdiGan Wang Garry RoedlerJohn.
COSYSMO Workshop Future Directions and Priorities 23 rd International Forum on COCOMO and Systems/Software Cost Modeling Los Angeles, CA Wed Oct 29 & Thurs.
1 Systems Engineering Reuse Principles Jared Fortune, USC Ricardo Valerdi, MIT COSYSMO COCOMO Forum 2010 Los Angeles, CA.
The 25th Int’l Forum on COCOMO & Systems/Software Cost Modeling
Risk Analysis and Mitigation with Expert COSYSMO Ray Madachy, Ricardo Valerdi Naval Postgraduate School MIT Lean Aerospace Initiative
1 Lecture 2.6: Organization Structures Dr. John MacCarthy UMBC CMSC 615 Fall, 2006.
COSYSMO Reuse Extension 22 nd International Forum on COCOMO and Systems/Software Cost Modeling November 2, 2007 Ricardo ValerdiGan Wang Garry RoedlerJohn.
1 COSYSMO Workshop - Survey on Intuitive Judgments (Part III) COSYSMO = 1,000 PM Historical data = 1,100 PM COSYSMO = 100 PM Historical data = 110 PM.
System-of-Systems Cost Modeling: COSOSIMO July 2005 Workshop Results Jo Ann Lane University of Southern California Center for Software Engineering.
Estimating System of Systems Engineering (SoSE) Effort Jo Ann Lane, USC Symposium on Complex Systems Engineering January 11-12, 2007.
COSOSIMO* Workshop Outbrief 14 March 2006 Jo Ann Lane University of Southern California Center for Software Engineering CSE.
©2006 BAE Systems. Practical Implementation of COSYSMO Reuse Extension Gan Wang, Aaron Ankrum, Cort Millar, Alex Shernoff, Ricardo Valerdi.
Towards COSYSMO 2.0: Update on Reuse Jared Fortune, USC Ricardo Valerdi, MIT USC ARR 2009 Los Angeles, CA.
Copyright © 2001, Software Productivity Consortium NFP, Inc. SOFTWARE PRODUCTIVITY CONSORTIUM SOFTWARE PRODUCTIVITY CONSORTIUM COSYSMO Overview INCOSE.
INCOSE 1 st reactions. One other area that struck me has the sheer number of levels of proficiency—in ours we are going with 5 and the first one is limited.
1 Ricardo Valerdi – USC Center for Software Engineering April 2004 Drivers & Rating Scales.
COCOMO-SCORM: Cost Estimation for SCORM Course Development
Don Von Dollen Senior Program Manager, Data Integration & Communications Grid Interop December 4, 2012 A Utility Standards and Technology Adoption Framework.
Software Development *Life-Cycle Phases* Compiled by: Dharya Dharya Daisy Daisy
ESD web seminar1 ESD Web Seminar February 23, 2007 Ricardo Valerdi, Ph.D. Unification of systems and software engineering cost models.
1 Early Systems Costing Prof. Ricardo Valerdi Systems & Industrial Engineering Dec 15, 2011 INCOSE Brazil Systems Engineering Week.
Dr. Ralph R. Young Director of Software Engineering Systems and Process Engineering Northrop Grumman Information Technology (703)
1 Process Engineering A Systems Approach to Process Improvement Jeffrey L. Dutton Jacobs Sverdrup Advanced Systems Group Engineering Performance Improvement.
19 th COCOMO Forum1 19 th International Forum on COCOMO and Software Cost Modeling Los Angeles, CA October 28, 2004 Ricardo Valerdi – USC Center for Software.
1 מודל ניהול הצוותים של MSF. 2 Causes of failure  Poorly-defined objectives  Insufficient planning  Lack of executive support  Organizational barriers.
University of Southern California Center for Systems and Software Engineering COSATMO/COSYSMO Workshop Jim Alstad, USC-CSSE Gan Wang, BAE Systems Garry.
CHECKPOINTS OF THE PROCESS Three sequences of project checkpoints are used to synchronize stakeholder expectations throughout the lifecycle: 1)Major milestones,
9/17/2002 COSYSMO Usage Experience Panel: What is Happening at Lockheed Martin Garry Roedler, Lockheed Martin Engineering Process Improvement Center
Gan Wang 22 October th International Forum on COCOMO® and Systems/Software Cost Modeling in conjunction with the Practical Software and Systems.
March Jo Ann Lane University of Southern California Center for Software Engineering CONSTRUCTIVE SYSTEM OF SYSTEMS INTEGRATION COST MODEL COSOSIMO.
CEN5011, Fall CEN5011 Software Engineering Dr. Yi Deng ECS359, (305)
CII Forum – 10/22/03 18th International Forum on COCOMO and Software Cost Modeling 1 Los Angeles, CA October 23, 2003 Ricardo Valerdi – USC Center for.
1 Microsoft Project Solution Offerings and the next chapter of EPM September 17th, 2003 Brendan Giles, PMP Systemgroup Management Services.
University of Southern California Center for Systems and Software Engineering Dr. Mauricio Peña January 28, 2013.
March 2004 At A Glance NASA’s GSFC GMSEC architecture provides a scalable, extensible ground and flight system approach for future missions. Benefits Simplifies.
Cmpe 589 Spring 2006 Lecture 2. Software Engineering Definition –A strategy for producing high quality software.
Software Project Management (SEWPZG622) BITS-WIPRO Collaborative Programme: MS in Software Engineering SECOND SEMESTER /1/ "The content of this.
An organizational structure is a mostly hierarchical concept of subordination of entities that collaborate and contribute to serve one common aim... Organizational.
Unit – I Presentation. Unit – 1 (Introduction to Software Project management) Definition:-  Software project management is the art and science of planning.
Overview of Addressing Risk with COSYSMO Garry Roedler & John Gaffney Lockheed Martin March 17, 2008.
SE513 Software Quality Assurance Lecture12: Software Reliability and Quality Management Standards.
Some Preliminary Results Ricardo Valerdi Center for Software Engineering University of Southern California Disclaimer: Please do not distribute outside.
1 ESD.36 11/27/07 Ricardo Valerdi, PhD
Project Cost Management
Systems Engineering Cost Estimation
COSYSMO Data Sources Raytheon Northrop Grumman Lockheed Martin
COSYSMO: Constructive Systems Engineering Cost Model
COSYSMO Delphi Round 2 Results
Towards COSYSMO 2.0: Update on Reuse
Software Engineering I
DOD’S PHASED SYSTEM DEVELOPMENT PROCESS
Working Group Meeting Report
University of Southern California Center for Software Engineering
Presentation transcript:

Systems Engineering Cost Estimation Systems Engineering Day, São José dos Campos, Brazil Dr. Ricardo Valerdi Massachusetts Institute of Technology June 6, 2011

Theory is when you know everything, but nothing works. Practice is when everything works, but no one knows why. Harvard is where theory and practice come together... Nothing works and no one knows why. - on the door of a laboratory at Harvard

The Delphic Sybil Michelangelo Buonarroti Capella Sistina, Il Vaticano ( )

4 Cost Commitment on Projects Blanchard, B., Fabrycky, W., Systems Engineering & Analysis, Prentice Hall, 1998.

5 FeasibilityPlans/Rqts.DesignDevelop and Test Phases and Milestones Relative Size Range Operational Concept Life Cycle Objectives Life Cycle Architecture Initial Operating Capability x 0.5x 0.25x 4x 2x Cone of Uncertainty Boehm, B. W., Software Engineering Economics, Prentice Hall, 1981.

6 How is Systems Engineering Defined? Acquisition and Supply –Supply Process –Acquisition Process Technical Management –Planning Process –Assessment Process –Control Process System Design –Requirements Definition Process –Solution Definition Process Product Realization –Implementation Process –Transition to Use Process Technical Evaluation –Systems Analysis Process –Requirements Validation Process –System Verification Process –End Products Validation Process EIA/ANSI 632, Processes for Engineering a System, 1999.

COSYSMO Data Sources BoeingIntegrated Defense Systems (Seal Beach, CA) RaytheonIntelligence & Information Systems (Garland, TX) Northrop GrummanMission Systems (Redondo Beach, CA) Lockheed MartinTransportation & Security Solutions (Rockville, MD) Integrated Systems & Solutions (Valley Forge, PA) Systems Integration (Owego, NY) Aeronautics (Marietta, GA) Maritime Systems & Sensors (Manassas, VA; Baltimore, MD; Syracuse, NY) General DynamicsMaritime Digital Systems/AIS (Pittsfield, MA) Surveillance & Reconnaissance Systems/AIS (Bloomington, MN) BAE Systems National Security Solutions/ISS (San Diego, CA) Information & Electronic Warfare Systems (Nashua, NH) SAIC Army Transformation (Orlando, FL) Integrated Data Solutions & Analysis (McLean, VA) L-3 Communications Greenville, TX

8 COSYSMO Scope Addresses first four phases of the system engineering lifecycle (per ISO/IEC 15288) Considers standard Systems Engineering Work Breakdown Structure tasks (per EIA/ANSI 632) Conceptualize Develop Oper Test & Eval Transition to Operation Operate, Maintain, or Enhance Replace or Dismantle

9 COSYSMO Size Drivers Effort Multipliers Effort Calibration # Requirements # Interfaces # Scenarios # Algorithms + 3 Adj. Factors - Application factors -8 factors - Team factors -6 factors COSYSMO Operational Concept

10 COSYSMO Model Form Where: PM NS = effort in Person Months (Nominal Schedule) A = calibration constant derived from historical project data k = {REQ, IF, ALG, SCN} w x = weight for “easy”, “nominal”, or “difficult” size driver = quantity of “k” size driver E = represents diseconomies of scale EM = effort multiplier for the j th cost driver. The geometric product results in an overall effort adjustment factor to the nominal effort.

11 UNDERSTANDING FACTORS –Requirements understanding –Architecture understanding –Stakeholder team cohesion –Personnel experience/continuity COMPLEXITY FACTORS –Level of service requirements –Technology Risk –# of Recursive Levels in the Design –Documentation Match to Life Cycle Needs OPERATIONS FACTORS –# and Diversity of Installations/Platforms –Migration complexity PEOPLE FACTORS –Personnel/team capability –Process capability ENVIRONMENT FACTORS –Multisite coordination –Tool support Cost Driver Clusters

12 Stakeholder team cohesion Represents a multi-attribute parameter which includes leadership, shared vision, diversity of stakeholders, approval cycles, group dynamics, IPT framework, team dynamics, trust, and amount of change in responsibilities. It further represents the heterogeneity in stakeholder community of the end users, customers, implementers, and development team ViewpointVery LowLowNominalHighVery High Culture  Stakeholders with diverse expertise, task nature, language, culture, infrastructure  Highly heterogeneous stakeholder communities  Heterogeneous stakeholder community  Some similarities in language and culture  Shared project culture  Strong team cohesion and project culture  Multiple similarities in language and expertise  Virtually homogeneous stakeholder communities  Institutionalized project culture Compatibility  Highly conflicting organizational objectives  Converging organizational objectives  Compatible organizational objectives  Clear roles & responsibilities  Strong mutual advantage to collaboration Familiarity and trust  Lack of trust  Willing to collaborate, little experience  Some familiarity and trust  Extensive successful collaboration  Very high level of familiarity and trust

Technology Risk The maturity, readiness, and obsolescence of the technology being implemented. Immature or obsolescent technology will require more Systems Engineering effort. ViewpointVery LowLowNominalHighVery High Lack of Maturity Technology proven and widely used throughout industry Proven through actual use and ready for widespread adoption Proven on pilot projects and ready to roll-out for production jobs Ready for pilot useStill in the laboratory Lack of Readiness Mission proven (TRL 9) Concept qualified (TRL 8) Concept has been demonstrated (TRL 7) Proof of concept validated (TRL 5 & 6) Concept defined (TRL 3 & 4) Obsolescen ce - Technology is the state-of-the- practice - Emerging technology could compete in future - Technology is stale - New and better technology is on the horizon in the near-term - Technology is outdated and use should be avoided in new systems - Spare parts supply is scarce

Migration complexity This cost driver rates the extent to which the legacy system affects the migration complexity, if any. Legacy system components, databases, workflows, environments, etc., may affect the new system implementation due to new technology introductions, planned upgrades, increased performance, business process reengineering, etc. ViewpointNominalHighVery HighExtra High Legacy contractor Self; legacy system is well documented. Original team largely available Self; original development team not available; most documentation available Different contractor; limited documentation Original contractor out of business; no documentation available Effect of legacy system on new system Everything is new; legacy system is completely replaced or non-existent Migration is restricted to integration only Migration is related to integration and development Migration is related to integration, development, architecture and design

15 Cost Driver Rating Scales Very LowLowNominalHighVery High Extra HighEMR Requirements Understanding Architecture Understanding Level of Service Requirements Migration Complexity Technology Risk Documentation # and diversity of installations/platforms # of recursive levels in the design Stakeholder team cohesion Personnel/team capability Personnel experience/continuity Process capability Multisite coordination Tool support

16 Cost Drivers Ordered by Effort Multiplier Ratio (EMR)

ISO/IEC Conceptualize Develop Transition to Operation Acquisition & Supply Technical Management System Design Product Realization Technical Evaluation Operational Test & Evaluation ANSI/EIA 632 Effort Profiling

18 Before Local Calibration

19 After Local Calibration

20 Prediction Accuracy PRED(30) PRED(25) PRED(20) PRED(30) = 100% PRED(25) = 57%

21 Academic prototype Commercial Implementations Proprietary Implementations COSYSMO-R SECOST SEEMaP Impact Academic Curricula Intelligence Community Sheppard Mullin, LLC Policy & Contracts Model 10 theses

22 Contact Ricardo Valerdi MIT (617)