Making connections matter: 2 use cases on graphs & analytics solutions

N O V E M B E R 2 0 2 1
Making connections matter
Two use cases on graphs & analyticssolutions

2 | Copyright © 2021 Deloitte Development LLC. All rights reserved.
Table of Contents
A P O I N T O F V I E W O N G R A P H T E C H N O L O G I E S
Our Vision
Introducing Graph technology
The next step in data management
Data management use case: Bill of Material and Data
quality control
Recommendation systems and smart assistants
Recommendation system use case: Online Shopping
Assistant

Graphs are everywhere
In a connected world, data relationsand context are everything.
O U R V I S I O N

What are Graph databases and Graph analytics
The knowledge base is enriched with connections where each entity contributesto giving context to the others
I N T R O D U C I N G G R A P H T E C H N O L O G Y
Connections has primary citizen
Each core participates to
definition of other connected
cores
Densely connected data analytics
Graph database

Technology benefit
Performance Problem solving Real time use Flexibility Multi dimension Integration
Graph technology is most powerful when trying to uncover, leverage or add relationships withindata. Its flexibilityalso makes it a powerful tool for
regularly changing data

Graph database capabilities: what changes?
Graph databases can empower data managementand complex problem solving, ease understanding and communicationand maintain traditional
capabilities
Visual interactions
Querying
Data management and reasoning
Data analytics
2
3
1
4
Human-like structure to
supports visual interaction
and
data and exploration
while adding depth to
data managementand
analytics
through
connection and context
enricheddata
for
smarter and faster
solutions

Benefit demonstrated
The value of graph technology is demonstrated in
numerous applications
Recommenders Data management- cleansing
Data management - 360 view for
engineering
Supply chain analysis and
optimization
Data management - KYC Graph|Report to design risk and control
frameworks
From enhanced framework visualization,
to recommenders, optimization and
advanced data management, leveraging
connection can make a difference in
taking the next step for data-driven
decisions

Data
management
with Graphs

Data management with Graphs
D A T A M A N A G E M E N T
Take the next step in data
management…
To leverage context and visual
insights
…With semantic relation
management

Data management with Graphs – When and Where
D A T A M A N A G E M E N T
360 view of 1
2
Data Cleansing
3
Analytical Master data management

Solution 1: Bill of Material analysis
B I L L O F M A T E R I A L A N A L Y S I S
Analyzing BoM data for rule violation and data inconsistency
• Merging multiple data sources
• Hierarchical data and share data points (commonality)
• Embedded business rules
• Analyze complex structures in an acceptable time
• Improve visualization and accelerate communication and decision-making
• Automate detection of inconsistencies
Key topics
The Ambition

Technology stack
Graph database
ETL tool
Relational DB (staging)
System 1 System N
Analysis
Visualization
tool
Task
management
Tool
Data source
Loading pipeline
Analytical
management
stack
We designed a modular pipeline
to deliver an end-to-end solution
for data analytics based on
graphs and managing data
management actions
System …
Data flow

An introduction to Bill of Material
Bill of Process
Simplified view of a Bill of Material: list of all components, tools, packaging, etc. to build, maintain or ship a machine

Modelling Bill of Materials and Business Rules as a Graph

Demo
• BoM visualization in the Graph
• Analysis of un-attached modules in product structure
• Serial Number Profile Inconsistencies
Demo
Lego Porsche Targa
Lego Porsche Turbo

Demo
?
Demo

Case: Serial number profile inconsistencies
C003
A000
B001
Clean and Stay Clean
• Identification code
• Defines how to assign serial numbers to items
• Can be assigned per material or per plant-material
• Hierarchical regulation of serialization
• Rule violation -> loss of information
• Ensure that the rules are respected
• Detected violations
• Prioritize cleansing
Serial Number Profiles (SNP)
Rules

Demo
C003
C003
A000
B001
C003
single level
inconsistency
B001
multi level
inconsistency
multi level
inconsistency
Case 1: identify issue constellations
Case 2: identify all loss under
a known problematic part
Case 3: identify any loss under
part independently of the
level
Demo

Conclusion on use case
• Fast expend and analysis on 100k+ part structures with results under 30min
• Increased communication with the interactive One-glance view
• Prioritization of issues based on contextualized effort/gain estimation
Getting insights in minutes instead of days for multilevel BoMs
The Impact

Recommendation
systems

Recommendation systems and Smart assistants
R E C O M M E N D A T I O N S Y S T E M S
From Recommendation …
And smart assistants
…to transparent recommendations

Solution 2: Online Shopping Assistant
S H O P P I N G A S S I S T A N T
• Real time recommendations
• Conversational AI
• Embedded expert knowledge
• Provide more relevant recommendation using embedded expert knowledge
• Make interaction with recommender more engaging
Key topics
The Ambition

Technology stack
We designed a modular and fully
customizable pipeline.
The solution is scalable and provides real-
time recommendations with possibilities to
store customer’s feedback to improve
algorithm
ETL tool
Data (relational database / other)
Graph database
Assistant algorithms
Chatbot interface
Front-end connected via API
Data flow
Loading pipeline
Assistant stack
Interaction layer

Demo
• Interface visualization
• Chatbot interaction
• Recommendation based on expert knowledge of the product
Demo

Conclusion on use case
The Impact
• Real time recommendation through conversational AI
• Prioritization of choice based on customers’ needs
• Store and leverage customers’ journey to improve solution
Getting recommendations that fits your purpose

Conclusion
M A K I N G C O N N E C T I O N S M A T T E R
• Develop modular solutions
• Leverage knowledge and data in relation to context
• Improve insights, visualization and communication
Key takeaway
• Data management
• Recommenders
• Optimization
• Visualization
Our Focus

Meet our team
We are a network of specialists around
the globe working on Graph solutions.
Do you have questions about this
presentation? Want to know more about
Graph solutions? Don’t hesitate to reach
out!
C R E D E N T I A L S
Simone Bom
Consultant
Stefan van Duin
Partner
SvanDuin@deloitte.nl
Marion Robin
Specialist Lead
mrobin@deloitte.nl
• Large team of AI experts
• Reusable trainings and analysis
pipelines
• Consistent and cost-effective labeling
resources
• A proven approach to develop end-to-
end solutions where Graph technology
is integrated into existing systems,
operations and processes
• A team of professionals experienced in
large scale technological and
organizational implementations
• Technology competences and
partnerships
• A team of Graph experts that
develop enterprise-wide solutions
• Flexibility to implement solutions in
an existing environment
• Extensive expertise in implementing
best practices
Deloitte differentiators & accelerators

This publication contains general information only, and none of the member
firms of Deloitte Touche Tohmatsu Limited, its member firms, or their related
entities (collective, the “Deloitte Network”) is, by means of this publication,
rendering professional advice or services. Before making any decision or taking
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As used in this document, “Deloitte” means Deloitte Consulting LLP, a subsidiary
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of the legal structure of Deloitte USA LLP, Deloitte LLP and their respective
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the rules and regulations of public accounting.
Copyright © 2021 Deloitte Development LLC.
All rights reserved. Member of Deloitte Touche Tohmatsu Limited
Thank you.

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