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Challenges of Future Battle Command Experimentation:
An Analyst’s Perspective
Craig DoescherLTC Brian Hobson
Dr. Frank Myers
14 June 2005
2
The Challenge“many experiments have been less productive than they could have been
….many past campaigns of experimentation have contributed far less to the body of knowledge than they might have…”
The Response
• Implementing a multi-year experimentation campaign that is shaped by consistent adherence to a set of broad goals and designed to answer a set of related issues.
• Recognizing that military experimentation is a learning process - one that supports discovery and innovation - far more than a hypothesis-testing process to verify theoretical cause and effect relationships.
• Implementing proven techniques of analysis and research design that are adaptable to the experiment at hand.
The Fundamental Challenge of Experimentation
3
Purpose of Brief
To use a major TRADOC experiment (IE04) as an illustrative example of fundamental recurring experimental design issues
that are arising with battle command experimentation.
EndstateTo give the audience an understanding of battle command
experimentation, its challenges and recommendations on how to do it better.
“Out of intense complexities, intense simplicities emerge.”
-Winston Churchill
4
Outline
• IE04 Overview– Objectives– Battle Command Methodology– Analytic Approach
• Challenges to IE04– Concept– Technical– Training– Scenario– Schedule– Analytical
• Recommendations
5
IE04 Overview • Army Concept Development and Experimentation Program’s FY04 culminating
experiment, executed from 12-22 June 2004, was a human in the loop, simulation supported experiment designed to develop qualitative and quantitative insights to assess the ability of the UA to exercise effective battle command in a representative stressful future operating environment.
Sense Cognitively ProcessDistribute Process Present
The Warfighter’s Network
The Focus of KPP Analysis
Increment 1: The FCS network must enable battle command and provide situational awareness to the manned platform and dismounted soldier level.
Rationale: Battle command is the art and science of applying leadership and decision making to achieve mission success. Distributed operations and high tempo maneuver will demand rapid synchronization, swift adaptation of plans and control measures and direct exchanges across vertical and horizontal echelons to integrate joint intelligence, surveillance, and reconnaissance (ISR), fires and maneuver to achieve effects. The network must be dependable, and capable of functioning degraded, greater than 80% (Threshold)and 98% (Objective) static, and greater than 75% (Threshold) and 90% (Objective) mobile.
Reference: Change 3 to FCS ORD, 14 Apr 03
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IE04 Experiment Objectives
• Identify the effects on Battle Command actions and the ability of the UA to achieve mission success during varied network dependability conditions to support JROC and MS B Update decisions (decision).
• Inform the FCS Battle Command System software development (UFD) in support of the LSI software build (product).
• Identify and refine UA inter- and intra-nodal functions in support of UA O&O refinement and mission training plan (MTP) development (products).
• Based on recent TRADOC guidance, investigate a proposed Aviation Squadron organization and missions within the Maneuver UA (decision).1
1 While not part of the original FY04 ACDEP guidance, this objective was assigned and approved two weeks prior to the experiment.
These objectives were the FY04 ACDEP approved objectives and directly inform required decisions and the development of products.
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Study IssuesB
attle
Com
man
dFo
rce
Effe
ctiv
enes
sB
attle
Com
man
dEn
able
rs
Overarching Issue: What are the effects of varied levels of network dependability on the ability of a Unit of Action (UA) Commander to execute effective Battle Command and achieve mission success?
Sub-issue 1: What are the impacts on situational awareness at varied levels of network dependability ?
Sub-issue 2: How does the degraded network affect decision making during execution?
Sub-issue 3: How does the degraded network affect the ability of the UA to accomplish its mission?
Secondary Issue 1: What are the essential requirements and functionality of the FCS Battle Command System?
Secondary Issue 2: What are the necessary inter- and intra-nodal functions required to execute effective Battle Command?
Secondary Issue 3: How does the alternate aviation structure impact UA mission success?2
2 While not part of the original FY04 ACDEP guidance, this study issue was derived and approved two weeks prior to the experiment.
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Battle Command MethodologyIssue: What are the effects of varied levels of network dependability on theability of a UA Commander to execute effective battle command and achieve mission success?
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2
1
Movement to LD
Penetration
Exploita
OBJSquat
OBJ Legpress
UA
OBJDeadlift
OBJHack
UA S: 24.00 E: 35.00
S: 24.00 E: 39.30
S: 54.00 E: 55.00
S: 58.00 E: 60.00
S: 51.00 E: 55.00
S: 54.30 E: 58.00 3
2
1
Movement to LD
Penetration
Exploita
OBJSquat
OBJ Legpress
UAUA
OBJDeadlift
OBJHack
UAUA S: 24.00 E: 35.00
S: 24.00 E: 39.30
S: 54.00 E: 55.00
S: 58.00 E: 60.00
S: 51.00 E: 55.00
S: 54.30 E: 58.00 3
2
1
Movement to LD
Penetration
Exploita
OBJSquat
OBJ Legpress
UA
OBJDeadlift
OBJHack
UA S: 24.00 E: 35.00
S: 24.00 E: 39.30
S: 54.00 E: 55.00
S: 58.00 E: 60.00
S: 51.00 E: 55.00
S: 54.30 E: 58.00 3
2
1
Movement to LD
Penetration
Exploita
OBJSquat
OBJ Legpress
UAUA
OBJDeadlift
OBJHack
UAUA S: 24.00 E: 35.00
S: 24.00 E: 39.30
S: 54.00 E: 55.00
S: 58.00 E: 60.00
S: 51.00 E: 55.00
S: 54.30 E: 58.00
• Mission Success• Network &
BC Causality
Force Effectiveness
NetworkModelInputs
• Transmission Times• Processing Times
Network Degradation
Factors
• Weather• Terrain• Reliability• Enemy
AMSAA
Battle CommandFCS BC Metric
Dependability
• Message Completion• Message Timeliness
IndependentVariable
Dependent Variable
Network Model
(ALCES)
CombatModel
(Federation)
Force-On-Force Simulations
• Sensors behave IAW their certified performance data and contribute to decision-making IAW their operational employment in the scenario.
• Acquisitions by sensors exhibit inherent inaccuracies and do not necessarily portray ground truth.
Causality?
Surrogate C2System – MC2
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sality
?
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IE04 Experiment Architecture
XUA
Green Cell(Joint and Echelons Above)
BIC MI NLOS FSBAVNCA
XUA
FCS UA Deployed Command Post & Mobile Command Groups
Commander& Staff atFt Rucker
Commander& Staff at
Ft Sill
Commander& Staff at
CA2
UAX
Ft Lee
Aviation SUAFt Rucker
Fires SUAUA
X
Ft Sill
XUA
ME SUAUA
X
Ft KnoxFt Knox Ft Knox
Ft Knox Ft KnoxFt Knox &Ft Benning
RedCell
White Cell
Personnel609 participants
168 UA role players18 UEx role players
12 UEy and joint players24 different organizations
Players56% Active Duty
24% CGSC Graduates25% Staff Exp > Division
47% Future Force Experience
- UA O&O Plan (30 Jun 03).- UA Force Design (Increment 1).- FCS ORD (14 Apr 03).- FCS UA AMSAA Systems Book (v 3.0).- Caspian Scenario (v 2.0).- TRADOC DSCINT-approved capabilities-
based threat.
2d CAB:Entity level representation with company, platoon, and squad-level response cells
1st & 3rd CABs:Entity and grouped level representation with battalion-level response cells
Data Collection and
Analysis Team
63 participants19 different organizations
Ft Knox6 Players
Ft Knox11 Players
(All Sites)
Ft Knox
UExXX
Ft Leavenworth
Ft Lee
OTB(Ft Knox)
FireSim(Ft Sill)
ALCES(Ft Knox)
MC2(All Sites)
ATCOM(Ft Rucker)
SSE(Ft Benning)
SLAMEM(Huntsville)
Simulation Federation
WECM(Ft Knox)
CMS(Ft Knox)
EADSIM(Ft Bliss)
(Huntsville)
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Experiment ScheduleJanuary February March April May June
SeptemberFinal
Report
Experiment design development Experiment design refinement
Simulation architecture development Integration & testing
Scenario development Threat refinement Scenario modifications
Study issue development Definition of data requirements Data collection plan
Player training
Routine IPRs and updates
UA DEV II
AAR
Mon Tues Wed Thurs Fri Sat17 1814 15 16 191300
Pilot Test# 1
Sun20
June2004
1630-1700HotWash
0800Pilot Test #3
1630-1700HotWash
0800Pilot Test #4
AAR
24 2521 22 23 260800Maneuver
Day # 2
270800Seize Key
TerrainDay # 3
2100-2130HotWash
0800IsolateCoG
Day # 41845-1915HotWash
0800AttackCoG
Day # 5
Analysis
Analysis
Analysis
0800Set
ConditionsDay # 1
1930-2000HotWash
AAR
0800 Pilot Test
# 2
1630-1700HotWash
AAR
AAR
28 JuneBackbrief
MG Tucker
AugustIIR
TTPDevelopment
1300 Pilot Test
# 3
2115-2145HotWash
Analysis
1 JulyBrief
GEN Byrnes
SeptemberUA DEV III
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Challenges to IE04
• Compression of the preparatory schedule precluded complete and robust integration testing. Previously undetected technical problems emerged during the experimental phase resulting in the cancellation of one of the two planned trial runs.
• The ability to generate and capture reliable and consistent data from the supporting simulations was not achieved. Data output files were inappropriate for analysis, requiring the analytic team to rely only on qualitative data captured by human observers.
• The information management procedures implemented in the experimental network did not appropriately capture the capabilities of the envisioned FCS network. All information and data were simply broadcast throughout the experimental network, generating significant delays in information timeliness and influencing the observed decision-making processes.
• The representation of force capabilities was flawed:– The UA force representation deviated from the 30 June Increment I Threshold
capabilities. The implemented performance capabilities exaggerated the capabilities of the BCT.
– It was inconsistent across the supporting simulations. The application of effects in one simulation federate, for example, might not be represented in another federate, precluding any valid analysis of lethality or survivability.
These challenges prevented a quantitative assessment of the study issues.
As a result of these challenges, the planned analytic methodologies were dynamically modified to enable a collection of battle command processes and
enablers under different conditions.
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Experimental Design … What We LearnedThe experimental design and integrated timeline must be driven by,
and support, the objectives …
… to achieve a return on investment for our experimentation program, we must conduct more focused, appropriately resourced, and better planned experiments.
Concept: All of the current battle command concepts are not mature enough to enable a complete assessment of the ability and effectiveness of the UA to execute the O&O.
Scenario: Current scenario development processes do not account for limitations in the experiment design technical architecture.
Schedule: Slippages in critical dates and a lack of quality control adversely impacted experimental design. An integrated schedule with defined milestones, actionable decision points, and enforced quality control must be instituted.
Training: Current training strategies are not producing sufficient levels of player proficiency.
Technical: Only limited technical success was achieved due to a lack of rigorous thread testing and large-scale load and integration testing.
Analysis: While “One Team, One Report” produced an integrated approach to analysis across TRADOC, a campaign approach that matures the learning over the year might have better informed experimental design considerations and enabled experiment success.
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Concept Learning
The investigation of these concepts must be focused and integrated, based on common tools and assumptions, and accomplished with rigor.
While IE04 experimental design limitations impacted the quality of data and insights generated from the experiment, IE04 served as a forcing function to reveal several
conceptual areas that require further maturation … • Networked Fires – How does the networked fires process maintain discipline in the application of
fires and effects, while enabling the dynamic application of the UA Commander’s intent at the time and place of his choosing?
• Battle Damage Assessment – How does the UA Commander determine if desired effects (lethal and non-lethal) are achieved to enable an assessment of his PIR and a quick transition to subsequent actions?
• Battle Command in Urban Terrain - How does the UA set the conditions, conduct operations, and determine effectiveness in an urban fight?
• Information Management and Dissemination – How is information efficiently managed and disseminated to enable a shared level of SA among all echelons?
• Security of Sustainment – How does the sustainment organization and concept ensure a secure in-stride replenishment to maneuver elements to maintain combat power?
• Battle Command System Functionality – What functionality is required in the battle command system that will enable the execution of UA concepts and ensure compliance with JC2 requirements?
• Staff Structure – How do key UA elements interact, and what are their task and product requirements, to include interactions with higher, adjacent, and subordinate echelons?
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Illustrative Example of Concept Immaturity - BDA
HPT Early in Phase IIA
430 182 316 390
512312
450 280609 312
59960 2609359946 26187445450406335
561 273
544339
407335
O&O suggests “networked fires enable detection, delivery, and assessment in near-real time with every platform and soldier providing sensor input,” but, it is not clear how this concept:
• Generates BDA for non-lethal effects;Enables BDA when there is limited or no sensor coverage in engagement area, orOvercomes enemy deception and denial techniques employed against targeting.
The UA implemented TTP to enable BDA …
• Included BDA missions in the R&S plan.Displayed target status on the COP via networked fires.Cued BDA assets to targets via the networked fires AGM.Displayed BDA-completed targets on the COP.
… some recurring BDA issues from past experiments:
• Who manages BDA?• How is BDA conducted?• What assets conduct BDA?
“BDA must be able to tell the commander if he is succeeding
… it is a measurement of success for PIR.”
UA Cdr, AAR, 23 June 2004.
• The UA ISC dedicated ISR assets in the R&S plan to accomplish BDA tasks.
• These ISR assets were dedicated to BDA using the UA attack guidance matrix (AGM), and these assets were initially cued based on target nomination via the networked fires process.
The ISR Officer in MCG1 and the ISC NCO and Target Officer in the ISC used the COP target status displays to visually cue and dynamically manage BDA assets through BDA completion.
These personnel used the BDA completion status on the COP to manually track HPT and keep the UA Commander informed according to his PIR.
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Scenario Challenges
Broadcast Systems
Near Space
SIGINT & IMINT Aerial
Common Sensor (Army)
ER/MP UAV
Space Based Radar
Global Hawk & Predator
U- 2 SAR/EO/IR
MC2A
3 2U n c la s s i f i e d
U n c la s s i f i e d
X X3
P L B L U E
P L B L U E
X13
X12 O B J B L A IN E
O B J S E W E L L
O B J S H E R M A N
O B J K E N T O B J G R A N T
O B J C H E S S
O B J Q U E E N
O B J s L IO N , T IG E R
O B J Y A K
8 5 K M
U E O p e r a t io n s S k e tc h(D + 3 6 - D + 4 0 )
X1 1 0 1
X3 2 S T R
X1 7 3
X1 1
D + 3 6 /3 7 : C o n d u c t o p e r a t io n a l v e r t ic a l m a n e u v e r a n d t h e n a t ta c k to s e c u r e k e y te r r a in
D + 3 8 : A t ta c k s to s e c u r e a n a p p r o a c h
to is o la te t h e C o G
D + 3 9 /4 0 : A t ta c k s to s e iz eC o G (O B J B A T )
U N C L A S S I F IE D
U N C L A S S I F IE D
2 0 K M
7 2 K M
O B J B A T
4 6 K M7 0 K M
1 1 0 K M
7 0 K M
9 2 K M8 1 K M
3 0 0 K M
2 5 0 K M
3 D
ays
Pilo
tA
AR #
1
2 D
ays
Att a
ck ( R
eset
)
3 D
ays
At ta
ckA
AR
# 2
A A R # 32 D a y s
M o v e / A t ta c k (u r b a n )
P h a s e I IA
P h a s e I I I
UA dependencies on UE2 HIMARS Battalions
100 CAS sortiesSLAMRAAM Platoon
Engineer Battalion 5 TUAV Aerial Relays
1 x 8 AH64 for Mobile Strike Ops
Threat was multi-corps force - mechanized, paramilitary and militia - fighting throughout depth of their homeland, attempting to implement adaptive TTPs outlined in the future operating environment.
Scenario was scaled back and local hardware loading caused latency to the C2 devices
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Table M-13. Percent of Player Ratings Factors as Having a Positive, Negative, and Neutral Impact on
Performing Networked BC Factors Negative
Impact Positive Impact Neutral
Impact Technical Difficulties 80% 10% 10%
Simulation Fidelity 65% 12% 23%
Training 63% 19% 18%
Lack of Personnel in Player Roles 57% 8% 35%
Distributed Communication 46% 36% 18%
BC Enablers/Systems 31% 39% 30%
Organizational Design 22% 34% 44%
Operational Concepts 14% 44% 44%
Average Written Test Scores Across Administrations by Sites
0102030405060708090
100
Pre-training Post-training Post-exercise
Pre-training Post-training Post-exercise
Future Force Concepts MC2 Functionality
Perc
ent C
orre
ctUAMBL
Ft Sill
Ft Benning
Ft Leavenw orth
Ft Lee
Ft Rucker
Training ChallengesWith an immature and uncontrolled environment, conceptually and
technically, difficult to train players, pucksters, and observers.
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Technical ChallengesBattle Lab Collaborative Simulation Environment
(BLCSE)Battle Lab Collaborative Simulation Environment
(BLCSE)
Federation of ModelsFederation of Models
ATCOM
OF OTB
MC2
EADSIM
Fire Sim XXI
WECM
SLAMEM
Universal Controller
ALCES
Fort Rucker Fort Bliss/ Huntsville
Blue RWA; Red ADA Blue ADA; Joint EffectsRobotic Sensor Control
SIGINT Surrogate C2 System Comms Effects
Indirect Fires; NLOS Joint ISR All other combat entities
Fort Sill HuntsvilleCMS
MinesSSE
Fort Benning
IC
TRAC ESS
TRAC ESS
SQL SERVER
SQL SERVER
Data Collection/Management
PostProcessing
Exercise ManagerQuality Control
Exercise ManagerExercise Manager
FederationQuality Control
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Event Issue Simulation Support
Duration
Blue Red White
Division Advanced
Warfighting Experiment
Capture the impact of information as an element of combat power within the division construct
Full training federation
including CBS & TACSIM
All divisional C2 nodes to include division Main, TAC and rear, all brigade CPs and selected battalion CPs
Complete WCOPFOR team
Supplemented BCTP team, TRADOC SMEs, TRAC Analysis Team and CAP team
10 days + several train-up exercise and rehearsals
Strike Force MAPEX
Investigate four alternative SF force designs
NoneFour teams of TRADOC SME plus one serving Bde Cdr - 50 players
4 representatives from TRADOC DCSINT
TRAC Analysis Team, Ft Knox Proponent rep, Greybeard to facilitate AARs
1 week
Strike Force Headquarters
Rockdrill
Investigate information exchange requirements within the headquarters
LAN enabling email
exchange
Representative manning of SF headquarters - 75 players
4 representatives from TRADOC DCSINT
TRAC Analysis team, TPIO Architecture representatives, Ft Knox Proponency rep
1 week
Strike Force Headquarters
STAFFEX
Investigate capability of SF commander to exercise battle command with proposed HQ design in varying scenario settings
Eagle-Modsaf plus live
adjudication - scenario team
Complete manning of one shift of the SF headquarters - 125 players
10 representatives from TRADOC DCSINT
TRAC Analysis Team, BCTP OC team, Greybeard for conceptual oversight, TRADOC SF team
2 weeks
SBCT CAMEX
Investigate alternative SBCT design options
JANUSTwo teams of TRADOC Commandants, Deputies & staff - 30 players
6 representatives from TRADOC DCSINT
TRAC Analysis Team, CAC OC Team
2 days
FCS UA C4ISR
experiment
Investigate capability of UA commander to exercise battle command given proposed C4ISR architecture
JVB
One shift of UA headquarters plus all subordinate battalion headquarters and selected company-level elements - 85 players
50 representatives from TRADOC DCSINT - role playing Corps to Brigade level commanders
TRAC Analysis team, White Cell to adjudicate gaming, Green cell to represent higher headquarters
3 weeks of training plus 2 weeks of gaming
Player participation
Analysis - Not a Single Data Point
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SummaryIE04 enabled some objectives to be qualitatively informed … all of these
objectives require additional efforts.
• Identified some of the challenges and effects on Battle Command (UA O&O).
• Identified functionality and required capabilities for the Battle Command System (Battle Command UFD and FCS ORD).
• Identified and refined the UA inter- and intra- nodal functions and tasks (UA O&O, doctrine, MTPs).
Experimentation Maturation
• Experiment design and scheduling processes.
• Scenario design implications.• Technical integration and testing
methodology associated with “loaded networks.”
• Advances in analytical methodology and tools.
• Hardware and software requirements.• Training requirements and recommendations.
Product Development and Refinement
• FCS ORD and UA O&O:• How to fight doctrine, logistics concept.• Organizational changes (aviation, UA CPs).• UA/UE roles and responsibilities.
• Operations Mode Summary/Mission Profile.• User’s Functional Description (UFD).• FCS System of Systems Training Plan (STRAP):
• Inter and Intra-nodal tasks (MTPs).• Network Fires protocol (AGM).
As a forcing function, IE04 also enabled the following:
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Analytical Challenges
TrainingC
once
pts
Tech
nica
l
Analytic Rigor of Objectives
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Recommendations • Concepts
– Focus the experiment on such concepts that have a certain level of maturity
– Ensure the concepts are documented and understood
• Technical – Based on the analytic venue, select the federation that is
appropriate not just convenient– Test, test, test, VV&A, rehearse– Conduct VV&A of entire environment (data, federation,
terrain, OA/SA, Scenario, TTPs, training)– Document capabilities and limitations
• Training– With concepts and a technical environment that is
understood, focus training and build staff teamsWith these three recurring fundamental challenges addressed,
the analytic rigor that is desired can be realized
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A Design for FY05 Experimentation …
-
UEyxxx
SoldierThread
Manx
Sustx
Firesx
MEx
Avnx
RSTAx
UTExx TSC
x4
Build 1 (Jan 05)
Build 0 (S
ep 04)B
uild 2 (May 05)
IE 05 (S
ep 05)-
UEyxxxUEyxxxxxx
SoldierThread
Manx
Manx
Sustx
Sustx
Firesx
Firesx
MEx
MEx
Avnx
Avnx
RSTAx
RSTAx
UTExx
UExxx TSC
x4
FY05 experimentation, or OMNIFusion, represents a “build
process” that enables a shift infocus from UA to UEx and SUAs,and facilitates an experimental
design process that is based oncampaign qualities. This campaign-
quality build process addressesconcerns from FY04
experimentation, provides a crawl,walk, run approach, and better
enables the achievement of FY05objectives.
Omni FusionIE 05
• L-V-C SIMEX• BCBL-L
Omni FusionBuild 2
• STAFFEX andRehearsal
• BCBL-L
Omni FusionBuild 1
• SIMEX• UAMBL
Omni FusionBuild 0
• WARGAME• BCBL-L
Enabling Concept Development Experiments