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BIG TRANSFORMATION

Introduction

DE TRANSITIE VAN AEGON NAAR EEN DATA GEDREVEN ORGANISATIE

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Agenda

Introduction

Anchoring analytics in the organization

Building the analytical community

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Introduction

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Hiek van der Scheer• Head of Data & Analytics in

Center of Excellence for Digital• Passion for fact based marketing• PhD in Econometrics, University

of Groningen• Worked as leader in McKinsey’s

Advanced Analytics & Big Data practice

• Prior to that, managing the Marketing Intelligent practice at VODW

• Focused on industries with large customer databases: Insurance, Banking, Telco and Utilities

4Aegon at a glance

Aegon at a glance

€ 1.8 billion2015 Underlying earnings before tax

61% Amer-icas

29% Eu-rope

1% Asia9% AAM

Life insurance, pensions & asset management

30 millioncustomers2015

Total sales of €10.4 billion1)

2015

Over 29,000 employeesJune 30, 2016

Revenue-generating investments € 717 billionJune 30, 2016

€ 43 billion paid in claims & benefits 2015

1) Sales represents new life sales + accident & health premiums + general insurance premiums + 1/10 of gross deposits

5International presence

In more than 20 countriesA strong international presence

Aegon businesses

Joint ventures

Aegon Direct & Affinity Marketing Services

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Agenda

Introduction

Anchoring analytics in the organization

Building the analytical community

7Role of data science

Crucial in every step of our value chainData science

Product development Marketing Sales/

distributionUnderwriting/ pricing

Customer contact

Claims management

Tailor products to individual

customer needs

Personalize messages

across channels

Differentiate approach towards brokers

Optimize service process

Price at individual

level

Predict fraud using

advanced analytics

8How does Aegon uses (Big) data?

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Culture & mindset

Data, IT, and analytic

approaches

2 3

Tools and integration into

business processes

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Skills & enablingorganization

Clear vision & roadmap

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Anchoring data scienceIt takes more than ‘Data’ and ‘Science’ to anchor data science

10Anchoring data scienceWe have made progress in all 5 areas but still have journey in front of us

▪ Global analytical academy with great impact

▪ Training modules for general managers to get more familiar with the possibilities of data science

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Skills & enablingorganization

▪ Strong commitment from management

▪ Ongoing process to adopted in decision-making

Culture & mindset

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▪ More non-technical, user-friendly tools available

▪ Analytical insights are leading to new KPIs that are being steered on

Tools and integration into

business processes

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▪ Access to unique sources of data still somewhat ad-hoc

▪ Great examples of excellence in advanced analyses (predictive) to drive business insights

Data, IT, and analytic

approaches

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▪ Role of Data & Analytics clearly articulated in the 2020 strategy

▪ IT reference architecture in place to support this

Clear vision & roadmap

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Agenda

Introduction

Anchoring analytics in the organization

Building the analytical community

12Building analytical communityWe are building a strong analytical community

Analytical community: Customer Intelligence, Actuaries, Risk, …

Global Analytical Committee- Strategy- Address

overarching topics

Center of Excellence- Expert support- Standards- Joint projects- Best practice

sharing

Analytical Academy- International

program- Across disciplines- Training and

assignments

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13Global analytical committee

Vision for Data & Analytics and align with the business Strategy Create program to involve all levels in the organization to be become

more data driven Leverage Fintech companies

Create a data driven mindset and culture

Standardization (tooling, models, KPIs, etc.) Infrastructure Data management Provide overview of new developments around data & analytics

(tooling, approaches)

Get the enablers for a data driven organization are in place

Create and maintain overview of use cases and prioritize per CU Define and develop best practices for important use cases Initiate global projects

Drive impact programs

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Provide support in the form of subject matter experts and project teams for analytics projects in the countries

1.

Center of Excellence to accelerate the data & analytics transformation

Stimulate & facilitate multi-country collaboration on analytical initiatives, like tools and best practices

Help the CUs with shared learning and skill development in the analytical domains

2. 3. 4.

Help the CUs set strategic direction and goals for data & analytics transformation

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15Broad program focusing on all aspects of data science

Ana

lysi

s &

Insi

ghts

Proc

ess

& A

pplic

atio

n

• Knowledge of (big) data technology

• Dealing with complex and large data sets

• Coding skills analytical tooling for data preparation, analysis and visualization

• Problem solving and opportunity identification

• Impactful, structured communication and data-driven story telling

• Influencing skills and change leadership

• Building expertise in math and statistics

• Data discovery/data mining through different analyses

• Predictive modeling & machine learning

• Reasoning from value creation backwards, instead of analysis-forward

• Understanding of big data strategy & transformations

• Understanding of analytics applications in the value chain

The 4 Data Science domains

Data and Technology Skills

Impact and advisory skills

Analytical methods and techniques

Business domain expertise

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THANK YOU