hrt-9019 applying data science technologies to overcome ... · from content such as concepts,...

HRT-9019Applying Data Science Technologies to Overcome Job Confusion -Watson Talent Competency Insights —Stephen MitchellLead Data Scientist – Watson TalentJohn MedickeDistinguished Engineer

Think 2018 / HRT-9019 / March 19, 2018 / © 2018 IBM Corporation

Please note

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The information mentioned regarding potential future products is not a commitment, promise, or legal obligation to deliver any material, code or functionality. Information about potential future products may not be incorporated into any contract.

The development, release, and timing of any future features or functionality described for our products remains at our sole discretion.

Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will experience will vary depending upon many factors, including considerations such as the amount of multiprogramming in the user’s job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results similar to those stated here.

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Background

Economic value creation is increasingly based on highly specialized skills and knowledge.

Disruptive technologies and socio-economic forces can swiftly outdate the shelf life of people’s skill sets.

By 2020, across all types of occupations, more than a third of the core skills needed to perform most jobs will be made up of skills not yet considered crucial to the job (source: World Economic Forum).

The notion of a “job for life” is disappearing. However...

…the average worker in the US has 48 potential job transition possibilities.

Think 2018 / HRT-9019 / March 19, 2018 / © 2018 IBM Corporation 3

From: Towards a Reskilling Revolution: A Future of Jobs for All. World Economic Forum, January 2018


Talent and skill shortages are widespread, highest talent shortages since 20071

Technology disrupts how we work and creates new jobs which require new skills

Candidate Experience impacts the business and Recruitment has become Marketing

Employees are demanding new careers, career guidance and engaging experiences What got you here will not get you there

Traditional ATSCore systems Like HRIS

ERP/single suite

Source: Manpower Group – Talent Shortage Survey 2016/2017

The Talent Landscape has dramatically changed

Our Methods must change too


Assess, Select & Hire best “fit”

IBM Watson Talent will augment your talent management foundation

Know Skills & Competencies

Build strong candidate relations and proactive talent pools

Deliver great Candidate Experiences & motivate candidates to apply

Get automatic recommendations of best fit talent

Activate Career Growth and Internal Mobility

Enable PersonalizedLearning & Development

Create Data-Driven Success Profiles Ongoing

Learning and Development

Improve ROI of your talent

Watson TalentTalent Mgmt. Best Practices

ReqPrioritization

Social Listening and Real-time Insights for Recruiters

Find your Fit

IBM WatsonCandidate Assist IBM Watson

Recruitment

IBM WatsonCareer Coach

Develop the existing talent Attract new talent Know what ‘success’ looks like


IBM Watson Candidate Assistant: A Next Generation Candidate Experience

Engages candidates in a deeper conversation and recommends jobs relevant to candidate’s personality, skills and interests

Attract New Talent with Irresistible Experiences#NoMoreBlackHoles #StopSearchingBeFound


Finding Relevant Jobs and Matching to Candidates

Competencies, Interests, Experiences,

Expectations

Job Match Scorer

Job Description

Experiences, Expectations, Interests

Upload CVCV Parser

User Competency and Experience

Profile

Job Competency Model

Job Requisition

Job Discovery

• Watson Conversation• Watson Natural Language Understanding

Job Matching

……

Engagement

Company Culture, Branding andEngagement

User Model


IBM Watson Recruitment: World’s first and only cognitive recruitment solution designed to improve quality of hire and recruiter efficiency

• Automatically prioritizes jobs and predicts application progress to focus recruitment efforts

• Automatically recommends the most qualified candidates with maximum predicted level of success

• Accelerates candidate conversions using Social listening with real-time marketing and competitive insights


Watson Recruitment can adapt to how the client defines success

Success

Qualify

Screen

Interview

OfferAccept

Survival

Performance

• Watson Recruitment can learn what success means based on data

• Success is defined by hiring data or post-hire employee data for deeper insights

• Model learns key ingredients in success based on data available


Watson Recruitment: The Job Matching Flow

Analysis of Historical

Hiring Creation of Success Profile

per JobSuccess Profile from Talent Frameworks

Create Requisition

Apply Success Profile

Applications

Scoring of ApplicantsAnalyze

• Watson Discovery News• Watson Natural Language Understanding• Watson Natural Language Classifier

50 dimensions including prior experience , education,

certifications, assessments, competencies, etc..

Think 2018 / HRT-9019 / March 19, 2018 / © 2018 IBM Corporation12

IBM Watson Career Coach: World’s first and only cognitive career coach, recognized by Deloitte as key Cognitive Innovation

Personalized Career Advisor

Personalized Job Match

Personalized Career

Navigator

Greater Employee Engagement and Talent Mobility

Discovers an employee's true desires and abilities and matches them with opportunities within a company resulting in higher employee engagement, retention, growth and internal mobility


A Personal Coach For Every Employee in Your Workforce

Career Navigator

Resume, Skills, Experiences – Profile

Job Opportunities

Coach

Job Matching

Fit, Demand, Movement

Details

Apply

Add to Path

Details

CareerRecommender

JobScorer

Job Taxonomy

Job Requisition

Talent Card Learning Recommendations


Job Opportunities

Employee Competencies

and Experiences

Job Match Scorer

Job Description

Profile

Add Experiences and Competencies

Upload CVCV Parser

User Competency and Experience

Profile

Job Competency Model

Job Requisition

Talent Card

Job Recommendation

• Watson Conversation• Watson Natural Language Understanding• Watson Natural Language Classifier

Job Matching


Career Navigator

Profile

Add Experiences and Competencies

Employee Current Job

All Employees History

Employee Job History,

Competencies

Job Profiles

Job Transition Model

User Competency

Profile

Movement Score

Fit Score

Demand Score

Career Move Recommender

Fit Scorer

Job Taxonomy

Talent Card

Career Recommendations

• Watson Conversation• Watson Natural Language Understanding• Watson Natural Language Classifier


Watson Services used in Watson Talent

Key Watson Capabilities Used Unstructured Analytical Value Where it’s used

Watson Discovery

Unlock hidden value in data to find answers, monitor trends and surface patterns

Natural Language Understanding

Analyze text to extract meta-data from content such as concepts, entities, keywords and more

Conversation

Quickly build and deploy chatbotsand virtual agents across a variety of channels

Machine Learning

Models & algorithms learn from data and find hidden insights

Watson Candidate Assistant

Watson Recruitment

Watson Career Coach

Enhanced search to discover trends and important topics within the talent landscape, jobs and competencies.

Deeper understanding of concepts, recognized entities, keywords and relationships

Inquire about job opportunities and enhance career conversations by determining skillsets and goals to be achieved

Extract value from rich volumes of text to rank jobs based on analysis and find best fit talent

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Best Practices in Applied ML


Challenges of doing data science in HR space

• High degree of unstructured data• Heterogeneous environment of Human

Capital Management (HCM) Systems.• HR Processes often operate outside the

system of record. • Minimal controls or standardization on data

governance.


Making sense of the ambiguity of talent acquisition data

– Natural language processing

– Job profiles, skills, and competency models

– Standardization

– Feature engineering

– Machine learning

– Influencers of success

….. ….. …. …. …. ….. … …..

….. ….. …. …. …. ….. … …..

….. ….. …. …. …. ….. … …..

….. ….. …. …. …. ….. … …..

….. ….. …. …. …. ….. … …..

….. ….. …. …. …. ….. … …..


Using the Natural Language Classifier• Natural Language Classifier is used on broad, cross-industry skills that may be

described in many ways through work experience or responsibilities

• Watson NLC is trained to recognize these foundational skills through TF competency definitions and proficiency levels as well as training data from resumes and job requisitions

• Tested for predictive strength and weighted accordingly


Feature Engineering

• Using Watson NLC we can take unstructured data about skills (hard and soft), job history, and educational background and transform these data into multiple features for our machine learning models to train on.

Resume + Other Job Application Data

50 dimensions of competencies


Auto ML approach for applicant scoring

We employ an iterative approach to machine learning in which an ensemble of methods are utilized, each with a range of model parameters.

The best performing combination of machine learning model and parameter values are identified.

Machine Learning Algorithm #1

Machine Learning Algorithm #2

Machine Learning Algorithm #n

Most Accurate Machine Learning Algorithm and Machine Learning Parameter Values

Parameter Set #1

Parameter Set #2

Parameter Set #n


Model Validation

Data are split into a training dataset, a validation dataset, and a test dataset.

Validation Set Test SetßTraining Setà

Stratified Cross Validation

Model performance metrics (precision, recall, and more) are output to the user to aid in the interpretation of model classifications and performance.


Sneak peek into the future of HRExperience the latest big ideas in talent management - AI, cloud, mobile and more!

Technology and business thought leadersHear from the world's top influencers and thinkers, up-close and personal.

Network, network, networkConnect with your peers in exclusive HR roundtables, exchanges and receptions.

Sessions that challenge and provokeA full schedule of sessions focused exclusively on HR tech and talent management.

Hands-on access to new solutionsInteract with IBM's new talent management AI tools, guided by product experts.

https://www.ibm.com/talent-management/events/think

Combining Forces to Transform Your Business: How IT and HR leverage AI

Tuesday, March 2011:30-12:10pmLarge Theater, Business and AI Campus

HR Exchange at Think: Reinventing Talent, Transforming Business

Monday, March 19 12:00pm-5:00pmMandalay Bay Ballrooms A-D

Notices and disclaimers

26Think 2018 / January 12, 2018 / © 2018 IBM Corporation

© 2018 International Business Machines Corporation. No part of this document may be reproduced or transmitted in any form without written permission from IBM.U.S. Government Users Restricted Rights — use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM.Information in these presentations (including information relating to products that have not yet been announced by IBM) has been reviewed for accuracy as of the date of initial publication and could include unintentional technical or typographical errors. IBM shall have no responsibility to update this information. This document is distributed “as is” without any warranty, either express or implied. In no event, shall IBM be liable for any damage arising from the use of this information, including but not limited to, loss of data, business interruption, loss of profit or loss of opportunity. IBM products and services are warranted per the terms and conditions of the agreements under which they are provided.IBM products are manufactured from new parts or new and used parts. In some cases, a product may not be new and may have been previously installed. Regardless, our warranty terms apply.”Any statements regarding IBM's future direction, intent or product plans are subject to change or withdrawal without notice.

Performance data contained herein was generally obtained in a controlled, isolated environments. Customer examples are presented as illustrations of how thosecustomers have used IBM products and the results they may have achieved. Actual performance, cost, savings or other results in other operating environments may vary.References in this document to IBM products, programs, or services does not imply that IBM intends to make such products, programs or services available in all countries in which IBM operates or does business.Workshops, sessions and associated materials may have been prepared by independent session speakers, and do not necessarily reflect the views of IBM. All materials and discussions are provided for informational purposes only, and are neither intended to, nor shall constitute legal or other guidance or advice to any individual participant or their specific situation.It is the customer’s responsibility to insure its own compliance with legal requirements and to obtain advice of competent legal counsel as to the identification and interpretation of any relevant laws and regulatory requirements that may affect the customer’s business and any actions the customer may need to take to comply with such laws. IBM does not provide legal advice or represent or warrant that its services or products will ensure that the customer follows any law.

Notices and disclaimerscontinued

27Think 2018 / DOC ID / Month XX, 2018 / © 2018 IBM Corporation

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