agile, bmnt, business model, corporate innovation, customer development,dod,nsa, diux, h4d, hacking for defense, lean, lean launchpad, lean startup, stanford, steve blank

1. Team Sentinel
● Team members:
○ Jared Dunnmon
○ Darren Hau
○ Atsu Kobashi
○ Rachel Moore
● Cumulative # of interviews: 73 + 12
○ Users: 3 Experts: 9
● What we do: Enable rapid, well-informed decisions by establishing a common maritime
picture from heterogeneous data
○ Open and automated data aggregation (i.e. incorporate open source data)
○ Flexible layering and filtering with improved UI/UX
○ Enhanced intel through contextualization and easily accessible, common database
○ Identifying deviations from baseline by utilizing historical data
● Why it matters:
○ Information overload
○ A2/AD prevents deployment of traditional ISR in a timely manner
○ Data aggregation platforms and database access in PACOM appear extremely manual
● Military Liaisons
○ --- (Colonel, US Army)
○ --- (Commander, US Navy)
● Problem Sponsor
○ --- (Lieutenant, US Navy 7th Fleet)
● Tech Mentors include:
○ --- (Palantir)

2. QUOTE OF THE WEEK
“THAT’S CLASSIFIED.”

3. Contents
1. Customer Discovery
2. Mission Model Canvas
3. Value Props
4. Mission Achievement
5. MVP

4. Hypotheses Experiments Results Action
Significant data
about many data
fusion programs
available at the
unclass level
IN PROGRESS
- Interviews with a variety of
stakeholders at PACOM
-MVP from last week: asking
our contacts to fill out a
spreadsheet indicating their
awareness of different data
fusion tools
- Suboptimal response
levels on ask from last
week (possibly due to
major 7th Fleet operations)
-Will continue this week
- Visit to San Diego
- Continue pushing this
efforts this week
IUU fishing
problem is a good
proxy problem for
7th Fleet MDA with
more widely
available data
sources
PARTIALLY
VALIDATED
- Interviews with PACOM
COP and GCCS expert
-Interviews with IUU fishing
stakeholders with previous
Navy experience
-Research on existing IUU
fishing tools
- Access to open-source
visualization/analysis
tool from UN Fishing and
Agriculture Organization
- Understanding of ship
behavior patterns (AIS on
buoys, insights on ship
tracking/movements)
-Won’t be able to
understand everything
Navy does on MDA
analytics, but a good start
- Working with nonprofits
to get access to marine
ship data
-Use IUU fishing problem
to demonstrate rapid
development of flexible
data fusion/analytics
capability
Customer Discovery

5. Hypotheses Experiments Results Action
Physical “sensors”
are the only way to
add new data
feeds for 7th Fleet
INVALIDATED
- Interviews with NPS
researchers
-Interview with PACOM
SME on GCCS and COP
-Interview with MFIC
personnel
- Distributed marine
sensors are one possible
way to think about this
capability
-Drones + ship
recognition emerging
-Social media an
emerging data source
-Considering integration of
these additional
future/non-traditional data
sources into our MVP
Flexible integration
of available sensor
feeds into both
COP and intel
functions would be
a useful capability
VALIDATED
-Interviews with NPS
personnel researching
applicability of UAVs to
MDA
-Interviews with IUU (Illegal,
Unreported, Unregulated)
fishing stakeholders on
analog problem
-Interview with PACOM
SME on GCCS and COP
- Right now, a key general
problem (exacerbated by
A2/AD) is that data feeds
that are available can
change rapidly
- COP and intel systems
that allow for flexibility in
visualization and analysis
enable new sensor
prototyping and effective
use of existing data
- Focusing MVP on a way
to flexibly and seamlessly
use whatever data is
available (algorithms and
visualization)
Customer Discovery

6. Research
- Interviews to assess needs,
organizational dynamics,
procurement strategy
- Site visits to see current practices
-Understanding current workflow
Connecting People and
Programs
- Ensuring tool developers and
users are aware of one another
- Finding functional gaps to fill
Prototype
- Compile existing data resources
- Create representative “fake”
datasets
- Evaluate relevant ML algorithms
for prediction/rules for push alerts
-Create demo of flexible data
fusion/analytics for IUU fishing
Strategic Decision Makers
Analysts (N/J2)
Operators (N/J3)
Planners (N/J5)
IUU People (working on it)
- Timely operational decisions
-Common and consistent view of the Area of Responsibility (AOR)
-Flexible integration of new feeds into COP and analytics
- Decreased time to predict hot spots, ID & differentiate threats
- Reduced time for analysts to find information and draw conclusions
- Prototype operability + demonstrated scalability
Data Fusion/Sensor Integration Software
- Build solution that integrates with current systems (e.g. GCCS,
QUELLFIRE, FOBM, EWBM, INSIGHT)
- Work with PMs and key influencers to determine optimal
funding/dissemination avenues and integration with current tool
pipeline
- Deploy prototype, confirm buy-in and update features
- Scale deployment, improve product as necessary
Fixed
- Buying proprietary data
- Software tools
- Evaluation of commercial products
Prototyping
- Existing sensor platforms and feeds
- Academic research
- Existing data fusion platforms
Scaling
- Available commercial + military data
- Existing database tools (Palantir,
AWS)
- Need commanding officer to
confirm decision-making benefits
- Need intelligence officers from ONI
/ N2 and operators from N3 to
confirm effectiveness of insights
- Need IT approvals to integrate into
systems
- Need support of commercial
partners if we want to leverage their
platforms
-Need support of existing
PMOs/S&T personnel to make sure
we’re not duplicating work
Beneficiaries
Mission Achievement
Mission Budget/Costs
Buy-In
Deployment
Value
Proposition
Key Activities
Key Resources
Key Partners
Military
- 7th Fleet + designated sponsor
- NPS/ONR
- Acquisition Personnel
- Existing PMOs/PORs
- Other Fleets
Commercial
- Distributed sensor platform
companies (i.e. Saildrone, AMS)
- Data analytics (i.e. Palantir, Google)
Academic
- Universities (i.e. University of Hawaii)
- National Labs (Lincoln Labs, Sandia)
Other
- IUU fishing + anti-smuggling
stakeholders (i.e. Coast Guard, PNA)
- Disaster relief agencies
Mission: Enabling Rapid, Well-Informed Decisions from Heterogeneous Data
Testing
- 7th Fleet assets for pilot
- Research barge
- Access to model analyst data
interface and in-development tools
- Access to sample incoming sensor
feeds
Variable
- Travel for site visits, pilots
- R&D personnel
-Development
IMPROVE TACTICAL AND
STRATEGIC DECISION
MAKING VIA BETTER DATA
HANDLING
(1) Rapid Strategic
Decisionmaking via Improved
Reporting and Coordination
(2) Improved Tactical Decision
Making via Timely, Accurate,
Information Sharing
(3) More Effective Analysis via
Searchable, Visualizable,
Source-Flexible Data
Integration (Layering &
Filtering)
(4) Predictive Intel and Alerts
(e.g. Machine Learning) Flexibly
Applied to Available Data and
Rapidly Updateable to Account
for New Sources
ENHANCE INCOMING DATA
STREAMS
(1) Improved Collection of
Existing Data Streams (e.g.
Fishing Broadcasts)
(2) Painless Incorporation of
Multiple New Sensing
Modalities
(3 Integration of Incoming Data
Streams with Existing Object-
Oriented Database

7. Products
& Services
- Timely data
- Good UI/UX
for
presenting
data
- Streamlined
reporting process
- Improved
coordination
across ranks
- Utilizes current
tool pipeline
Customer
Jobs
Gains
Pains
Gain
Creators
Pain
Relievers
- Good UI/UX
- Platform
incorporates more
data streams
- Platform is robust
and can handle
drop out of data
streams
- Allocate assets
- Identify,
eliminate
threats
- Predict hot
spots
- Safety of team
- Projecting
peace, stability
in region
- More informed
decisions
- Faster decisions
- Decisions made
on most up-to-
date info
- Poor quality/lack of
data
- Latency of data ->
insight
Admiral/Strategic Decision Maker
Value Proposition Canvas
Customer persona:
● 3 or 4 star admiral
● Born in late 1950’s
● Have their own office on-base
● Gives out challenge coins
● 30,000 ft view thinker
● Spent entire professional career
in Navy (deeply ingrained
culture)

8. Products
& Services
- Contextualized,
object-oriented
database
- Algorithms for
processing,
analyzing data
- Ability to search for trends
across database
- Integration of disparate data
sources
- Automation of data analysis
- Improved UX/UI
- Predictive notifications
- Filtering and layering features
- Tool architecture is flexible and
intelligent
Customer
Jobs
Gains
Pains
Gain Creators
Pain
Relievers
- Compatible data format
- Incorporate multiple data
streams with existing
object-oriented database
- Integration into current
processes is simple
- Collect & analyze
data
- Communicate
findings
- Piece together
contextualized
awareness
- More actionable insights
- Faster identification & response times
- Easy-to-use
- Information continues to be processed
and visualized even if data streams are
added/dropped (no Christmas Light
effect)
- Incorporation of context is
manual/mental
- Poor quality / lack of data
- Latency of data -> insight
- Long onboarding processes
Analyst (N2)
Value Proposition Canvas
Customer persona:
● Sits in front of computer all day
● Job is normally boring with bursts
of excitement
● Some may have constantly
varying hours/schedules
● “19 year old from Oklahoma”
● Regimented schedule
● May or may not like what they do

9. Products
& Services
- N/A
- Actually a common
operating picture!
- Data is actually synced
across databases
- Tool architecture is flexible
and intelligent
Customer
Jobs
Gains
Pains
Gain Creators
Pain
Relievers
- No hardware to deploy so
no risk of asset or
personnel loss
- Fewer change orders
- Training and integration
with current processes is
simple
- Utilize assets and
human capital in
order to obtain
ISR data on
adversary or
regions of interest
- Timely and enhanced allocation and
deployment of assets
- Information continues to be
processed and visualized even if
data streams are added/dropped (no
Christmas Light effect)
- High manpower, time
- Operator error
- Safety concern for
deploying in unfriendly
territory
- Struggle to redeploy
systems on short notice
(<12 hours) = frustration
- Long onboarding processes
Operations (N3)
Value Proposition Canvas
Customer persona:
● General sense that N2 and N6
“work” for them
● “19 year old from Oklahoma”
● Regimented schedule
● May or may not like what they do
(green indicates that validation is still
needed)

10. Beneficiary Mission Achievement
Intelligence
Analysts
- Decreased time to aggregate data, classify and differentiate surface vessel
activity, and present conclusions.
- Flexible integration of new feeds into analytics
Operators - Real-time (no lags of 2-6 hours!) common operational picture (COP) of surface
vessel activity with notifications of abnormal activity based on algorithms and
analyst conclusions.
- Flexible integration of new feeds into COP
Strategic Decision-
maker
- Up-to-date information on activity in AOR
- Better understanding of what data contributed to analysis in CUB.
Mission Achievement

11. MVP
Pew Charitable Trusts Virtual Watch Room

12. MVP
Global Fishing Watch

13. MVP: Modular Intake, Algorithm, and Display

14. MVP: Modular Intake, Algorithm, and Display

15. MVP: Modular Intake, Algorithm, and Display

16. MVP: Modular Intake, Algorithm, and Display

17. Thank you!
Any questions?

18. Customer Discovery - Get/Keep/Grow Diagram
Awareness Interest Consideration Purchase Keep Unbundling Up-sell Cross-sell Referral
Activity
&
People
- Evangelist &
advocate from
originator Flt
- ???
Corey
Hesselberg,
CDR Jason
Schwarzkopf,
MIOC watch
standers
- Buy-in from
flag officers
- ADM Swift,
VADM Aucoin,
RADM Piersey
- N8/9
- Dave
Yoshihara
(PacFlt N9)
- 7th Fleet ???
- Maintainers
(N6)
- Bob Stevenson
(PacFlt N6)
- 7th Fleet ???
N/A Expanding
COP & intel
extensions /
functionality
within 7th
Fleet
Expanding
user base
within 7th
Fleet
Expanding
tool set to
other fleets
Metrics % people who
have heard of
program
before vs after
*how to
reassess?
# people who
say “we want
this”
Seems
binary… any
recommendati
ons?
# Systems
outfitted
?? ?? ?? # users within
7th Fleet using
tool
# fleets using
tool

19. Map of System Functions and Needs
QUELLFIRE
GCCS (1)
FOBM
STORAGE/
COMMS
CST
GCCS (3)GCCS (2)
STORAGE/
COMMS
STORAGE/
COMMS
Sensors Sensors Sensors
.oth-.json Translator
Visualization
Analytics
Ship-to-Ship Sharing
Long-Term Storage
KEY NEEDS
FUNCTIONS
&
PROGRAMS
SHIP 2 SHIP 3SHIP 1

20. MVP: Software Domain Awareness
Program POC Organization
Function &
Goals
To be used
by whom?
Security
Level Status Contract History Inputs
Technical
Details
CSII
Insight
MTC2
Quellfire
DCGS-N
Increment 2
C2PC
HAMDD
SeaVision
GCCS
EWBM
RC2
(Resilient
C2)

21. Sample In-Development Product: ONR/CTI EWBM Tool

22. MVP (3 weeks ago)

23. MVP (3 weeks ago)

24. MVP (3 weeks ago)

25. MVP (4 weeks ago)
AIS Weather

26. MVP (4 weeks ago)
AIS Weather

27. MVP (4 weeks ago)
AIS Weather

28. Customer Workflow
N2
N3
N2
(“owns”
the
intel)
N3
(“owns”
the
assets)
Ready-To-Use DataDeployment
Data
Acquisition
Data
Analysis
Data
Order/Decision

29. Customer Workflow

30. Key Acquisition Paths
○ Linking in with an existing POR (PMW-150, etc.)
■ Pros: Allocated funding, long-term integration plans
■ Cons: Long timescale, getting in the door
■ POCs: ONI, SPAWAR (Stan Kowalski), Primes
■ Source of Excitement: TBD
○ Rapid Acquisition Pathways (Limited Objective Experiments, Rapid Reaction
Technology Office)
■ Pros: Speed, Close to user, Don’t have to go through Navy (other services
work)
■ Cons: Limited spending authority
■ POCs: 7th Fleet (Jason Knudson), DHS (Chuck Wolf)
■ Source of Excitement: Rapid deployment, changed acquisition model
○ DARPA
■ Pros: Development mindset, existing programs (Insight) that are well-aligned,
deployment authority/capability to pay for deployment to end-users

31. Sample Deployment Path (Software, POR Path)
1. Operational testing to make sure meets military specs (engage SPAWAR for this)
a. Ensure NSA-standard Information Assurance (IA)
i. Lock down system and code
ii. Make sure no category 1,2,3 in code - backdoors, exceptions, etc.
b. Observe appropriate NIST protocols (TBD)
2. First, limited deployment to evaluate functionality (on testbed system or specific asset)
3. Then, if integrated into a POR:
a. Deployed on whatever platform is needed
b. Moves into sustainment phase
c. Think about disposal & replacement--we want continuous improvement!
4. IT installs where required
a. Technical support install software and make sure up and running
b. Maintains communications systems and networks
5. Personnel training for system operation and maintenance
a. CTMs focus on maintaining classified systems & special collections abilities
WE WILL BE GETTING MORE DETAIL ON THIS GOING
FORWARD!