VALUE CREATION FOR SMBs
WITH BIG DATA
by: Andrey Sadovykh, Paul-Emile Poisson, Aleksei Papin
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
2
Summary
© Sadovykh, Poisson, Papin, 2014
PART #1: BIG DATA
PHENOMENON 3
Big Data = Volume + Variety + Velocity
4 Source : IDC & EMC
Volume = sheer amount of data
Variety = polystructured nature = text, audio and video
Velocity = rate at which it is generated and analyzed
Big data
is
commonly
characterized
by three
vectors:
Data grows exponentially
5 Source : IDC & EMC
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)
Only ½ % of Data is analyzed
6 Source : IDC & EMC
In 2012, 2 837EB generated - just ½% actually analyzed.
That still amounts to 14EB (or 14.185 million terabytes)
Not all of data
generated will be
actually useful
Practically all that we do creates data
7
1. Number of @-mails sent every second : 2,9 million
2. Video uploaded to YouTube every minute: 25 hours
3. Data processed by Google every day: 24 petabytes
4. Tweets per day: 50 million
5. Products ordered on Amazon per second: 73 items
How big is the market?
8
In March 2012 it was forecasted that big data will become a $17 billion market by 2015 (since updated to $23.8bn by 2016 )
The chances are, though, that big data will take its place in the mainstream
of IT activities.
Source : IDC & EMC
0
5
10
15
20
25
2010 2011 2012 2013 2014 2015 2016
$(B
illio
ns)
Big Data Pure Players 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
9
SMBs generate almost 60% of added value
Small business,
but big revenues
Source : EuroStat
10
SMBs can leverage Big Data
Traditional analytics means cannot cope
with such volumes, variety and velocity of
data.
Big Data phenomenon is driven by
accelerated growth of the unstructured
data.
Proliferation of Cloud computing and
Software-as-a-Service made it possible for
appearance of affordable data analytics
tools for SMBs.
1.
2.
3.
© Sadovykh, Poisson, Papin, 2014
PART #2: BIG DATA
SERVICE PROVIDERS 11
Data, Platforms, Analytics, Applications
Platforms Visualization / Analytics
Data Providers
Ads Targeting
Marketing Analytics
Fraud Detection / Costs
© Sadovykh, Poisson, Papin, 2014
Findings
13
Managed services for business specific
statistical models start to appear with
the first results in fraud detection or
climate fine forecast.
Business analytics: companies can
build their own data analytics and
reporting on the web from ready to use
building blocks.
Marketing analytics is a mature industry
with many players addressing SMB
sector
© Sadovykh, Poisson, Papin, 2014
PART #3: SMB SURVEY 14
15
32 SMBs
participated in our
survey about:
Big Data phenomenon understanding
Value creation and Go-To-Market
SMBs’ pain points
Trends
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
Packaging
Import/Export services
16
We interviewed SMBs
from different
sectors.
Most interviewed
SMBs are micro
companies and
IT related.
SMB Sectors
48%
7%
14%
10%
4% 17% <200 K€
200 K€ to 500 K€
500 K€ to 1 M€
1 M€ to 3 M€
3 M€ to 10 M€
> 10 M€ Non-IT SMBs
SMB Revenues
© Sadovykh, Poisson, Papin, 2014
17
Most SMBs associate
Big Data value
with Web Services for
Data Analytics
22%
33%
56%
44%
Web Service for
Data Analytics
Data Processing
Tools for Developers
Not agree Agree
© Sadovykh, Poisson, Papin, 2014
18
Statistical Models
and Data Integration
bring the most value
to SMBs
19% 19%
7%
56%
74% 78%
Data
Visualization
Statistical
Models
Data
Integration
Not agree Agree
© Sadovykh, Poisson, Papin, 2014
19
Not all SMBs
managed to
apply Big Data
38% do not use Data
Analytics
© Sadovykh, Poisson, Papin, 2014
20
Sales increase
preoccupation
prevails 67%
56%
22%
Sales
increase
Cost
reduction
Risk
reduction
© Sadovykh, Poisson, Papin, 2014
21
SMBs struggled to
provide
quantifiable ROI
indications
© Sadovykh, Poisson, Papin, 2014
22
54% of SMBs
mainly employ
internal resources
for Data Analytics
implementation
7%
54%
39%
consultants
our employees
no data analytics
Who implemented Data Analytics?
© Sadovykh, Poisson, Papin, 2014
23
SMBs prefer Web
sites to learn
about Big Data
13
6
5
6
3
News Web-
Sites
Blogs Conferences Press IT Consulting
Information Channels
© Sadovykh, Poisson, Papin, 2014
24
80% of IT SMBs prefer
to buy through self-
service
web channels
12
3
2
Web-site IT Consulting Sales reps
Procurement Channels
© Sadovykh, Poisson, Papin, 2014
25
For Non-ITs:
“Sales
representatives
bring value”
© Sadovykh, Poisson, Papin, 2014
26
Potential pain
points for
Big Data at SMBs
Budget limitations
Risk aversion, need for ROI guarantees
Lack of employees
experienced
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
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
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
62% hope
to grow revenue by11%
54% think
to grow data storage
by 30%
44% estimate
data traffic grow by 30%
81% estimate that their
infrastructure is ready
29
SMB Trends for 2014
© Sadovykh, Poisson, Papin, 2014
PART #4:
RECOMMENDATIONS
30
Concentrate on turn key services.
Clearly explain ROI gains when addressing SMB
market.
Provide scalable self-services to
SMBs.
Start adopting Big Data from marketing analytics.
Cost and risk reduction services
are largely untapped.
31
Recommendations
© Sadovykh, Poisson, Papin, 2014
BIG DATA COULD BE THE SOLUTION
FOR YOUR BUSINESS TOMORROW…
32
33
Contacts
• For further information and
full report please contact:
This presentation is prepared in the context of the consulting
project conducted by HEC Paris Business School
© Sadovykh, Poisson, Papin, 2014