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DoD Counterintelligence STRATEGY MAPPING. William L. McCoy Senior Program Manager Lockheed Martin Integrated Technology. Ver 10.0 September 29, 2005. STRATEGY MAPPING OBJECTIVE.

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slide1

DoD

Counterintelligence

STRATEGY

MAPPING

William L. McCoy

Senior Program Manager

Lockheed Martin Integrated Technology

Ver 10.0 September 29, 2005

slide2

STRATEGY MAPPING OBJECTIVE

To develop a methodology that defensibly and quantitatively maps the DoD CI Strategy (and eventually DoD CI resources to achieve it) to DNI Strategic Objectives, NCIX Pillars, Defense Intelligence Goals, and other guidance documents.

briefing overview
BRIEFING OVERVIEW
  • Purpose:Recommend survey universe, sample size (if required)

and analysis methodology for strategic mapping project that maps

DoD CI General Goals to:

    • National Counterintelligence Pillars
    • Director of National Intelligence Strategic Objectives
    • USD(I) Defense Intelligence Goals
  • Discussion:
    • DT Survey Results
    • Part 1 – Universe and Sample Size Methodology
      • Recommendation and Decision
    • Part 2 – Data Reduction and Analysis
      • Recommendation and Decision
  • Next Steps
slide5

PART 1

UNIVERSE AND SAMPLE SIZE METHODOLOGY

slide6

SURVEYING

  • Survey types:
    • Sample – more involved as we must make corrections

for the error introduced by not surveying the universe.

Sampling is required if the universe is too large.

    • Population – more straight forward as no errors are

introduced by sampling but requires manageable universe.

  • Sampling introduces an additional step of determining and
  • correcting for the variance – hence the arcane statistics.

The analysis commences after the numbers are crunched.

The results can be accepted at face value or adjusted/revised

based on subject knowledge.

slide7

OPTION DISCRIMINATORS

OPERATIONAL DEFINITIONS FOR SURVEY

“TERMS OF ART” DISCRIMINATORS

slide8

UNIVERSE ASSUMPTIONS

  • OPTION 3
  • estimate
  • CIRROC
  • Member
  • Organizations 80
  • Total 80
  • OPTION 2
  • estimates
  • AF OSI 65
  • Navy NCIS 75
  • USMC 25
  • Army 55
  • Agencies 80
  • Total 300
  • OPTION 1
  • estimates
  • AF OSI 450
  • Navy NCIS 700
  • USMC 200
  • Army 350
  • Agencies 300
  • Total 2,000
    • SAMPLE SIZE
  • Target population of 2,000
  • Confidence interval +/- 5%
  • Confidence level of .95
    • Then sample size = 92
    • SAMPLE SIZE
    • Target population of 300
  • Confidence interval +/- 5%
  • Confidence level of .95
    • Then sample size = 73
  • SAMPLE SIZE
    • Target population of80
    • 100% survey possible
  • Then target universe = 100%

ASSUMPTIONS

OPTION 1: The survey is administered to randomly selected DoD CI leadership and planners down to

unit officersand senior NCOs and includes civilians.

OPTION 2: Uses OPTION 1 assumption but restricts survey participation to DoD CI leadership, planners,

and resource managers down to major unit level.

OPTION 3: Limits the survey to National level DoD CI leaders, strategic planners, and resource managers.

slide9

OPTION 1 DETAIL

Assumption: To map CI strategy we need input from all levels of the DoD CI community (OSD, CIFA, Services,

Agencies, Regions, Brigades, Groups, Battalions, Detachments, etc.) from DoD CI leadership and planners

down to unit CI officers and senior CI NCOs and civilian equivalents.

  • PROs:
    • Elicits input from those not normally associated with strategy issues.
    • Provides an operator perspective on CI strategy.
  • CONs:
    • Partially substitutes opinion for judgment.
    • Includes population with out experience with or insight into National or Defense CI activities.
    • Risk of missing significant information – may lower the sample mean below the threshold.
slide10

OPTION 2 DETAIL

Assumption: To map the strategy we need to know the view of all headquarters elements (less support) in the DoD CI

community from DoD CI leadership, and planners, CI officers and senior CI NCOs and civilian equivalents at OSD, CIFA,

Services, and Agencies down to Regions and Brigades.

  • PROs:
    • Provides perspectives from those dealing with both CI planning and execution issues.
    • Develops a broadly based input on strategy by including more operational and very strategic CI

leaders and planners.

CONs:

    • Population may not be conversant or experienced in National or Defense strategy issues.
    • Includes population with out experience with or insight into National or Defense CI activities.
    • Risk of missing significant information – may lower the sample mean below the threshold.
slide11

OPTION 3 DETAIL

Assumption: To map the strategy we need to know the perspective of DoD level leaders, strategy planners, and resource managers within the DoD CI community (OSD, CIFA, Services, Agencies).

  • PROs:
    • Generates responses from a population with ongoing knowledge of and experience with

National and Departmental strategy, budget, and resource issues.

    • Develops a broadly based view of strategy from DoD CI organizations.

CONs:

    • Survey population includes only headquarters leadership – misses CI field operator challenges.
slide12

RECOMMENDATION:

OPTION 3

  • The most relevant population –
  • current knowledge of and engaged
  • in National and Departmental CI
  • goals, strategies, resources, and
  • budgets.
  • Responders would have the
  • background and current knowledge
  • relevant to measuring strategy linkage.
  • Less risk of missing significant
  • results as there is no sample, thus no
  • risk of Type 2 error.
slide13

PART 2

DATA REDUCTION AND ANALYSIS

slide15

TAKING THE TOP SCORE

OPTION 1

Results from initial DT survey.

SELECTING LINKAGE DETERMINED BY: THE TOP ONE OR TWO

RESULTS IN A CATEGORY

PRO: Easy to understand.

CON: Does not explain why the top one or two cut-off; why

not the top three or four. More robust approaches

possible.

slide16

ADJUSTING THE CUTOFF BY THE

STANDARD DEVIATION

OPTION 2

Results from initial DT survey.

SELECTING LINKAGE DETERMINED BY:USING THE MEAN PLUS

ONE STANDARD DEVIATION

PRO: Still easy concept to understand and answers the

“why” for the cut-off.

CON: 1 sigma is too high for including alternates and splitting a

sigma, while doable, is questionable.

slide17

CUTOFF USING THE 85TH PERCENTILE

OPTION 3

Results from initial DT survey.

SELECTING LINKAGE DETERMINED BY:USING PERCENTILE

PRO: Understandable concept, answers the “why” for the cut-off. the range can

easily be broadened to include secondary selections by adjusting the

percentile.In some cases the Percentile approach may “table up”

additional choicesnot presented by OPTION 1.

CON: Less relationship to normal distribution theory.

slide18

RECOMMENDATION

OPTION 3 is recommended – it provides

a defensible solution with reasonable rigor

using commonly understood data analysis

techniques.

next steps
NEXT STEPS
  • Develop survey instructions and invitations according

to the approved universe – <1 week

  • Administer the survey – 1 week
  • Complete data steps:
    • Input – 3 days
    • Reduction – 1 day
    • Analysis – 1 day
  • Publish, disseminate, and apply results
slide22

EXCURSION –

TWO BASIC TYPES OF SURVEYS

Surveys are divided into two categories:

  • 1. A survey of the universe – also called a “census” or a “poll”
  • 2. A sample survey that is representative of the universe:
    • The only time we don’t survey the universe is when time, cost, or
  • accessibility of respondents create the need for a sample – in other
  • words, when we have no other choice.
    • The goal of a sample is to produce the same results that would have been obtained had every single member of a universe been
  • interviewed.
  • The key to reaching this goal is a fundamental principle called equal probability of selection.
  • Cluster, stratified, and other forms of surveys are based on the
  • foregoing.
slide23

TO DETERMINE THE UNIVERSE,

“WHO CAN TELL US WHAT WE NEED TO KNOW?”

UNIVERSE SELECTION PRINCIPLES:

  • The survey\'s universe must fit the facts of the case.
  • The target population must correspond to the topic studied.
  • A universe which is relevant to the problem being studied and
  • includes respondent qualification requirements is a vital
  • requirement of high quality research.
  • When selecting the universe every member of that universe
  • must have an equal probability of sample selection.

INDICATE THE UNIVERSE SHOULD BE POPULATED WITH:

  • Those in DoD who are engaged and familiar with the National and Departmental CI goals, strategies, resources, and budgets.
slide24

HYPOTHESIS TESTING:

STEP 2 EXPLANATION

Setting the Level of Significance

  • The significance level is used for accepting or rejecting the null hypothesis.
  • The difference between the results of the experiment and the null hypothesis
  • is determined.
  • Assuming the null hypothesis is true, the probability of a difference that large
  • or larger is computed .
  • This probability is compared to the significance level.
  • If the probability is less than or equal to the significance level, then the null
  • hypothesis is rejected and the outcome is said to be statistically significant.
  • The lower the significance level, the more the data must diverge from the
  • null hypothesis to be significant.
slide25

FORMULA FOR CALCULATING SAMPLE SIZE

Sample Size

Z2 * (p) * (1-p)

SS = -----------------------

c2

1.962 * (.5) * (1-.5)

SS = -----------------------

.102

1.962 * (.5) * (1-.5)

SS = -----------------------

.102

.964

SS = -----------------------

.01

Where:

SS = 96 rounded

More follows

slide26

. . . AND CORRECTING FOR A FINITE UNIVERSE

SS

Corrected SS = -----------------------

SS-1

1+ ------

pop

96.04

Corrected SS = -----------------------

96.04-1

1+ ----------

2,000

where:

96.04

Corrected SS = -----------------------

95.04

1+ ----------

2,000

96.04

Corrected SS = -----------------------

1.04752

Corrected SS = 92 rounded

slide27

. . . OR YOU CAN USE THE FREEWARE

SAMPLE SIZE CALULATOR

Given a universe of 2000 and a confidence

interval of 10 (+\- 5), you are 95% certain

that a sample size of 92 will provide results

consistent with a total survey of the universe.

WHICH SAYS:

slide28

STRATEGY MAPPING

SAMPLE SIZE METHODOLOGY

EXAMPLE

  • Assuming:
  • DoD CI strength of 2,000
  • Confidence interval of +/- 5%
  • Confidence level of .95
  • Then sample size = 92

}

FYI:

The sample

size for a

population

of 3,000 is

93 and for

300 is 73.

Z2 * (p) * (1-p)

SS = -----------------------

c2

SS

Corrected SS = -----------------------

SS-1

1+ ------

pop

BASED ON

OR

slide30

RESEARCH PROBLEM

  • The most difficult task in developing a research project is to narrow
  • down the field of study and the research problem. A distinction needs
  • to be made between a problem and a research problem.
  • A problem is an observed discrepancy or gap between what is known
  • and not known.
  • The identification of the problem is an interpretation of the gap based
  • on a set of observations.
  • A research problem is a judgment drawn from the interpretation of the gap.
slide31

RELIABILITY AND VALIDITY

VALIDITY: Information is presented or used in the

way for which it was intended.

RELIABILITY: We can expect to obtain the same

information time after time.

slide32

DATA MANAGEMENT

SURVEY

INPUT

STORAGE

Data summed by guidance

Category and by General and

Performance Goal, standardized

to 100, and reviewed through

correlation and other techniques.

Summary or unsummarized data

provided to CI leadership and

strategy planners for review and

analysis.

COMMENCE ANALYSIS

slide33

The standard error of a sample of sample size is the sample\'s

standard deviation divided by the square root of n. It therefore

estimates the standard deviation of the sample mean based on

the population mean. Note that while this definition

makes no reference to a normal distribution, many uses of this

quantity implicitly assume such a distribution.

The standard error of an estimate may also be defined as the

square root of the estimated error variance of the quantity,

slide34

RESEARCH QUESTION

How does DoD counterintelligence strategy

map into national and DoD intelligence and

counterintelligence guidance?

slide35

HYPOTHESIS TESTING:

The Null and Alternative Hypotheses

H0 – NULL HYPOTHESIS: There is no relationship between DoD

Counterintelligence Strategy and National Counterintelligence Pillars.

H0: µ - M < 0

H1 –ALTERNATIVE HYPOTHESIS: There is a relationship between

DoD Counterintelligence Strategy and National Counterintelligence

Pillars.

H1: µ - M =>0

slide36

HYPOTHESIS TESTING:

  • Next steps:
  • Set the Level of Significance at .95; alpha = .05
  • Identify the Test Statistic and calculate the
  • critical value (or probability)
  • Formulate the decision rule - in this case if the
  • Test Statistic is => 0 reject the Null Hypothesis
slide38

HYPOTHESIS TESTING

Initial DT NCI Survey Results

slide39

HYPOTHESIS TESTING

Problem with Sampling

Fairly robust statistics required to understand the survey result. It could have

been poor universe selection or an improperly designed survey instrument.

slide40

HYPOTHESIS TESTING

Initial DT NCI Survey Results

slide41

HYPOTHESIS TESTING

Problem with Sampling

Fairly robust statistics required to understand the survey result. It could have

been poor universe selection or an improperly designed survey instrument.

slide42

SELECTION WITHOUT REPLACEMENT

GOAL: Provide an NCI Pillar for each DoD CI Strategy General Goal

  • Assign the DoD CI GG having the highest score
  • If the DoD CI GG will be repeated, select the
  • second highest DoD CI GG score
  • Continue until all DoD CI GGs are exhausted
slide43

OPINION VICE JUDGMENT

opinion  u\'pinyun

A personalbelief or judgment that is not founded on proof or certainty

A belief or sentimentshared by most people; the voice of the people

A messageexpressing a belief about something; the expression of a belief that is heldwith

confidence but not substantiated by positiveknowledge or proof

The legal documentstating the reasons for a judicial decision

The reason for a court\'s judgment (as opposed to the decision itself)

A vagueidea in which some confidence is placed

ad