Presentation is loading. Please wait.

Presentation is loading. Please wait.

SCEA 2000 - 15 June 2000 JRS, TASC, 5/7/2015, 1 BMDO Cost Risk Improvement in Operations and Support (O&S) Estimates J. R. Summerville,

Published byDamon Archibald Elliott Modified over 9 years ago

Similar presentations

Presentation on theme: "SCEA 2000 - 15 June 2000 JRS, TASC, 5/7/2015, 1 BMDO Cost Risk Improvement in Operations and Support (O&S) Estimates J. R. Summerville,"— Presentation transcript:

1 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 1 BMDO Cost Risk Improvement in Operations and Support (O&S) Estimates J. R. Summerville, R. L. Coleman, M. E. Dameron Annual SCEA National Conference Manhattan Beach, CA 15 June 2000

2 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 2 Outline Purpose Overview of BMDO Cost Risk Methodology Issues with Risk in O&S Ideas for improvement Implementation Analysis of Results Conclusion

3 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 3 Purpose Research done for, and funded by the Ballistic Missile Defense Organization (BMDO) under direction of Ms. Donna Snead and Mr. Lowell Naef. Purpose was to further enhance BMDO Cost Risk Model, which has been used to develop independent life cycle cost risk assessments since 1989 –Model is currently well received, however there are some recognized weaknesses that await further research. One such area is the capability for quantifying risk in O&S. –The focus of this paper will be to examine ways reflect more accuracy in O&S cost risk estimates.

4 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 4 BMDO Cost Risk Approach

5 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 5 BMDO Cost Risk Model WBSInitial PointCE S/TEstimate Estimatedrawdrawwith Risk 1.0 Hardware100M127M 1.1 Item 1 80M 1.1 1.15100M 1.2 Item 2 20M 1.151.2 27M 2.0 SW 10M 1.031.3 13M 3.0 SE/PM 11M 14M Total121M168M Take the base Number Multiply by a random variable resulting from the Monte Carlo process Collect the results in a histogram Some elements are roll-ups The result is an estimate with risk Steps: Example (one iteration): Some elements are factors off of others

6 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 6 BMDO Cost Risk Model Functional Correlation 1 Suppose SE/PM = a * Hardware a =.1, with Standard Deviation of.01 H/W = 100, with Standard Deviation of 10 Iteration 1 Iteration 2 Iteration 3 Iteration 4 H/W = 100 a =.09 Drawn Variables H/W = 110 a =.10 H/W = 90 a =.11 H/W = 90 a =.09 Functional Correlation SE/PM = 9 SE/PM = 11 SE/PM = 9.9 SE/PM = 8.1 Without Correlation SE/PM = 9 SE/PM = 10 SE/PM = 11 SE/PM = 9 xx xx xx x x SE/PM H/W SE/PM H/W 1 An Overview of Correlation and Functional Dependencies in Cost Risk and Uncertainty Analysis, DoDCAS 1994, R. L. Coleman, S. S. Gupta

7 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 7 Should We Have Risk in O&S? We know: –O&S Cost is correlated to Acquisition Hardware/Software, (e.g. SW Maintenance, spares, etc.) –Correlation of cost growth exists between the R&D and Production phases of Acquisition 1 We believe: this implies correlation in cost growth between O&S and Acquisition from onset –Note, this does not mean cost growth during O&S –Intuitive, though no data analysis to support 1 Cost Risk Estimates Incorporating Functional Correlation, Acquisition Phase Relationships, and Realized Risk, SCEA National Conference 1997, R. L. Coleman, S. S. Gupta, J. R. Summerville, G. E. Hartigan

8 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 8 Issues with BMDO O&S Risk Example: SW Maintenance vs. Dev SW Point Estimat e As Dev SW increases, SW Maint should as well, causing a higher mean, and thus a higher risk percentage. Lack of correlation holds down the SW Maint cost here. Numbers are for example only Most BMDO elements currently have little to no sched/tech risk in O&S –Compare Risk % and CV w/other phases –Lack of correlation is the culprit

9 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 9 Ideas for Improvement Use Functional Correlation 1 where available Expand on Functional Correlation using the following methods: –Cost Response Curves –Injected Correlation –Algebraic manipulation Details to follow 1 Cost Risk Estimates Incorporating Functional Correlation, Acquisition Phase Relationships, and Realized Risk, SCEA National Conference 1997, R. L. Coleman, S. S. Gupta, J. R. Summerville, G. E. Hartigan; An Overview of Correlation and Functional Dependencies in Cost Risk and Uncertainty Analysis, DoDCAS 1994, R. L. Coleman, S. S. Gupta

10 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 10 Cost Response Curves 1 Y= 0.74 X - 0.18 Example: Use existing cost tools to create a functional relationship –E.g. for Software: SLIM, SEER, SASET –Run several iterations on different SLOC values to derive an equation that links maintenance cost to development cost –Incorporate in cost model as a functional relationship 1 Cost Response Curves - Their generation, their use in IPTs, Analyses of Alternatives, and Budgets, DoDCAS 1996, K. J. Allison, K. E. Crum, R. L. Coleman, R. G. Klion

11 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 11 Injected Correlations Setup links to create correlation implicitly –Correlation coefficients are not estimated directly –Procedure involves linking cost growth factors between elements, and creating correlation in the simulation as a result –The amount of correlation you have implicitly estimated can be calculated after the simulation has run… example later…

12 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 12 Other Approaches Other extensions of Functional Correlation are possible Similar to the CRC, FC may be applied if there is a CER that is related to a common variable in Acquisition, e.g. weight. –This case involves simple algebraic manipulation of the O&S equation in order for it to reference the resulting cost of the related CER rather than its common parameter

13 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 13 Implementation

14 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 14 Navy Area O&S Breakdown

15 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 15 O&S Model Adjustments Before: 1% of O&S phase Correlated to Acquisition After: 89% of O&S phase Correlated to Acquisition Used functional relationships where possible –Disposal, spares Injected correlation in cases where functions not available –SW Maintenance, Intermediate Maintenance

16 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 16 Navy Area O&S Breakdown Directing Correlation Ship Adjunct Processors SW Development Recurring Production Recurring Production Recurring Production Acquisition Item to be Correlated

17 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 17 Risk in Navy Area O&S Before and After

18 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 18 Correlation Example SW Maintenance Before:After: Actual Simulation Results Not CorrelatedCorrelated Risk = 3.6%Risk = 35.1%

19 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 19 Risk % in Navy Area O&S Before and After

20 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 20 Navy Area Risk

21 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 21 Analysis Risk increased for all newly correlated items Total percent still seems understated when compared to other phases--why? –Bulk of Phase $ (69%) under “Other Recurring Investments” Cost is for periodic replacement of ship adjunct processors Correlated to adjunct processor HW in the ship production phase, low risk –Note new O&S risk % close to Ship Production risk %

22 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 22 Resulting Correlation Software Maintenance Example  = 0.61 This is not to say we have confidence that these results exactly reflect reality, but it is clearly a better alternative than what was previously accepted This is not to say we have confidence that these results exactly reflect reality, but it is clearly a better alternative than what was previously accepted

23 SCEA 2000 - 15 June 2000 jrsummerville@tasc.com JRS, TASC, 5/7/2015, 23 Conclusion The methodology presented in this paper has significantly enhanced the quality of BMDO O&S cost estimates –Concepts are simple to implement –All required assumptions can feasibly be made by cost analysts Future improvements will result with the development of better CERs for O&S that provide known relationships with Acquisition.

Download ppt "SCEA 2000 - 15 June 2000 JRS, TASC, 5/7/2015, 1 BMDO Cost Risk Improvement in Operations and Support (O&S) Estimates J. R. Summerville,"

Similar presentations

Value-at-Risk: A Risk Estimating Tool for Management

Value-at-Risk: A Risk Estimating Tool for Management
Cost as a Business Driver 1 John Brown C Eng MIEE mr_ Software Cost Estimation.

Cost as a Business Driver 1 John Brown C Eng MIEE mr_ Software Cost Estimation.
Asset Pricing. Pricing Determining a fair value (price) for an investment is an important task. At the beginning of the semester, we dealt with the pricing.

Asset Pricing. Pricing Determining a fair value (price) for an investment is an important task. At the beginning of the semester, we dealt with the pricing.
1 COMM 301: Empirical Research in Communication Lecture 15 – Hypothesis Testing Kwan M Lee.

1 COMM 301: Empirical Research in Communication Lecture 15 – Hypothesis Testing Kwan M Lee.
Hypothesis testing and confidence intervals by resampling by J. Kárász.

Hypothesis testing and confidence intervals by resampling by J. Kárász.
Introduction CreditMetrics™ was launched by JP Morgan in 1997.

Introduction CreditMetrics™ was launched by JP Morgan in 1997.
Extension The General Linear Model with Categorical Predictors.

Extension The General Linear Model with Categorical Predictors.
Data Mining Methodology 1. Why have a Methodology  Don’t want to learn things that aren’t true May not represent any underlying reality ○ Spurious correlation.

Data Mining Methodology 1. Why have a Methodology  Don’t want to learn things that aren’t true May not represent any underlying reality ○ Spurious correlation.
Variance reduction techniques. 2 Introduction Simulation models should be coded such that they are efficient. Efficiency in terms of programming ensures.

Variance reduction techniques. 2 Introduction Simulation models should be coded such that they are efficient. Efficiency in terms of programming ensures.
1 SSS II Lecture 1: Correlation and Regression Graduate School 2008/2009 Social Science Statistics II Gwilym Pryce www.gpryce.com.

1 SSS II Lecture 1: Correlation and Regression Graduate School 2008/2009 Social Science Statistics II Gwilym Pryce
Three Approaches to Value There are three general approaches that we use to value any asset. –Discounted Cash Flow Valuation –Relative Valuation –Contingent.

Three Approaches to Value There are three general approaches that we use to value any asset. –Discounted Cash Flow Valuation –Relative Valuation –Contingent.
Fundamentals of Information Systems, Second Edition

Fundamentals of Information Systems, Second Edition
1 Introduction to System Engineering G. Nacouzi ME 155B.

1 Introduction to System Engineering G. Nacouzi ME 155B.
1 Validation and Verification of Simulation Models.

1 Validation and Verification of Simulation Models.
BA 427 – Assurance and Attestation Services

BA 427 – Assurance and Attestation Services
1 A MONTE CARLO EXPERIMENT In the previous slideshow, we saw that the error term is responsible for the variations of b 2 around its fixed component 

1 A MONTE CARLO EXPERIMENT In the previous slideshow, we saw that the error term is responsible for the variations of b 2 around its fixed component 
Determining the Size of

Determining the Size of
RLC, TASC, 8/8/2015, 1 (703) 631-2000 x2181 Risk In Cost Estimating General Introduction & The BMDO Approach 33 rd ADoDCAS 2-4 February.

RLC, TASC, 8/8/2015, 1 (703) x2181 Risk In Cost Estimating General Introduction & The BMDO Approach 33 rd ADoDCAS 2-4 February.
So are how the computer determines the size of the intercept and the slope respectively in an OLS regression The OLS equations give a nice, clear intuitive.

So are how the computer determines the size of the intercept and the slope respectively in an OLS regression The OLS equations give a nice, clear intuitive.
Pearson Correlation Example A researcher wants to determine if there is a relationship between the annual number of lost workdays for each plant and the.

Pearson Correlation Example A researcher wants to determine if there is a relationship between the annual number of lost workdays for each plant and the.

Similar presentations

Ads by Google