big data priorities: january 24, 2013 webinar

January 24 2013, Webinar Panel Discussion

Featured Speakers

Hilary Mason Chief Scientist bitly, inc

David Boyle SVP Insights EMI Music Group

Ken Wincko Senior Marketing Director Dun & Bradstreet

Carol Krol Managing Editor, Custom Content CBS Interactive

Angus Macaskill Industry Analyst CBS Interactive

Agenda

Overview of findings from ZDNet’s Big Data Priorities

2013 Research

Panel discussion of key findings

Panel response to questions from audience

Wrap-up

Project Scope, Timeline, Respondents

The business imperatives of Analytics and Big Data

Fieldwork in October and November 2012

Respondent profile:

45.1%

38.9%

15.9%

N=596

<100

>100

Not Disclosed

15.9%

15.1%

2.7%

3.9%

4.5%

5.7%

6.7%

7.0%

9.2%

13.4%

15.8%

0% 5% 10% 15% 20%

Not Disclosed

Other

Transportation/Aerospace

Engineering/Construction/R&D

Media/Entertainment/Design

Retail/Distribution/Wholesale

Manufacturing

Banking/Financial Services/Insurance etc

IT and Communications

Business Services/Consulting

Education/Health Care/Government

Percentage of organizations n=596

5

50.3%

37.1%

23.8%

0% 10% 20% 30% 40% 50% 60%

2014

2013

2012

Percentage of organizations saying Analytics/Big Data has high potential, n=596

Tim

e P

erio

d

Organizations say the business potential

of Analytics/Big Data will grow rapidly

Audience Poll

What is the potential for Data Analytics/Big Data to have a major

influence on your organization’s business performance this year?

Is it:

Low

Moderate

High

8

41.1%

40.5%

25.4%

34.7%

22.1%

18.6%

15.9%

18.1%

16.8%

21.9%

25.4%

22.5%

13.7%

8.6%

21.6%

14.4%

2.1%

4.1%

7.3%

5.0%

4.2%

6.3%

4.3%

5.2%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Not Disclosed

<100

>100

ALL RESPONDENTS

Percentage currently using/not using Analytics/Big Data daily, n=596

Around one-half of businesses use

Analytics in everyday decision-making

9

16.3%

29.6%

15.9%

13.0%

9.3%

9.3%

9.6%

7.8%

6.7%

7.4%

7.0%

28.9%

18.9%

17.8%

15.6%

15.9%

14.4%

13.7%

13.3%

12.6%

8.5%

8.9%

28.5%

17.0%

31.1%

31.5%

29.6%

28.1%

23.7%

24.8%

24.8%

26.7%

21.5%

16.3%

21.9%

24.8%

24.1%

27.8%

26.7%

28.9%

28.5%

29.3%

27.8%

37.8%

10.0%

12.6%

10.4%

15.9%

17.4%

21.5%

24.1%

25.6%

26.7%

29.6%

24.8%

0% 20% 40% 60% 80% 100%

Social Listening / sentiment analysis: e.g. track what social media updates say about companies, brands, products

Build data products: create and sell data that has value to other businesses

Logistics

Risk Assessment/modelling: financial market modelling and simulations; assess risks and exposure of financial

markets/assets; detect fraud patterns etc.

Product/Service: Create deeper understanding of product or service, product or service development, product or service

lifecycle, product servicing

Financial management

Customer acquisition: Use enhanced understanding of customers / prospects to acquire new business

Markets, marketing analysis: Create deeper understanding of markets, campaign effectiveness analysis etc.

Productivity gains, cost savings

Clients/Stakeholders: Create deeper understanding of clients (or stakeholders if Government/Not for profit organization) e.g.

customer analytics, customer churn analysis.

Revenue generation: e.g. recommendation engine, offer triggers, growing customer value, cross-selling etc.

Percentage using Analytics/Big Data, n=270

Not a Priority Low Priority Medium Priority Major Priority Top Priority

For most businesses, Analytics/Big Data is all about

outcomes in revenue, customers, productivity and markets

10

12.9%

25.8%

38.6%

22.7%

0% 10% 20% 30% 40%

More than 3 years

Within 2 to 3 years

Within 1 to 2 years

Within 1 year

Percentage of organizations disclosing, n=233

Analytics/Big Data ROI expectations are high

11

6.4%

19.3%

32.2%

32.2%

9.9%

0% 10% 20% 30% 40%

To a great extent

To a major extent

To a medium extent

To a minor extent

Not at all

Percentage of organizations using Analytics/Big Data, n=233

Almost all organizations have achieved some measurable

financial benefit, and 25% have achieved major financial benefit

12

Businesses use a variety of data sources, especially

in-house and online, for day-to-day decision-making

6.3%

23.7%

26.7%

27.4%

28.9%

34.4%

44.8%

77.4%

0% 20% 40% 60% 80%

None of the above

Mobile Devices, location data e.g. smartphones, tablets

Data as a Service (DaaS) i.e.the aggregation,integration, automation and dissemination of 3rd party information from suppliers such as StrikeIron, Experian,TheWebService, …

Internet Clickstream data e.g. analysing where visitors go on your web site

Networked Devices and Sensors – e.g. electronic devices such as IT hardware, smart energy meters, temperature

sensors, chips in products etc.

Social Networking and Media e.g. tracking and analysing social media updates, tweets, blog posts

Internet transactions data e.g. from purchases, enquiries, requests etc.

Operational Data e.g. from Finance, ERP, CRM and other internal applications

%age of organizations disclosing, n=209

13

21.3%

11.9%

19.8%

19.3%

27.7%

4.7%

5.4%

18.6%

23.0%

48.3%

0% 10% 20% 30% 40% 50%

We have an analytics capability that sources data from a data warehouse and a big data platform (e.g. Hadoop, or

next generation columnar data warehouse, or similar technologies)

We have an analytics capability that sources data from a big data platform (e.g. Hadoop, or next generation columnar data warehouse, or similar technologies)

We have an analytics capability that sources data from a data warehouse

We have an analytics capability that sources data directly from transactions/operational databases (i.e. no data

warehouse)

We have neither an analytics nor big data capability in place

Percentage of organizations, n=596

End of 2012

End of 2013

Deployment of Analytics and/or Big Data

platforms will gather pace in 2013

14

2.2%

2.6%

2.6%

6.7%

9.6%

13.7%

13.7%

22.6%

26.3%

0% 5% 10% 15% 20% 25% 30%

Manufacturing / production Leader

Chief Marketing Officer (CMO)

Data Science Team or Team Leader

Chief Operating Officer (COO)

Business Intelligence (BI) Team or Team Leader

Chief Financial Officer (CFO)

No-one has the responsibility – we don’t have a strategy/plan

CEO

Chief Information Officer (CIO)

Percentage of organizations using analytics and/or Big Data, n=270

Primary responsibility for budget, strategy

and plans for Analytics/Big Data

15

13.7%

8.1%

8.9%

8.9%

11.5%

12.6%

16.3%

20.0%

0% 5% 10% 15% 20%

None of the above

Inability to demonstrate the return on investment

Inability to agree ownership of data across the organization

Inability to prioritise funding for big data

Lack of senior executive leadership and support

Other initiatives are given funding priority

Lack of skills in the organization in the areas of analytics / data / data science

Lack of an analytics culture in the organization

Percentage of organizations using analytics and/or Big Data, n=270

The major obstacles to deriving maximum benefit from Analytics:

lack of an analytics culture, data skills and executive support

Audience Poll

Which of the following (if any) are the biggest obstacles to your

organization deriving maximum benefits from analytics

Lack of an analytics culture in the organization

Lack of senior executive leadership and support

Inability to agree ownership of data across the organization

Inability to prioritize funding for big data

Lack of skills in the organization in the areas of analytics / data /

data science

Inability to demonstrate the return on investment

17

13.8%

22.4%

29.8%

34.0%

0% 5% 10% 15% 20% 25% 30% 35%

We’ve looked at Analytics/big data but don’t see a suitable return

We can see a potential return from big data but we don’t have the in-house skills to make it work

We can see a potential return from big data but it’s not a priority for us right now

We’re not in an industry sector that has a lot of data

Percentage of organizations not using analytics and/or Big Data, n=362

Why have organizations not embraced Analytics/Big Data? They

don’t have much data, they just don’t see a return, lack of skills

Q&A

Wrap-up

Respondents see big potential in analytics/big data –over one-

half say it will have high impact on the business by 2014

The targeted business outcomes are improvements in revenue,

customers, productivity and markets

Deployment of advanced analytics/big data platforms is in its

infancy, but will grow rapidly in 2013

Lack of analytics culture, data skills, executive support, and

policy on data are barriers – businesses need to find solutions

Data is sourced form internal and external sources, and ue of

mobile data and DaaS is growing

January 24 2013, Webinar Panel Discussion

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