In this captivating session, we'll unveil the profound impact of AI, poised to revolutionise the business landscape. Prepare to shift your perspective, as we transition from the lens of a data scientist to the visionary mindset of a product manager. We're about to demystify the captivating world of Generative AI, dispelling myths and illuminating its remarkable potential. We will also delve into the pioneering applications that Inchcape is leading, pushing the boundaries of what's achievable. Join us for an exhilarating journey into the future of AI, where professionalism meets unparalleled excitement, and innovation takes center stage!

1. How the world’s leading
independent automotive
distributor is reinventing
itself through “DATA”
Ram Thilak
Group Head – Data Science & AI
Inchcape plc

2. Introduction
1
Ram Thilak
Formative
years:
Started as Apps Developer for
Investment Bank
Masters in Enterprise
Business Analytics in NUS
ISS
Quantitative Finance Analyst
for NUS Investment Fund
Smart
Manufacturing –
R&D and
Singapore Ops:
Started as Intern and
promoted to Senior Data
Scientist in 3 years at HP
Singapore working across
Printer Ops, Supply Ops,
Industry 4.0, Customer
Analytics, Finance and
Sales
Regional Data –
Centre of
Competence :
First Data Science hire for
the region and build over
10 data science use-cases
to scale to the business
Setup MLOps for the
region, lead migration to
Cloud and drove strategic
initiatives to drive analytics
adoption
Chief Data
Scientist & Group
Head of Data
Science & AI:
Leading everything
data science & AI
for Inchcape across
the globe with a
team of 50 data
scientists across
Philippines,
Colombia and Chile

3. Inchcape at a glance…..
Distribution Excellence Vehicle Lifecycle Services
Our
Enablers
Responsible Business
Our Growth
Drivers
Digital, Data &
Analytics
Culture and
Capabilities
Efficient Scale
Operations
Accelerate: Inchcape’s growth strategy

4. Our approach is driven by the customer need
4
▪ Consumers spend
considerable time
online researching a vehicle
before entering the dealership
▪ Consumers expect an
omni-channel experience; one
that seamlessly integrates both
physical and digital
▪ Number of visits to a dealership
have reduced; however, providing
a rich omni-channel
and personalised experience
remains crucial
Source: BCG
4.5 to 6 hours
spent online researching
price and product
specifics prepurchase
75% to 85%
of customers make the
purchase at a dealership
having chosen a car
based on online sources
40% to 50%
customers welcoming
digital experiences
at dealerships
>1 visit
on average
made to dealership
prepurchase

5. A global digital infrastructure, driving smarter decisions
Omni-channel Predictive analytics and
business intelligence
Digital eXperience
Platform
Data
Analytics Platform
5
Inchcape Digital Architecture: a single, common global technology stack
Digital Delivery Centres: our internal digital delivery capability
Our global tech capability is powered by…..
Providing consumers with a fully
functional digital showroom
Built on a platform with the ability
to scale, quickly, to new markets
Enables the capture of significant
customer and vehicle data
Central capability to drive better
local and global decision
Using predictive analytics to
facilitate business intelligence
Globally integrated data repository,
addressing the entire value chain

6. Scaling AI Doing AI
6
“Doing Analytics is largely a problem that a Data Scientist can solve
whereas Scaling Analytics needs more than a team of Data Scientists”
1. How “Digital” is your business and how
much of your data collection process is
automated?
2. Involve Data Scientist from Day 0
3. Do you have right operating model based
on 3Ps (People, Process and Purpose)
Ref: https://towardsdatascience.com/doing-analytics-vs-scaling-analytics-b20795984ce2#:~:text=Doing%20Analytics%20is%20largely%20a,associated%20with%20in%20the%20past.

8. 8
Venture Capital Investing style
Product Selection
Treating “Data” and “Algorithms”
as products

16. Building AI Products aligned to Inchcape’s Value Chain
16
Real Time
Lead Scoring
Parts Pricing
Optimisation
Digital Spend
Attribution
Aged Stock
Prediction
Trade-in Pricing
Prediction
Aftersales Churn
Prediction
Guaranteed Future
Value (GFV)
Prediction
New Car
Demand
Forecasting

17. Real-time Lead Scoring is improving our lead-to-sale
conversion bringing high quality leads to our front-line
Inchcape 17
New approach (powered by DAP) Live in 30 Markets.
Available to all businesses on Salesforce.
Key differences
• Data-driven machine learning model
drives best path to purchase for
customer.
• Real-time tracking of lead volume and
temperature.
• Lead Insights integrated into Salesforce
Lead Management system on front-line.
Impact
• Reengineering of lead nurture journey
vs traditional approach.
• 40% efficiency improvement on
front-line.
• Better handling of hot leads on front line
= higher conversion.
• Better handling of warm leads = higher
overall conversion.
Rule-based lead-classification based on
website forms
e.g. Join
mailing
list
e.g. Book
test drive
Historic approach
Cold
lead
form Only leads
classified
as ‘Hot’sent
to sales team
Website
forms only
Hot
lead
form
Real-time machine Learning lead-scoring
model
Real-time
Machine Learning
scoring model
Ownership
status
Walk-in
activity
Online
behaviour
Website
actions
e.g. Download
brochure
Warm
lead
form
E-mail nurture
campaign
e-mail
nurture
campaign
Contact
centre
campaign
Sales
team
Front-line
Sales team
Potential
Lead
Potential
Lead
Marketing
interactions
Half of “Hot” Leads mis-classified.
Sales team frustrated with low-quality digital leads.

18. Future
Global roll out; currently
live in 20 markets
Deploy to third-party network;
drive higher Parts penetration
Higher aftersales retention rates
(beyond years 1-3); meaningful
improvement in customer retention with
win back rates at >20% in some markets
18
Aftersales customer
Distance
to service
center
Days left
for warranty
expiry
Service history
(costs, frequency,
delays) etc.
# repairs /
# parts
replaced
Aftersales Churn Prediction Algorithm
% probability to churn in
next x days + ‘reason
codes’
For lower
probability
customers:
targeted
Salesforce
journeys
For top
churners:
Contact
Center
based
campaigns
Aftersales churn prediction is improving service retention
Before
Limited visibility of customers most
at risk of leaving service network
Now
Machine learning model
identifies customers ‘at risk’
‘At risk’ customers proactively
contacted by Contact Centre
to drive higher retention

19. Data analytics is supporting Inchcape’s core goals…
19
More
Customers
Improved
Efficiencies
Higher
Growth
+ +
+26%
service
bookings
+30%
time spent on
genuine hot-leads
+10%
Parts revenue
Aftersales
churn-prediction
algorithm
Lead scoring
algorithm
Parts S&OP
predictive analytics
Initial results from test-phase and pilots

20. Digital and data tightly coupled amplifies the value..
Vehicle Lifecycle Value makes the argument stronger for Digital & Data
20
Note: Analysis shows the split of profit attainable over an average vehicle’s life, and assumes four different owners during that period
The analysis captures the vehicle sales, finance & insurance commission and the aftersales services (including independent aftermarket)
1st sale
%
2nd sale
%
3rd sale
%
New Vehicle Import
0-4 years
4+ years
Demand forecasting/
supply management
Digital marketing
Omni-channel fulfilment
Aftersales retention
Vehicle trade-in pricing
New / Used vehicle pricing
Parts pricing
Finance & Insurance Aftermarket Trade-in
%

21. Data has supercharged Inchcape as a leader..
Results of an independent third-party report
21
▪ Inchcape’s
global scale and internal
development capability is
a key point of differentiation
▪ Only a few (larger) distributors
are well-progressed with
digitalisation
▪ The incumbents appear
to be reticent to make investment
in technological advancement
Leader
Challenger
Basic
Challenger
Basic Leader
Digitalisation
Analytics
Identifies position of
competing larger scale
distributors

22. 22
Data
Engineering
Data Science & AI Pillar Business Intelligence Pillar
Machine Learning Operations Data Quality & Governance
Full Stack Development Pillar
Analytics Translation/
Consulting Pillar
Holds core expertise in
solving complex business
problems through
algorithms
Make data
accessible, reliable
and structured with
good quality
Getting solutions
to production by
integrating into
source systems
Consultants who
handle product
management & biz
communication

23. We make our team of 200 work like a “Jazz Band”…
23

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