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How the World's Leading Independent Automotive Distributor is Reinventing Itself Through "Data" - Ram Thilak

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NUS-ISS

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!

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How the world’s leading
independent automotive
distributor is reinventing
itself through “DATA”
Ram Thilak
Group Head – Data Science & AI
Inchcape plc
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
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
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
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
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.
How the World's Leading Independent Automotive Distributor is Reinventing Itself Through "Data" - Ram Thilak
8
Venture Capital Investing style
Product Selection
Treating “Data” and “Algorithms”
as products
How the World's Leading Independent Automotive Distributor is Reinventing Itself Through "Data" - Ram Thilak
How the World's Leading Independent Automotive Distributor is Reinventing Itself Through "Data" - Ram Thilak
How the World's Leading Independent Automotive Distributor is Reinventing Itself Through "Data" - Ram Thilak
How the World's Leading Independent Automotive Distributor is Reinventing Itself Through "Data" - Ram Thilak
How the World's Leading Independent Automotive Distributor is Reinventing Itself Through "Data" - Ram Thilak
How the World's Leading Independent Automotive Distributor is Reinventing Itself Through "Data" - Ram Thilak
How the World's Leading Independent Automotive Distributor is Reinventing Itself Through "Data" - Ram Thilak
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
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.
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
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
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
%
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
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
We make our team of 200 work like a “Jazz Band”…
23
Use this QR code to connect with me on
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event survey.

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How the World's Leading Independent Automotive Distributor is Reinventing Itself Through "Data" - Ram Thilak

  • 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
  • 24. Use this QR code to connect with me on
  • 25. Speakers’ decks will be shared with attendees who completed the post event survey.