Accelerating Innovation through Graph Thinking

Accelerating Innovation Through Graph Thinking
Neo4j Innovation Lab

Alessandro Svensson
Head of Neo4j Innovation Lab
San Mateo, California

A diﬀerent approach to
adopting Neo4j and Graphs

3
Innovation & Digital
Transformation
“Connected Data is Part of
Strategic Future”
1
Developers
A Known Problem to
Solve with Graphs
2
Business
user
Use Cases are a
Proven Fit
Neo4j
Adoption
Paths

‣ Connected Insights
Strategically Signiﬁcant
Use Cases
‣ Predictions
‣ Recommendations
‣ Knowledge Networks
Leveraging data to make:

Strategically Signiﬁcant
Use Cases
Connectedness / Strategic Direction Legacy / Reality

Enterprises derive
extraordinary value from
connections in their data
Enabled by Connections
But data is stored with
legacy technology in silos
Held Back by Legacy
Companies Are:

Impact when Innovating
with Graphs
Paradigm Shift
Information
Maintenance
Multi-silo

Research
Business Domain

Paradigm Shift Adopting Graphs
(Developers/Architects/Data Scientists)
Knowledge Networks
Predictive

Maintenance
Cross-silo

Research
Transformation
Impact when Innovating
with Graphs
Information
Maintenance
Multi-silo

Research
Business Domain

Digital Transformation with Graphs

Airline-customer
Major European Telco
Major US Telco
Online Retailer
Top tier Management Consultant
Topp tier Investment & Retail Bank
Top 5 Software Company
Fortune 100 Financial Services Company
H120172014 2015 2016 H22017 2018
200
Digital Transformation with Graphs

A 3.5 day workshop — The Innovation Lab Sprint

Guaranteed

Viability/Value
Proposition
Discovery
Ideation
Using design thinking to
understanding the underlying
needs for what to innovate
What?
Technology/
Data Science
Understanding technical limitations and
how they affect product and services,
and deﬁning the requirements to
capture and connect your data
How? Why?
Will this affect cost and revenue for
an existing business logic, or set
your organizing up for executing on a
new business logic?
Three Focus Areas

Viability/Value
Proposition
Discovery
Ideation
Technology/
Data Science
The Innovation Lab
Sweet Spot
Three Focus Areas

Our Methodology 🥜
Neo4j Innovation Lab Playbook, 2019

Identify Target
Use Case
Generate
Data Model
Related “Graph
Questions”
Executive Feedback
Presentation
Build Prototype/
Wireframes

Key entitiesNorth StarOpportunitiesChallenges Identify Target
Use Case
Generate Data
Model
Related “Graph
Questions” Executive Feedback
Presentation
Build Prototype/Wireframes
Use Case Generation
Day 1
Whiteboard Model
Day 1

Executive Feedback
Presentation
Executive Feedback
Presentation
Use Case
Generate Data
Model
Related “Graph
Questions”
Source data to
populate model
Build QueryImport Data
Materialize Model
Day 2

Executive Feedback
Presentation
Executive Feedback
Presentation
Use Case
Generate Data
Model
Related “Graph
Questions”
Source data to
populate model
Storyboarding/
Mockups
Identify Stakeholders /
Personas / Synopsis
Craft Scenario
Day 2
Materialize Model
Day 2

Executive Feedback
Presentation
Executive Feedback
Presentation
Use Case
Generate Data
Model
Related “Graph
Questions”
Source data to
populate model
Storyboarding/
Mockups
Personas / Synopsis
Build Prototype
Day 3

Executive Feedback
Presentation
Executive Feedback
Presentation
Use Case
Generate Data
Model
Related “Graph
Questions”
Source data to
populate model
Storyboarding/
Mockups
Personas / Synopsis
Finalize & Present
Day 3.5

Case Study

31
Preventing Burn Outs with
Connected Health Care
Data
XXMonth2017

32
- A Occupational
Healthcare company

33
This is where they came
from

34
Previa had a problem:
Too much data and no clue
what to do with it

Today
(Many users,
poor data-value gains)
Potential Future
(Huge potential in data,
substantial product
development gains)
Intelligence
Receptors
Data Quality, Connected Data, Real-time Analytics etc.
Users,Consumers,Thingsetc.

38
Previas advantage
Companies
as clients
7500 1.1M
Swedish
employees
365K
Sick leave
notifications/year
40K
Health
examinations/year

39
Focus: Sick leave data
Employees
since 2005
180K
Real-time
data
Short term
absence
Long term
absence

41
7July2017
The Whiteboard Model

42
Absence
Person
Condition
Service
HAS_DEPARMENT
EMPLOYS
OFFERED_SERVICE
FIRST_ABSENCE
USED_SERVICE
ABSENCE
FIRST_ABSENCE
DUE_TO
HAS
Data model from LAB sprint
Department
Condition
Absence
Person
Company
Service

43
Department
Employment
Condition
Absence
Person
Service Use
Company
Service
Category
Condition
Category
Service
Notiﬁcation
MANAGER_AT
HAS_EMPLOYMENT
HAS_NOTIFICATION
DIAGNOSED_WITH
HAS
HAS_CONDITION
BELONGS_TO
USES
HAS
PART_OF
BELONGS_TO
NEXT_ABSENCE
Data model today

46
CompanyEmployment
Condition
Absence
Person
Service
HAS AT
HASDUE_TO
DIAGNOSED_WITH
H
AS
USE

47
The Prototype
Notiﬁcations in real-time (no more
pre-calculated queries)
Current real-time status, and
previous events
Status-bar updated by traversing
entire network

48
En person bedöms ha medelhög risk för långtidssjukskrivningar
En person har sjukanmält sig för upplevd arbetsrelaterad frånvaro
Måndag 28 januari
Avdelning C - 56 anställda
Måns Månsson
Senast uppdeterad: 2018-01-20, kl: 11.24
Hitta oss Meny
Idag Historik Sök personal
varav 2 arbetsrelaterade
Frånvaroorsaker Korttidsfrånvaro
Långtidssjukskrivningar
Inﬂuensabesvär 5
3
3
1
1
Övre luftvägsinfektion
Stressrelaterade besvär
VAB
Sekretess
Frånvarande idag
5 personer tillbaka idag
Måndag 28 januari
Visa lista
Planerade återkomster kommande 7 dagarna
Friskanmälda personer per dag
3
Anna-Klara Larsson, Ekonomi
Beshad Farah, IT
Tony Rov, HR
1 3 0
Tis Ons Tors Fre
2 1
Lör Sön
5
Mån
13 frånvarande
3 frånvaroanmälningar idag

49
1
1
VAB
Sekretess
Frånvarande idag
Namn Typ av åtgärd
Lena Karlsson ACT-kurs
Tis Ons Tor
5 personer tillbaka idag
Frånvarohistorik
Antal personer frånvarande senaste 7 dagarna
Innevarande period
Samma period föregående år
Måndag 28 januari
Pågående åtgärder på avdelningen
Åtgärd börjad Åtgärd avslutas
2017-06-16 2017-06-16
Fre Lör Sön Mån
Visa lista
Planerade återkomster kommande 7 dagarna
Friskanmälda personer per dag
12
3
Anna-Klara Larsson, Ekonomi
Beshad Farah, IT
Tony Rov, HR
1 3 0
Tis Ons Tors Fre
2 1
Lör Sön
5
Mån

CRMCRM
51
Architecture
Stats
React, Apollo Frontend
Stats
GraphQL Backend
Stats
Data Collector
Data Warehouse
MSSQL
3Q
Lime
Visma
CRM

52
From old, to prototype, to new

53
Neo4j Innovation
Lab sprint

“Strategy”
Customer’s Team
(Between 3-8 participants)
“IT”
“Digitization” “Sales”
“Operations” “R&D/Innovation”
Neo4j Field Engineer
• Facilitates graph-modeling exercises
• Expert in Neo4j/Architecture & Data Science
• Cypher-queries for prototype
UX-designer
• Facilitates storyboarding/wireframing
• Builds UI-tool for prototype
Labs Leader
• Head facilitator & Team Leader
• Facilitates the use case generation-segment
• Project manages prototyping
Neo4j Innovation Lab Team
+
Facilitation
Engineering/
Data Science
Design

Digital
Transformation
/Innovation Teams
Key sponsor
+
Facilitation
Engineering/
Data Science
Design
Neo4j Field Engineer
• Facilitates graph-modeling exercises
• Expert in Neo4j/Architecture & Data Science
• Cypher-queries for prototype
UX-designer
• Facilitates storyboarding/wireframing
• Builds UI-tool for prototype
Labs Leader
• Head facilitator & Team Leader
• Facilitates the use case generation-segment
• Project manages prototyping

Examples of
Innovation
Lab
Oil & Gas

Software Companies
Heavy Industry
FMCG
Cruising Companies
Logistics
Financial Services
Media
Health Care
Energy
Telco
Industries Use Cases
Recommendation Engines
Smart Cities
Personalization
Fraud Detection
Data Lineage
Construction Planning
Regulatory Compliance
Media Advertising Systems
Supply Chain
Preventive Health Care Tools
Churn Prediction
Customer Service
Automation
Customer Journey Mapping
Retail Bill of Materials
Churn Prediction

The Neo4j Innovation
Lab Experience

Generating
Use Cases

CIO
BI Analysts
Chief Architect

Head of Digital Innovation
UX Designer
Lead Developer
Machine Learning/
Data Scientist

Data Modeling

Adam Cowley, Neo4j
Field Engineer
Data Modeling

Data Modeling
Eric Monk, Neo4j PS-
consultantData Scientist
Director of AI
Data Scientist
Innovation Lab
Leader

“If you build a polished prototype,
others will see flaws.

— Baba Shiv
Stanford Graduate School of Business
“If you build a polished prototype,
others will see flaws. If you build a
rough prototype, others will see
potential”

Building
Prototypes

Campaign details Recommendation Estimated performance Live dashboard
Brands Formats
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Campaign recommendation

Feedback
Received
“The productivity and output enabled by
how the days were structure and the
exercises within the sessions has been an
eye-opener.”
— Procter & Gamble
“Very impressed. Intense and fun! We
got a lot done in just a week. Great
experience and super eﬀective.”
— Santander Consumer Bank
“Unexpected and pretty incredible that
it’s possible to achieve such relevant and
applicable results in such a limited time
period.”
— Schibsted Media Group
“Involving. Knowledge building. Fun!
Extremely valuable and mind opening”
— Alfa Laval

Lastly…
…you should
engage in a
Innovation Lab-
work shop with us!
If you see
potential with
Graphs and
want to…
…accelerate use
case exploration and
validation through
prototyping…

alessandro.svensson@neo4j.com
Email
Linkedin
Alessandro Svensson, Neo4j

Thank you! #

Accelerating Innovation through Graph Thinking

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