Sentinel Week 4 H4D Stanford 2016

Team Sentinel

● Team members:

○ Jared Dunnmon

○ Darren Hau

○ Atsu Kobashi

○ Rachel Moore

● Cumulative # of interviews: 39 + 13

○ Users: 4 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

● 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

○ John Chu (Colonel, US Army)

○ Todd Cimicata (Commander, US Navy)

● Problem Sponsor

○ Jason Knudson (Lieutenant, US Navy 7th Fleet)

● Tech Mentors include:

○ Elston ToChip (Palantir)

Customer Discovery

Hypotheses Experiments Results Action

We want automated data layering

REFINED

- Interviews with CMDR Pablo Breuer (N3/6), CMDR Rob Williams (N0)

- There is too much layering going on- Info overload, esp in Straits of Malacca- Need a better filtering method

- Revamp the MVP to focus on filtering layers- Get a sanitized GCCS screen of Straits of Malacca

A common, easily-searchable database is desireable

VALIDATED

- Interviews with CMDR Rob Williams (N0), CMDR Chris Adams (N3), CTR3 Joseph Baba (N2), CMDR Pablo Breuer (N3/6)- Engagement with Elston ToChip (Palantir)- Interview with Chad Dalton, Pat Kelly (OGSystems)

- Need to submit help ticket to access certain databases- Palantir often interacts with customers who have siloed datasets- 6+ databases that people search through manually - takes hours

- Develop separate MVP to test database functionality- How to establish common database without losing context-specific attributes?- What are the data feeds for 7th Fleet vs. PacFlt vs. PACOM?

Analysts will analyze, no need to do our own algorithms

INVALIDATED

- Interviews with Dr. Evelyn Dahm (SOCPAC advisor, J5/8), CMDR Rob Williams (N0), CMDR Silas Ahn (N2)

- Would be helpful to establish baseline and alert when anomaly occurs- Want push notifications when a ship violates known patterns

- Determine example scenarios that 7th Fleet wants to monitor

Customer Discovery



REFINED





VALIDATED


- Need to submit help ticket to access certain databases- Palantir often interacts with customers who have siloed datasets- Analysts are spending too much time developing their own custom ETL tools



INVALIDATED




Customer Discovery



REFINED





VALIDATED


- Need to submit help ticket to access certain databases- Palantir often interacts with customers who have siloed datasets- People use data analysis products to support preconceived ideas



INVALIDATED




Customer Discovery



REFINED





VALIDATED


- Need to submit help ticket to access certain databases- Palantir often interacts with customers who have siloed datasets- JIOC, PacFlt, 7th Fleet do not see the same feeds -> may lag each other by 2-6 hours!



INVALIDATED




Coast Guard data fusion center visit scheduled for Friday (4/22)

Customer Discovery

Research- Interviews to assess needs, organizational dynamics, procurement strategy- Site visits to see current practices-Understanding current workflow

Prototype- Evaluate existing sensor platforms with commercial partners- Integrate sensor feeds of interest into prototype platform- Compile existing data resources- Create representative “fake” datasets- Evaluate relevant ML algorithms for prediction and rules for push alerts- Iterate on human-machine interaction

Strategic Decision MakersVADM Joseph AucoinADM Scott Swift (PacFleet)ADM Harry Harris (PACOM)

Analysts (N/J2)E.g. Jason Knudson, John Chu, Jed Raskie, Joseph Baba Operators (N/J3)CDR Chris Adams (7th Fleet)

Planners (N/J5)Need to find these people

- Common and consistent view of the Area of Responsibility (AOR)

- Timely operational decisions

- 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 (THIS SECTION IS A WORK IN PROGRESS!)

- Build solution that integrates with current systems (e.g. GCCS)

- Work with PMs and key influencers to determine optimal funding/dissemination avenues

- Deploy prototype, confirm buy-in and update features

- Scale deployment, improve product as necessary

Fixed- Buying proprietary data- Software tools- Hardware evaluation + prototyping equipment- Evaluation of commercial products

Prototyping- Existing sensor platforms and feeds- Existing deployment platforms- 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 want to leverage their platforms

Beneficiaries

Mission AchievementMission Budget/Costs

Buy-In

Deployment

Value Proposition

Key Activities

Key Resources

Key Partners

Military- 7th Fleet + designated sponsor- Naval Postgraduate School (NPS)- Office of Naval Research (ONR)- Acquisition Personnel

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- Access to sample incoming sensor feeds

Variable- Travel for site visits, pilots- R&D personnel- Manufacturing/Development

IMPROVE TACTICAL AND STRATEGIC DECISION

MAKING VIA BETTER DATA HANDLING

(1) Rapid Strategic Decisionmaking via Improved Reporting

(2) Improved Tactical Decision Making via Enhanced Information Sharing

(3) More Effective Analysis via Searchable, Visualizable Data Integration

(4) Predictive Intel and Alerts (e.g. Machine Learning)

ENHANCE INCOMING DATA STREAMS

(1) Improved Collection of Existing Data Streams (e.g. Fishing Broadcasts)

(2) Painless Incorporation of Multiple New Sensing Modalities

Products& Services

- Timely data- Good UI/UX for

presenting data

- Streamlined reporting process

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

- Poor quality/lack of data- Latency of data ->

insight

Admiral/Strategic Decision Maker

Value Proposition Canvas

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

Customer Jobs

Gains

Pains

Gain Creators

Pain Relievers

- Contextualized, object-oriented database

- Compatible data format- Incorporate multiple data

streams

- Collect & analyze data

- Communicate findings

- Piece together contextualized awareness

- More actionable insights

- Faster identification & response times

- Easy-to-use

- Incorporation of context is manual/mental

- Poor quality / lack of data- Latency of data -> insight

Analyst (N2)


Products& Services

- N/A

- Actually a common operating picture!

Customer Jobs

Gains

Pains

Gain Creators

Pain Relievers

- No hardware to deploy so no risk of asset or personnel loss

- Fewer change orders

- Utilize assets and human capital in order to obtain ISR data on adversary or regions of interest

- Better allocation and deployment of assets

- High manpower, time- Operator error- Safety concern for deploying

in unfriendly territory- Struggle to redeploy systems

on short notice (<12 hours) = frustration

Operations (N3)


MVP

MVP

MVP

Questions?

Customer Workflow

Customer Workflow

N2

N3

N2(“owns”

the intel)

N3(“owns”

the assets)

Ready-To-Use DataDeployment

Data Acquisition

Data Analysis

Data

Order/Decision

MVP (1 week ago)

AIS Weather

MVP (1 week ago)

AIS Weather

MVP (1 week ago)

AIS Weather

Data Acquisition

ContextualizedDatabase

MVP (2 weeks ago)

Deployment

Last Month

Today

Object-orientedDatabase

Query

- What data is most useful to capture?- What sensor modalities can capture?- What products exist?

- What deployment options exist?- What is easiest to deploy?- What is “good-enough” time to data acquisition?- What is the deployment process?

- Is .kmz format all that is necessary for compatibility?- What do companies like Palantir do today?

Education

Sentinel Week 4 H4D Stanford 2016