Chief Analytics Officer Fall USA 2017 - Jose Antonio Murillo
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Getting a Seat at the Table
José A. Murillo
October 2, 2017
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2
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4 McKinsey Global Institute (December 2016) . The age of analytics: Competing in a data-driven world
Which of the following best describes decision-making in your
organisation? Highly data-driven decision makers
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PwC's Global Data and Analytics Survey: Big Decisions (2016). Base: 2,106 senior executives.
18%
36%
25%
22%
Prescriptive
Predictive
Diagnostic
Descriptive
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Analytics in Search for a Seat at the Table
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How do you get the opportunity to
be heard?
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How do you make a difference in
your business?
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How do you get a seat at the table?
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Analytics at Banorte
"Translate information into profits"
Target
10X Cost
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Mandate
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Proof worthiness: A matter of survival in short term…
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… And in the long term build a
succesful Analytics team
Results
4.6X Target
Value created in
2016
$275 million
USD
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1st year:
1st year
10.6X Target 2nd year
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Getting a Seat at The
Table
Identify opportunity
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Business case
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Build consensus among stakeholders
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Team up with stakeholders to execute
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Rigorous assessment of results
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Share and celebrate results with team
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Share results with stakeholders
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Communicate results to C-Suite
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Analytics, Productivity and Value Creation:
A Case Study of Banorte's
Credit Card Experience
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Analytical Identification of Opportunities
Curtail cost of risk 1
Cross - sell 2
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46
68
100
-33%
-54%
Branch New cross-sell processMobile salesforce
Acquisition cost per purchase-active account by origination processIndex
Traditional acquisition processes
FIGURE 4
Cross–Sell Process Redesign Acquisition cost per purchase-active account by origination process Index
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Average rate of purchase-active cards per week since acquisitionPercentage of cards that become purchase-active
FIGURE 5
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
0 5 10 15 20
65
New cross-sellprocess
Traditionalacquisitionprocess
Mkt. avg. at 24 weeks
Weeks after acquisition
24
Cross–Sell Process Redesign Average rate pf purchase-active cards per week since acquisition Percentage of cards that become purchase-active
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$49$29$37
$18$16
$0
$160$154
$113$136
$118
$46$31
0
50
100
150
200
$7 22
110
Low Credit Limit
High Credit Limit
Avg.
Avg.
Incremental monthly spend of cards acquired through new process by size of credit limit$USD
FIGURE 6
Incremental monthly balance of cards acquired through new process by size of credit limit$USD
$104$113$67
$23$11
$450$383
$185$138$35
$25
0
100
200
300
400
500
0 1 2 3 4 5 6
$12
$208
$1
Months after acquisition
Cross–Sell Process Redesign
$49$29$37
$18$16
$0
$160$154
$113$136
$118
$46$31
0
50
100
150
200
$7 22
110
Low Credit Limit
High Credit Limit
Avg.
Avg.
Incremental monthly spend of cards acquired through new process by size of credit limit$USD
FIGURE 6
Incremental monthly balance of cards acquired through new process by size of credit limit$USD
$104$113$67
$23$11
$450$383
$185$138$35
$25
0
100
200
300
400
500
0 1 2 3 4 5 6
$12
$208
$1
Months after acquisition
$49$29$37
$18$16
$0
$160$154
$113$136
$118
$46$31
0
50
100
150
200
$7 22
110
Low Credit Limit
High Credit Limit
Avg.
Avg.
Incremental monthly spend of cards acquired through new process by size of credit limit$USD
FIGURE 6
Incremental monthly balance of cards acquired through new process by size of credit limit$USD
$104$113$67
$23$11
$450$383
$185$138$35
$25
0
100
200
300
400
500
0 1 2 3 4 5 6
$12
$208
$1
Months after acquisition
Incremental monthly spend of cards acquired through new process by size of credit limit $USD
Incremental monthly balance of cards acquired through new process by size of credit limit $USD
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Share results with the industry
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