pes & digital acceleration levers for the return to...
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15 FÉVRIER 2013
WAPES EVENTS
HUE, VIET NAM
July 25 2018
PES & digital acceleration levers
for the return to employment
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SUMMARY
2.
Digital tools and web service
design for PES
3.
Matching performance :
from job title to skills-based approach
1.
Big data, data science & open
innovation to offer new services
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1. Big data, AI, data science & open innovation
to offer new services
Our data optimization program is
based on 4 pillars:
BIG DATA DATA
SCIENCE
A.I
Artificial
Intelligence
OPENINNOVATION
Open API
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BIG DATA : a wealth of data to value
The exemple of Data generated by
French Public Employement Service
- 50 000 employees
- 8 million registered job seekers
- 400 000 companies using its free recruitement services
- 7 million job offers per year
- 36 billion € of unemployment benefits paid per year
- 46 million visits per month on https://www.pole-emploi.fr
- 3 million downloadings of its mobile app
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BIG DATA : a wealth of data to value
French PES Pole Emploi
generate 2 Peta-bytes of data
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DATA SCIENCE : to make sense
and create new services
The 3 different levels of data enhancement:
- the 360 ° view of the data or their aggregation
- the predictive view of a situation
- providing recommendations or action prescriptions
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15 FÉVRIER 20137
DATA SCIENCE : to make sense
and create new services
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- making the best use of labor market data, uses and behaviors
- using powerful probabilistic analysis algorithms, logic, multi-agent
system, neural networks, textual corpus analysis ...
- learning from the behavior of our users (machine learning)
- understanding users and interacting with them through Natural
Language Processing (NLP) and NLG (Natural Language
Generation)
A.I
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- evaluate with each jobseeker his or her "chances of
success" , tell him precise and personalized informations
aboat labor market
- Indicate to companies when their offer is likely to find a
matching profile
- predict that a company is likely to recruit
- help job consultants to target priorities
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OPEN INNOVATION
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2. Digital tools and web service design
for PES
USES CHANGE :
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USER EXPERIENCE
USE FIRST !
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Before create a new webservice,
ask you the right question :
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I want to do a simple
search on the internet, only
one field of entry is enough
I don’t need media news, the
weather, the horoscope or the
stock market prices
Exemple : GOOGLE Vs YAHOO pages
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The exemple of Pole emploi website : only usefull services simply to use
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A job store with internal services and open to externals partnership
websites and apps referenced by Pole emploi
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Mobile Apps Pole emploi to find offers, a training course or a
MOOC, applicants, prepare an appointement, write a resume
and send it, do an evaluation test, be informed of events…
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3. Matching performance :
from job title to skill-based approach
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job seekers files / job offers = matching system mainly by the job title
BEFORE : JOB TITLE
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The jobseeker enters in his job seeking file website page a description of
his/her skills
He can be helped by the job consultant in describing them accurately
For some skills, an evaluation is proposed.
Training courses could be proposed to fill the gap if necessary
The information system generates a resume automatically
The recruiter enters the job offer description with the hard and soft skills
required
The matching system can find people (or propose many more offers) that
would not have appeared before
NOW : SKILLS FIRST
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Welcome to your « Skills profile »
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Exemple of a welder : skills self evaluation page (hard and soft skills)
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Thank you for your attention
For further information please contact :
@ Philippe PAUMARD
Montpellier- France
Training division manager
Information technology unit
DSI Pole emploi