We studied impact of the Big Data phenomenon on SMBs. We conducted interviews among 30 SMBs to check: - Big Data understanding by SMBs - Adoption level of Big Data services - Value creation and go-to-market channels - Pain points in adopting Big Data

1. VALUE CREATION FOR SMBs
WITH BIG DATA
by: Andrey Sadovykh, Paul-Emile Poisson, Aleksei Papin

2. Summary
1. Big Data Phenomenon
• Understanding sources and trends of the phenomenon
• Overview of the Big Data market and SMB sector
2. Big Data Service Providers
• Current services in the market for SMB (bird’s eye view)
3. SMBs Survey
• SMB Segments
• Understanding Big Data
• Value Creation and Go-To-Market
• SMB Pain Points for Big Data
• SMB Trends
4. Recommendations and Lessons Learnt
© Sadovykh, Poisson, Papin, 2014
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3. PART #1: BIG DATA
PHENOMENON
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4. Big Data = Volume + Variety + Velocity
Big data
is
commonly
characterized
by three
vectors:
Volume = sheer amount of data
Variety = polystructured nature = text, audio and video
Velocity = rate at which it is generated and analyzed
Source : IDC & EMC
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5. Data grows exponentially
By 2020, the digital
universe will amount
to:
over 5,200GB per
person on the planet
In December 2012 the size of the digital universe (that is, all the digital
data created, replicated and consumed in that year) was estimated to be
2 837 Exabyte (EB) - Forecasted to grow to 40,000EB by 2020
One Exabyte = 1 000 petabytes (PB)
One Exabyte = 1 000 000 terabytes (TB)
One Exabyte = 1 000 000 000 gigabytes (GB)
Source : IDC & EMC
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6. Only ½ % of Data is analyzed
Not all of data
generated will be
actually useful
In 2012, 2 837EB generated - just ½% actually analyzed.
That still amounts to 14EB (or 14.185 million terabytes)
Source : IDC & EMC
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7. Practically all that we do creates data
1.
2.
3.
4.
5.
Number of @-mails sent every second : 2,9 million
Video uploaded to YouTube every minute: 25 hours
Data processed by Google every day: 24 petabytes
Tweets per day: 50 million
Products ordered on Amazon per second: 73 items
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8. How big is the market?
The chances are, though, that big data will take its place in the mainstream
of IT activities.
Big Data Pure Players Revenues
25
$(Billions)
20
15
10
5
0
2010
2011
2012
2013
2014
2015
2016
In March 2012 it was forecasted that big data will become a $17
billion market by 2015 (since updated to $23.8bn by 2016 )
Source : IDC & EMC
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9. SMBs generate almost 60% of added value
Small business,
but big revenues
• SMBs are 99,8% of enterprises in Europe
• 58,6% of revenues is generated by SMBs
• Easier to penetrate, low entry barriers, a lot of working domains
Source : EuroStat
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10. SMBs can leverage Big Data
1.
Big Data phenomenon is driven by
accelerated growth of the unstructured
data.
2.
Traditional analytics means cannot cope
with such volumes, variety and velocity of
data.
3.
Proliferation of Cloud computing and
Software-as-a-Service made it possible for
appearance of affordable data analytics
tools for SMBs.
© Sadovykh, Poisson, Papin, 2014
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11. PART #2: BIG DATA
SERVICE PROVIDERS
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12. Data, Platforms, Analytics, Applications
Platforms
Visualization / Analytics
Marketing Analytics
Ads Targeting
Fraud Detection / Costs
Data Providers
© Sadovykh, Poisson, Papin, 2014

13. Findings
Marketing analytics is a mature industry
with many players addressing SMB
sector
Business analytics: companies can
build their own data analytics and
reporting on the web from ready to use
building blocks.
Managed services for business specific
statistical models start to appear with
the first results in fraud detection or
climate fine forecast.
© Sadovykh, Poisson, Papin, 2014
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14. PART #3: SMB SURVEY
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15. Big Data phenomenon
understanding
32 SMBs
participated in our
survey about:
Value creation and
Go-To-Market
SMBs’ pain points
Trends
15

16. We interviewed SMBs
from different
sectors.
Most interviewed
SMBs are micro
companies and
IT related.
SMB Revenues
4%
<200 K€
17%
48%
10%
14%
7%
200 K€ to 500 K€
500 K€ to 1 M€
SMB Sectors
0
2
4
6
8
10
IT services
Medical services
Media and
advertisement
E-commerce
Finance
Computer Hardware and
Software Design
Games
Software editor
International phone calls
Mathematical modelling
Real estate
1 M€ to 3 M€
3 M€ to 10 M€
> 10 M€
Packaging
Import/Export services
© Sadovykh, Poisson, Papin, 2014
Non-IT SMBs
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17. 56%
44%
Most SMBs associate
Big Data value
with Web Services for
Data Analytics
33%
22%
Web Service for
Data Analytics
Data Processing
Tools for Developers
Not agree
© Sadovykh, Poisson, Papin, 2014
Agree
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18. 78%
74%
Statistical Models
and Data Integration
bring the most value
to SMBs
56%
19%
19%
7%
Data
Statistical
Visualization Models
Not agree
© Sadovykh, Poisson, Papin, 2014
Data
Integration
Agree
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19. Not all SMBs
managed to
apply Big Data
38% do not use Data
Analytics
© Sadovykh, Poisson, Papin, 2014
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20. Sales increase
preoccupation
prevails
67%
56%
22%
Sales
increase
Cost
Risk
reduction reduction
© Sadovykh, Poisson, Papin, 2014
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21. SMBs struggled to
provide
quantifiable ROI
indications
© Sadovykh, Poisson, Papin, 2014
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22. 54% of SMBs
mainly employ
internal resources
for Data Analytics
implementation
Who implemented Data Analytics?
no data analytics
39%
our employees
consultants
54%
7%
© Sadovykh, Poisson, Papin, 2014
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23. Information Channels
13
SMBs prefer Web
sites to learn
about Big Data
6
6
5
3
News WebSites
Blogs
© Sadovykh, Poisson, Papin, 2014
Conferences
Press
IT Consulting
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24. Procurement Channels
80% of IT SMBs prefer
to buy through selfservice
web channels
12
3
2
Web-site
IT Consulting
© Sadovykh, Poisson, Papin, 2014
Sales reps
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25. For Non-ITs:
“Sales
representatives
bring value”
© Sadovykh, Poisson, Papin, 2014
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26. Budget
limitations
Potential pain
points for
Big Data at SMBs
Lack of
employees
experienced
Risk aversion,
need for ROI
guarantees
in Big Data
Difficulty to
formulate right
questions, need
for guidance
Security
concerns
Extreme variety
of data
Need for very
custom solution
© Sadovykh, Poisson, Papin, 2014
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27. • 59% consider important budget
limitations at SMBs
• 55% indicate ROI guarantees as highly
desirable
• 59% report lack of personnel
experienced in Big Data and Data
Analytics as a potentiall blocking
point
© Sadovykh, Poisson, Papin, 2014
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28. • 59% report that SMBs need guidance
when dealing with Big Data
• 59% consider security aspects
important.
• Though, non-ITs are ready to rely on
data centers.
• 55% indicate data variety concerns
• 69% report the need for very custom
solution.
© Sadovykh, Poisson, Papin, 2014
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29. SMB Trends for 2014
62% hope
to grow revenue
by11%
44% estimate
data traffic grow
by 30%
54% think
to grow
data storage
by 30%
81% estimate
that their
infrastructure is
ready
© Sadovykh, Poisson, Papin, 2014
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30. PART #4:
RECOMMENDATIONS
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31. Recommendations
Clearly explain
ROI gains when
addressing SMB
market.
Concentrate on
turn key services.
Provide scalable
self-services to
SMBs.
Start adopting Big
Data from
marketing
analytics.
Cost and risk
reduction services
are largely
untapped.
© Sadovykh, Poisson, Papin, 2014
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32. BIG DATA COULD BE THE SOLUTION
FOR YOUR BUSINESS TOMORROW…
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33. Contacts
• For further information and
full report please contact:
• Andrey.Sadovykh@hec.edu
• Paul-Emile.Poisson@hec.edu
• Aleksei.Papin@hec.edu
This presentation is prepared in the context of the consulting
project conducted by HEC Paris Business School
© Sadovykh, Poisson, Papin, 2014
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