pes & digital acceleration levers for the return to...

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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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