20-21 February 2018, Mexico City: Workshop on building business linkages that books SME productivity. oe.cd/sme

1. Data
Analy)cs
in
SMEs
Relevant
Policies
Veronika
Michalkova
Policy
Analyst,
Ministry
of
Economy,
Slovakia

2. Data-­‐driven
decision
making
to
increase
SME
produc)vity
Data
Analy)cs
in
SMEs
• Data
Analy)cs
as
one
of
the
most
important
recent
trends
in
digitaliza)on
• Closely
linked
to
Industry
4.0
• Data-­‐driven
decision
making
=
leveraging
Data
Analy)cs
to
make
informed
decisions
• Volume,
Velocity,
Variety
+
• Posi)ve
impact
on
produc)vity
for
SMEs
Genera)on
Collec)on
Storage
Processing
Distribu)on
Analy)cs
Source:
OECD,
2013
The
data
value
chain
and
life
cycle

3. Big
Data
Analysis
by
SMEs
Data
Analy)cs
in
SMEs
Big
Data
Analysis
by
SMEs
in
the
EU
0
2
4
6
8
10
12
14
16
18
20
Malta
Netherlands
Belgium
United
Kingdom
Finland
Portugal
Estonia
Lithuania
Luxembourg
Denmark
Greece
France
Romania
European
Union
Slovenia
Slovakia
CroaQa
Italy
Sweden
Czech
Republic
Spain
Bulgaria
Hungary
Poland
Germany
Cyprus
%
Enterprises
analysing
big
data
from
any
data
source
Big
data
analysis
done
by
the
enterprise's
own
employees
Big
data
analysis
done
by
an
external
service
provider
Note:
Financial
sector
not
included
Source:
Eurostat,
2017
The
use
of
Big
Data
by
SMEs
remains
limited,
similarly
to
the
use
of
Enterprise
Informa)on
soNware
and
Cloud
solu)ons.

4. Effect
on
produc)vity
of
the
adop)on
of
data
analy)cs
by
SMEs
Data
Analy)cs
in
SMEs
§ Inves)ng
in
data
analy)cs
can
bring
important
producQvity
gains
of
6-­‐8%
in
(Baughin,
2017),
5-­‐10%
in
(OECD,
2015);
§ Firms
that
adopt
data-­‐driven
decision
making
obtain
5-­‐6%
higher
output
and
producQvity
than
with
other
ICT
investments
(Brynjolfsson,
2011).
§ Data
analyQcs
supplemented
with
cloud
soluQons,
allows
SMEs
to
scale
rapidly
with
low
ini)al
costs;
§ SMEs
enjoy
also
higher
customers
and
employees’
sa)sfac)on,
beRer
environmental
or
social
performance.
EXAMPLE:
study
in
the
UK
showed
that
out
of
500
firms,
the
top
quarQle
in
online
data-­‐use
were
13%
more
producQve
than
the
bocom
quarQle
Investment
in
Data
analyQcs
increases
producQvity…
…and
brings
other
relevant
benefits…
§ Make
complementary
investments
in
organisaQonal
and
managerial
capabili)es;
§ Increase
the
level
of
digital
literacy
of
employees;
§ Assess
and
manage
the
digital
risk
…but
investments
in
human
capital
is
needed

5. Benefits
of
Data
exploita)on
for
SMEs
Data
Analy)cs
in
SMEs
An
OECD
study
of
five
sectors
(online
adver)sement,
health
care,
u)li)es,
logis)cs
and
transport,
public
sector)
iden)fied
benefits
of
data
exploita)on:
• enhancing
research
and
development
(data-­‐driven
R&D)
• developing
new
goods
and
services
by
using
data
either
as
a
product
or
as
a
major
component
(data
products
and
data-­‐intensive
products)
• opQmising
producQon
or
delivery
processes
(data-­‐driven
processes)
• improving
markeQng
by
providing
targeted
adverQsements
and
personalised
recommendaQons
(data-­‐driven
marke)ng)
• developing
new
organisaQonal
and
management
approaches
or
significantly
improving
exisQng
pracQces
(data-­‐driven
organisa)on)

6. Seizing
the
benefits
of
Big
Data
Data
Analy)cs
in
SMEs
Organiza)onal
aspects
• Choosing
the
right
organiza)onal
model
–
a
single
analyst
unit
/
decentraliza)on
/
hybrid
(Grossman,
Siegel,
2014)
• Analy)cs
complemented
with
adequate
repor)ng
• Investments
in
human
capital
Technical
aspects
• Cloud
compu)ng
–
no
need
for
massive
infrastructure
investments,
more
aRrac)ve
solu)on
for
SMEs
• Overcome
lock-­‐in
effects
and
long-­‐term
contracts
• User-­‐friendly
tools,
open
source
soNware
• Considering
all
relevant
sources
• Data
intensity
highest
in
financial
services,
communicaQon,
uQliQes
and
discrete
manufacturing
sectors
(MGI,
2001)

7. Data-­‐driven
decision
making
–
challenges
to
SMEs
Data
Analy)cs
in
SMEs
Internal
Barriers
•
Lack
of
knowledge
and
awareness
•
Lack
of
skilled
human
capital
•
Mistrust
in
digital
economy
•
Ability
to
address
digital
risks
•
Limited
collec)on
and/or
storage
of
data
External
Barriers
•
Access
to
finance
•
Availability
of
data
•
Complex
regulatory
environment
•
Personal
data
restric)ons
•
Limited
choice
of
SME-­‐tailored
solu)ons

8. Poten)al
and
relevant
policies
Data
Analy)cs
in
SMEs
Regulatory
environment
• Special
regime
for
SMEs
in
the
area
of
data
protecQon
rules,
compliance
guidelines
• Assistance
in
addressing
digital
threats
• Data
localizaQon
• Open
data
iniQaQves
Skills
and
training
• Employee
training
program
focused
on
data
analyQcs
• Awareness
raising
through
management
training
• SME
Agencies
as
Big
Data
Sherpa
• DisseminaQng
best
pracQces,
templates
and
promoQng
successful
case-­‐studies
• Knowledge
diffusion
through
chambers
of
commerce,
SME
associaQons
Financial
support
• Vouchers
for
POC
studies
• Target
other
financial
support
schemes
to
the
use
of
ICT
and
data
Regulatory
environment
Skills
and
training
Financial
support

9. Thank
you!
veronika.michalkova@economy.gov.sk