Creating $100 million from Big Data Analytics in Banking

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How to make $100 million with Big Data
How we achieved a remarkable return for our
investment in total enterprise engagement in
the Big Data paradigm. A case study in true
end-to-end Big Data and customer-centricity.
<Sanitized version for Slideshare>
Guy Pearce
Managing Partner
REData Performance Consulting
Toronto, Canada
info@redata.ca
@pearcegf
@data_roi

@Teradata_Apps
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AGENDA

3 3/23/2014 Teradata Confidential
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0
10
20
30
40
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60
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100
May Jun Jul Aug Sep Oct Nov
$million
Utilization
Payments
Xactions
Credit
A remarkable outcome, but probably not nearly as
remarkable as the journey!
The results above are but the last chapter in a rich people story,
a story about the Magic of Engagement! So, let me begin…

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Margins under
pressure 
Increasing
Competition
Market share
under pressure
MARKET RESEARCH
FINDINGS*
• 3rd for “have competent and
knowledgeable staff”
• 3rd for “understand me”
> The findings included that not
understanding the customer
was a primary reason for
customer attrition
• 3rd for “make an effort to
understand me”
These findings were unacceptable. Something needed to be done!
The best solutions solve a problem. Burning platforms
make compelling cases for change!
*Ranking out of the major banks
STRATEGIC
CHALLENGES
Ext

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The problem statement concerned the customer. The
right “solution” would therefore have to solve these
Customer
Centricity
Channel
Innovation
Pricing
InnovationProduct
Innovation
The problem statement showed failing customer engagement. A
data-driven customer-centricity initiative was born
STRATEGIC
ALTERNATIVES

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Analytics were customer-centric. Quality and risk
were managed implicitly, the latter not ideal
Longitudinal
Behavioural
Analytics, by
customer
Risk-Return
Portfolio
Modelling, by
customer
Contribution
Profiling, by
customer
“Next Best”
Predictive
Analytics, by
customer
We integrated diverse analytics to best understand the customer,
and then focused everyone’s efforts on how best to serve them
The latter helped
optimize the sales
force geographically,
by sales potential
*
Geospatial
rendition of
“next best”,
aggregated by
municipality

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Tying it together, we proposed an integrated strategy
for data-driven customer-centricity as a solution
Nearly half of big companies’ data initiatives fail because of poor
integration between operating model and business model KPMG 2014
Strategy, Governance and Stakeholders
Marketing
Finance
Group IT
Measurement
Business Model
Product
Management
Channel
Management
Segment
Management
Operating Model
HR Operations
Big Data analytics
and insights
Objectives

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• MIS
• CRM
• Strategy
• Technology
• Environment
• Data Operations
• Data Integration
• Predictive Analytics
• Descriptive Analytics
• Data Sourcing (int/ext)
There were big lessons in building an action-oriented
big data core team
The degree of strategically accurate innovation and initiative that
drove the team to peak performance is a case study on its own

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• Steering Committee
> Channel Operations (action)
– Provincial and > 1000 branches
across the country
> Credit
> Product
> Strategy
> Marketing
> Segments
> Finance (recording)
> Change Management
> Human resources (training)
> Group IT (group CRM rollout)
Lessons learned were used to engage the
enterprise, an imperative for any enterprise-scale
initiative
Change Management 101: What’s the burning platform? Does it
impact me? What’s in it for me? How do I look good in this?

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Ma‟am, may I suggest…
(Aside
> W = what products you‟ve got
> X = what products a cohort of
customers of a similar profile to
you have
> Y = an estimate of what
products you‟ve got at our
competitors
> Z = an estimate of what
products you may need to fulfil
your aspirations)
(Structured conversation about
unique (diff(X-W) union Y union
Z))
Resulted in a 1:2 strike rate
Renewed, relevant, insightful one-to-one customer
engagement

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Insightful branch and suite staffing strategy, based
on potential, aggregated per customer per centre
Aggregated customer
insights were used as a
guide to set individual sales
targets, to assist with
determining staffing
levels, which in turn had
implications for training and
branch budgets
A case study in holistic strategy

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On adoption: Original slide to the board. Poor choice
of words, and over-simplified, but it worked 
The best adoption strategy is for people to want what you’ve got!

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Value
Customers
Front Line
Staff
CRM
Big Data
Analytics
B
A
To create value, Big Data „reached‟ the customer by
means of CRM and the front line staff
B = Stakeholders and Team
A = Strategy Alignment. Purpose
For simplicity, the diagram does not show the feedback loops between the different elements

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• Adjust the annual market research survey to facilitate
measuring how the engagement was impacting market share
• Make governance and risk an explicit track
Two things we should have done, but didn‟t think to
do in the heat of the moment

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Volume
Terabyte
Scale
Variety
One internal
data source
Eight
external
data sources
Velocity
Growing at
up to 1000
rows per
second
Processing
A Teradata
appliance
dramatically
improved
performance
and
reliability
But was it really Big Data?
Yes, by Gartner’s definition. We were unable to achieve real time
and mobile deployment … maybe in our next engagement!

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Big Data is BIG. Complications aside, Big
Data is less effective if it is not
positioned at the enterprise level:
• The board approves corporate strategy
• The CEO sponsors Big Data as a key
component of strategy enablement
• The CIO‟s team builds it
• The CMO‟s team creates excitement
• The CHRO‟s team upskills staff
• The COO‟s team makes it happen
• The CFO‟s team audits and measures
Sharing some lessons
If the objective of your Big Data project is to create value,
then people engagement is a critical success factor

The $100 million question: Is
Big Data something you should
be doing?
Guy Pearce
Managing Partner
REData Performance Consulting
Toronto, Canada
www.redata.ca
info@redata.ca
@pearcegf
@data_roi

Creating $100 million from Big Data Analytics in Banking

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