This slide deck gives an overview of findings from ZDNet's Big Data Priorities 2013 research study on the present state and future direction of analytics and big data in North America.

1. January 24 2013, Webinar Panel Discussion

2. Featured Speakers
Hilary Mason David Boyle Ken Wincko
Chief Scientist SVP Insights Senior Marketing
bitly, inc EMI Music Group Director
Dun & Bradstreet
Carol Krol Angus Macaskill
Managing Editor, Industry Analyst
Custom Content CBS Interactive
CBS Interactive

3. 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

4. Project Scope, Timeline, Respondents
 The business imperatives of Analytics and Big Data
 Fieldwork in October and November 2012
 Respondent profile:
Education/Health Care/Government 15.8%
Business Services/Consulting 13.4%
IT and Communications 9.2%
15.9% <100
Banking/Financial Services/Insurance etc 7.0%
Manufacturing 6.7%
45.1% >100 Retail/Distribution/Wholesale 5.7%
Media/Entertainment/Design 4.5%
Engineering/Construction/R&D 3.9%
38.9% Not Transportation/Aerospace 2.7%
Disclosed
Other 15.1%
Not Disclosed 15.9%
N=596
0% 5% 10% 15% 20%
Percentage of organizations n=596

5. Organizations say the business potential
of Analytics/Big Data will grow rapidly
2012 23.8%
Time Period
2013 37.1%
2014 50.3%
0% 10% 20% 30% 40% 50% 60%
Percentage of organizations saying Analytics/Big Data has high potential, n=596
5

6. 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

7. Around one-half of businesses use
Analytics in everyday decision-making
ALL RESPONDENTS 34.7% 18.1% 22.5% 14.4% 5.0% 5.2%
>100 25.4% 15.9% 25.4% 21.6% 7.3% 4.3%
<100 40.5% 18.6% 21.9% 8.6% 4.1% 6.3%
Not Disclosed 41.1% 22.1% 16.8% 13.7% 2.1%4.2%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Percentage currently using/not using Analytics/Big Data daily, n=596
8

8. For most businesses, Analytics/Big Data is all about
outcomes in revenue, customers, productivity and markets
Not a Priority Low Priority Medium Priority Major Priority Top Priority
Revenue generation: e.g. recommendation engine, offer
triggers, growing customer value, cross-selling etc. 7.0% 8.9% 21.5% 37.8% 24.8%
Clients/Stakeholders: Create deeper understanding of clients
(or stakeholders if Government/Not for profit organization) e.g. 7.4% 8.5% 26.7% 27.8% 29.6%
customer analytics, customer churn analysis.
Productivity gains, cost savings 6.7% 12.6% 24.8% 29.3% 26.7%
Markets, marketing analysis: Create deeper understanding of
markets, campaign effectiveness analysis etc. 7.8% 13.3% 24.8% 28.5% 25.6%
Customer acquisition: Use enhanced understanding of
customers / prospects to acquire new business 9.6% 13.7% 23.7% 28.9% 24.1%
Financial management 9.3% 14.4% 28.1% 26.7% 21.5%
Product/Service: Create deeper understanding of product or
service, product or service development, product or service 9.3% 15.9% 29.6% 27.8% 17.4%
lifecycle, product servicing
Risk Assessment/modelling: financial market modelling and
simulations; assess risks and exposure of financial 13.0% 15.6% 31.5% 24.1% 15.9%
markets/assets; detect fraud patterns etc.
Logistics 15.9% 17.8% 31.1% 24.8% 10.4%
Build data products: create and sell data that has value to
other businesses 29.6% 18.9% 17.0% 21.9% 12.6%
Social Listening / sentiment analysis: e.g. track what social
media updates say about companies, brands, products 16.3% 28.9% 28.5% 16.3% 10.0%
0% 20% 40% 60% 80% 100%
Percentage using Analytics/Big Data, n=270
9

9. Analytics/Big Data ROI expectations are high
Within 1 year 22.7%
Within 1 to 2 years 38.6%
Within 2 to 3 years 25.8%
More than 3 years 12.9%
0% 10% 20% 30% 40%
Percentage of organizations disclosing, n=233
10

10. Almost all organizations have achieved some measurable
financial benefit, and 25% have achieved major financial benefit
Not at all 9.9%
To a minor extent 32.2%
To a medium extent 32.2%
To a major extent 19.3%
To a great extent 6.4%
0% 10% 20% 30% 40%
Percentage of organizations using Analytics/Big Data, n=233
11

11. Businesses use a variety of data sources, especially
in-house and online, for day-to-day decision-making
Operational Data e.g. from Finance, ERP, CRM and other
internal applications 77.4%
Internet transactions data e.g. from purchases, enquiries,
requests etc. 44.8%
Social Networking and Media e.g. tracking and analysing
social media updates, tweets, blog posts 34.4%
Networked Devices and Sensors – e.g. electronic devices
such as IT hardware, smart energy meters, temperature 28.9%
sensors, chips in products etc.
Internet Clickstream data e.g. analysing where visitors go
on your web site 27.4%
Data as a Service (DaaS) i.e.the aggregation,integration,
automation and dissemination of 3rd party information from 26.7%
suppliers such as StrikeIron, Experian,TheWebService,…
Mobile Devices, location data e.g. smartphones, tablets 23.7%
None of the above 6.3%
0% 20% 40% 60% 80%
%age of organizations disclosing, n=209
12

12. Deployment of Analytics and/or Big Data
platforms will gather pace in 2013
We have neither an analytics nor big data capability in 48.3%
place
27.7%
We have an analytics capability that sources data directly 23.0% End of 2012
from transactions/operational databases (i.e. no data
warehouse) 19.3%
End of 2013
We have an analytics capability that sources data from a 18.6%
data warehouse 19.8%
We have an analytics capability that sources data from a 5.4%
big data platform (e.g. Hadoop, or next generation
columnar data warehouse, or similar technologies) 11.9%
We have an analytics capability that sources data from a
data warehouse and a big data platform (e.g. Hadoop, or 4.7%
next generation columnar data warehouse, or similar 21.3%
technologies)
0% 10% 20% 30% 40% 50%
Percentage of organizations, n=596
13

13. Primary responsibility for budget, strategy
and plans for Analytics/Big Data
Chief Information Officer (CIO) 26.3%
CEO 22.6%
No-one has the responsibility – we don’t have a strategy/plan 13.7%
Chief Financial Officer (CFO) 13.7%
Business Intelligence (BI) Team or Team Leader 9.6%
Chief Operating Officer (COO) 6.7%
Data Science Team or Team Leader 2.6%
Chief Marketing Officer (CMO) 2.6%
Manufacturing / production Leader 2.2%
0% 5% 10% 15% 20% 25% 30%
Percentage of organizations using analytics and/or Big Data, n=270
14

14. The major obstacles to deriving maximum benefit from Analytics:
lack of an analytics culture, data skills and executive support
Lack of an analytics culture in the organization 20.0%
Lack of skills in the organization in the areas of analytics /
16.3%
data / data science
Other initiatives are given funding priority 12.6%
Lack of senior executive leadership and support 11.5%
Inability to prioritise funding for big data 8.9%
Inability to agree ownership of data across the organization 8.9%
Inability to demonstrate the return on investment 8.1%
None of the above 13.7%
0% 5% 10% 15% 20%
Percentage of organizations using analytics and/or Big Data, n=270
15

15. 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

16. Why have organizations not embraced Analytics/Big Data? They
don’t have much data, they just don’t see a return, lack of skills
We’re not in an industry sector that has a lot of data 34.0%
We can see a potential return from big data but it’s not a
29.8%
priority for us right now
We can see a potential return from big data but we don’t
have the in-house skills to make it work 22.4%
We’ve looked at Analytics/big data but don’t see a suitable
13.8%
return
0% 5% 10% 15% 20% 25% 30% 35%
Percentage of organizations not using analytics and/or Big Data, n=362
17

17. Q&A

18. 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

19. THANK YOU FOR JOINING US
January 24 2013, Webinar Panel Discussion