DTIC ADA461455: Predicting Industry Personnel Security Investigation Requirements

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by  Defense Technical Information Center

Technical Report 07-01
January 2007

Predicting Industry Personnel Security
Investigation Requirements
Eric L. Lang
Defense Personnel Security Research Center

Leissa C. Nelson
Northrop Grumman Technical Services

Approved for Public Distribution—Distribution Unlimited
Defense Personnel Security Research Center

Technical Report 07-01 January 2007

Predicting Industry Personnel Security Investigation Requirements
Eric L. Lang, Defense Personnel Security Research Center
Leissa C. Nelson, Nothrop Grumman Technical Services

Released By – James A. Riedel
BACKGROUND HIGHLIGHTS
The 2000 Defense Authorization Bill PERSEREC reviewed data collected by
included a mandate that the the Defense Security Service (DSS)
Department of Defense (DoD) estimate Survey of Cleared Facilities (SCF). The
annual personnel security SCF is administered to approximately
investigation (PSI) requirements. 11,000 cleared defense contractor
Accurate PSI predictions are critical facilities each year to collect
so that DoD can develop budgets to information about the number of PSIs
cover industry PSI expenses and anticipated for the current fiscal year
adjudication workload. The need for and several years into the future. A
this information increased with the low response rate and estimate errors
2005 transfer of nearly all DoD PSIs have hindered prediction accuracy.
to the Office of Personnel PERSEREC used a regression
Management (OPM) and its imputation method to estimate
contractors. DSS contacted the missing survey data, and developed a
Defense Personnel Security Research facility-specific method to correct for
Center (PERSEREC) for assistance in over and under predictions by
improving PSI prediction methods. facilities. Using several years of SCF
PERSEREC conducted research and data, it was possible to demonstrate
developed an adjusted prediction that predictions made using a two-
method that could improve prediction stage estimation procedure (the
accuracy for industry PSI “adjusted prediction method”)
requirements. produced substantially more accurate
PSI estimates than those produced
using the current DSS prediction
method. Additional recommendations
for improving PSI predictions included
implementing a Web-based SCF (to
improve the speed and quality of
survey data) and creating policy to
encourage SCF participation by all
facilities.
Defense Personnel Security Research Center
99 Pacific Street, Suite 455-E
Monterey, CA 93940-2497

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3. DATES COVERED
1. REPORT DATE: (01-01-2007) 2. REPORT TYPE (From – To)
Technical Report 07-01 May 2005 - January
2007
5a. CONTRACT NUMBER:
4. Predicting Industry Personnel Security Investigation
5b. GRANT NUMBER:
Requirements
5c. PROGRAM ELEMENT NUMBER:
5d. PROJECT NUMBER:
6. AUTHOR(S)
5e. TASK NUMBER:
Eric L. Lang, Leissa C. Nelson
5f. WORK UNIT NUMBER:
7. PERFORMING ORGANIZATION NAME(S) AND
ADDRESS(ES)
8. PERFORMING ORGANIZATION REPORT NUMBER
Defense Personnel Security Research Center
PERSEREC: Technical Report 07-01
99 Pacific Street, Suite 455-E
Monterey, CA 93940-2497
9. SPONSORING/MONITORING AGENCY NAME(S) 10. SPONSORING/MONITOR’S ACRONYM(S):
AND ADDRESS(ES) PERSEREC
Defense Personnel Security Research Center
99 Pacific Street, Suite 455-E 11. SPONSORING/MONITOR’S REPORT NUMBER(S):
Monterey, CA 93940-2497
12. DISTRIBUTION/AVAILABILITY STATEMENT:
Approved for Public Distribution
13. SUPPLEMENTARY NOTES:
14. ABSTRACT:
Accurate annual predictions of personnel security investigation (PSI) requirements are important for the Department of Defense
(DoD) budgeting process and for ensuring that the necessary resources are available. The Defense Security Service (DSS)
currently obtains PSI prediction estimates through an annual survey of cleared industry facilities. However, actual PSI
requirements often differ substantially from PSI predictions. At the request of DSS, the Defense Personnel Security Research
Center (PERSEREC) reviewed DSS prediction methods, explored supplementary data that might enhance predictions, then
developed and tested a new, adjusted prediction method. The new method holds promise for improving PSI prediction accuracy.
15. SUBJECT TERMS: Personnel security investigations, industry surveys
19a. NAME OF
16. SECURITY CLASSIFICATION OF: RESPONSIBLE
Approved for Public Distribution PERSON: James A.
17. LIMITATION 18. NUMBER
Riedel, Director
OF OF PAGES:
19b. TELEPHONE
ABSTRACT: 66
a. REPORT: b. ABSTRACT: c. THIS PAGE: NUMBER (Include
Unclassified Unclassified Unclassified area code): 831-657-
3000
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PREFACE
PREFACE
The 2000 Defense Authorization Bill included a mandate that the Department of
Defense (DoD) assess personnel security investigation (PSI) requirements. Accurate
PSI predictions are critical so that DoD can develop budgets to cover industry PSI
expenses and adjudication workload. The need for this information increased with
the 2005 transfer of nearly all DoD PSIs to the Office of Personnel Management
(OPM) and its contractors. In response to the mandate, the Defense Security Service
(DSS) established a Central Requirements Office (CRO) for industry personnel
security clearances and instituted an annual survey of cleared facilities to obtain
information about the number of PSIs the facilities expected to require in upcoming
years.
Because the survey responses have not been sufficiently accurate in predicting
actual PSI requirements, DSS contacted the Defense Personnel Security Research
Center (PERSEREC) for assistance in improving prediction methods. PERSEREC
conducted research and developed an adjusted prediction method that could
improve prediction accuracy for industry PSI requirements. Recommended changes
in how annual survey data are collected should also enhance prediction accuracy.
PERSEREC presented the findings, including prediction algorithms,
recommendations and supporting information, to the DSS CRO May 2005. The
current report documents the research goals, methods, findings, and
recommendations for improving the prediction of industry PSI requirements.

James A. Riedel
Director
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PREFACE

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ACKNOWLEDGMENTS
ACKNOWLEDGMENTS
The authors appreciate a number of people who helped with this research. Jeremy
Peck contributed substantially to early data collection and analysis efforts. Staff at
the Defense Security Service (DSS) provided the data from the Survey of Cleared
Facilities. In addition, staff at the Federal Procurement Data Center (FPDC)
provided a wealth of useful procurement data.
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ACKNOWLEDGMENTS

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