Analytics Maturity

& How to Get There

February 12th, 2016

About SnA

2

SnA team combines skillsets in

three-key-areas: direct marketing

strategy, applied statistics and

database techniques.

In the past seven years, SnA has

completed over 30 advanced

analytics engagements with high-

profile clients in the EMEA region.

SnA is a boutique businessanalytics consultancy with 15resources actively engaged inclient deliverables

SnA helps blue-chip clients inBanking, Insurance, Telco, Retailand Energy understand theirtransaction level history &conduct predictive analysis

SnA's has been a SAS partnersince foundation and SnA’s corecapabilities include:

• Analytic CRM Strategy

Development

• Predictive Modeling for CRM

• Campaign Design and Analysis

for CRM

• Customer Segmentation

• Customer Life Time Value

• Credit Scoring

• Insurance Rate Making

• Line Optimization

• Collection Optimization

Selected List of Projects

• Analytical CRM foundation set-up

with multiple customer

segmentation schemes and

predictive models for direct

marketing campaign optimization

• Credit risk analysis and scorecard

implementation based on business

lines for multiple clients in Turkey

• Rate making for insurance

companies in auto and health

lines. Producing Generalized

Linear Models for automated

pricing for multiple product lines.

• Social network analysis from CDR

data to identify communities,

influencers and followers to

implement profiling and viral

marketing activities

• Implementing automated pre-

approved line strategies while

optimizing risk and customer

response.

Speaker Bio: Ömer Nadirler, Principal @ SnA

3

2000 completed University in TR

2001 graduate school in the US

2002 completed Graduate School in the US focusing on quantitative methods

2003

multiple advanced analytics consulting roles in the US working with financial

services, telco, retail, e-commerce clients; predictive models and optimization

2004

2005

2006

2007 moved back to TR and started working at SnA

2008

multiple analytics consulting projects working with clients from TR and the CIS

region, deliverables in advanced analytics

2009

2010

2011

2012

2013

2014

2015

2016 managing a team of 15 advanced analytics professionals across clients

Happy Times for an Analytics Professional

4

Happy Times for an Analytics Professional

5

Management

Professionals

are Excited

When You are

the Product

Privacy

Concerns

Everybody

Wants In

Don’t Forget to

Mention the Gang

Have No Fear

Is Data the New Oil?

6

• Newly adopted technologies make it easier and cheaper to capture data from different resources.

• Generating insight from raw data requires implementation of analytical technologies with qualified experts.

• Even mature markets experience a shortage of analytical and managerial talentto improve data driven decision making.

* Association of National Advertisers – Michael Palmer: “Data is just like crude. It’s valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc., to create a valuable entity that drives profitable activity; so must data be broken down, analyzed for it to have value.”

* McKinsey and Co – Big Data, The Next Frontier: A shortage of the analytical and managerial talent necessary to make the most of big data is a significant and pressing challenge and one that companies and policy makers can begin to address in the near term. The United States alone faces a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts to analyze big data and make decisions based on their findings.

Data Driven Decision Making

7

• Increasing level of data driven decision making in organizations require

transformation in multiple domains.

Data Denial Data Indifferent Data Informed Data Driven

Organization

distrusts data

and avoids

using it

Data is

perceived “unnecessary”

given other

available

inputs

Data is used

selectively in

decision

making

Data is used

to shape and

inform all

decision

making

Data Driven Decision Making

8

• Increasing level of data driven decision making in organizations require

transformation in multiple domains.

Data Denial Data Indifferent Data Informed Data Driven

Organization

distrusts data and

avoids using it

Data is perceived “unnecessary”

given other

available inputs

Data is used

selectively in

decision making

Data is used to

shape and inform

all decision

making

People Gut Based DecisionsIsolated Analysts

Report & Describe

Analytical Skills

Describe & Predict

Analytical Masters

Predict & Optimize

Process No Processes Narrow Focus on Analytics Integrating Analytics Centralized Analytics

Technology No Integration Across Fragmented Data Management Higher Quality Data Emerging Technologies

What Does the Journey Look Like?

9

• Here is a list of indicators for data driven organizations

Limited Data

Collection and

Management

Ad-hoc

Analytics to

Guide Some

Actions

Analytics

Informs Business

Decision Making

Describe &

Predict

Data Insights Are

Critical for Daily

Decision Making

Predict &

Optimize

Analytics to

Justify Actions

Low Data

Expertise and

Insights Sharing

Report &

Describe

Analytics

Recommends

Actions

Analytics

Prescribe

Actions

Aspirational Experiential Transformational

Use of Analytics

Business Outcome

Data Denial Data Indifferent Data Informed Data Driven

Signs That You’re a Data Driven Organization

10

• Here is a list of indicators for data driven organizations

Measure Everything

Deploy Analytics

Tools Expertly

Analysis Yields to

Recommendations

Create Change

Based on Data

Benefits from what the technology has to offer

Each and every decision point is designed for testing and

measuring

Analytics output produces a recommendation for improvement

Apply recommendations and never stop testing for increments

Signs That You’re a Data Driven Organization

11

• Here is a list of indicators for data driven organizations

Open & Sharing

Strong Testing

Culture

Broad Data Literacy

Strong Data

Leadership

Encourage hypothesis generation and testing

No Silos - bring data together

Decision makers with skill-set to interpret data

A leader evangelizing data as an important asset

How to Get There….

12

• Evaluate your level of analytics maturity

– Tools, Processes, Culture, Expertise, Governance

• Prioritize subject matter areas to improve: selective investments

• Sometimes it’s more of a change management effort than anything

else

• Working with professionals is the “cheaper” way

How to Get There….

13

Yes, these are important:

Lots of Reports

Hadoop Clusters

How to Get There….

14

Yes, these are important:

Lots of Reports

Hadoop Clusters

<

But not at the expense of these:

Pros Know

What They

are Doing

Experimentation

Open &

Sharing

Culture

Thank You

16

This document contains confidential information and shall not be used, disclosed

or reproduced, in whole or in part, for any purpose, without the prior written

consent of SnA Consulting.

SnA Consulting – Contact Information

Buyukdere Caddesi Levent Loft No: 201/93 Sisli / Istanbul / TR

+90-212-318-9135 www.sna-consult.com

Contact Information