Overview of O*NET Data Collection and Activities OIDAP Meeting Phil M. Lewis David R. Rivkin National Center for O*NET Development Pam Frugoli Employment and Training Administration, DOL May 4, 2011

1
Overview of ONET Data Collection and
ActivitiesOIDAP Meeting Phil M. LewisDavid
R. RivkinNational Center for ONET
DevelopmentPam FrugoliEmployment and Training
Administration, DOLMay 4, 2011
2
Goals of the Update Briefing

• Overview of ONET Project
• Data Collection Program
• Address OIDAP Questions
• Products Tools
• ONET Users
• Special Projects

3
OIDAP Questions

• Please describe how the ONET data collection
  strategy builds upon the BLS Occupational
  Employment Statistics (OES) database.
• Are you still using Dun Bradstreet data to find
  establishments? Were OES data not able to
  accomplish this, or is it an efficiency issue?
• What was the original balance between the
  Establishment Method and the Occupational Expert
  Method for populating the ONET database? Has
  that changed now that you are in maintenance
  mode? How are the occupational experts
  identified?
• Can you describe the role of the state workforce
  development offices in data collection for ONET?
  Has this changed over time?
• Why did ONET decide not to use field analysts to
  collect the data on occupations?

4
OIDAP Questions (cont.)

• What are the major challenges associated with
  identifying employees in specific occupations to
  observe in the field?
• How do Detailed Work Activities differ from
  Generalized Work Activities in the ONET? How
  were they empirically derived?
• We understand that a rule of thumb for
  statistical sufficiency was set at 15
  observations for each domain. Are you still
  satisfied with that number?
• Are you planning any changes in procedure or
  content as a result of the recent review of ONET
  by the National Research Council?
• How might your sampling parameters change if the
  results were subject to legal challenge?
• What advice do you have for SSA as they begin to
  develop an OIS for disability adjudication
  purposes?

5
Overview of ONET Project
6
Why ONET?

• 1980 Work, Jobs, and Occupations a Critical
  Review of the Dictionary of Occupational Titles
  (National Research Council)
• 1993 Final report of the Advisory Panel on the
  DOT (APDOT)
• 1999 The Changing Nature of Work Implications
  for Occupational Analysis
• 2000 ONET Data Collection Program Survey
  Pretest
• 2001 Official OMB approved ONET data collection
  using the ONET survey questionnaires
  initiated

7
ONET Project Team

• U.S. Department of Labor, Employment Training
  Administration
• National Center for ONET Development
• North Carolina Employment Security
• RTI MCNC HumRRO NC State University Maher
  Maher

8
National Center for ONET Development

• Data Collection
• Dissemination
• Implementation
• Research and Development
• Technical Assistance/Customer Support

9
What is ONET?

• A common language and dynamic system for
  describing the world of work for both the public
  and private sectors
• A comprehensive system for collecting and
  disseminating information on occupational and
  worker requirements

10
What is ONET?

• Flexible competency-based system with emphasis on
  skills transferability
• Framework for organizing job and worker
  information
• Data on occupations covering the entire U.S.
  Economy

11
What is ONET?

• Uses information technologies to facilitate the
  collection, storage, and distribution of quality
  data
• A resource for businesses, educators, job
  seekers, HR professionals, and publicly funded
  government programs

12
ONET Structure

• The ONET-SOC Occupational Taxonomy
• The ONET Content Model

13
SOC and ONET-SOC

• SOC mandated by US Office of Management and
  Budget
• Developed by multi-agency initiative

14
Key characteristics of U.S. SOC

• Structured for comparability
• Unified classification structure
• Four hierarchical levels to enable data
  collectors to choose a level of detail
  corresponding to their needs and ability to
  collect data on different occupations

15
SOC and ONET-SOC

• ONET-SOC is a SOC based classification that
  provides a greater level of detail as needed
• ONET-SOC 2010 taxonomy released December 2010
• Currently data collected on 974 ONET-SOCs
• Adds 269 more specific occupations
• New and emerging
• Different tasks and KSAs

16
ONET Content Model
17
Content Model Sub-Domains
Worker Characteristics Abilities Interests Work
Styles
Abilities Cognitive Psychomotor Physical Sensory
Cognitive Verbal Idea Generation
Reasoning Quantitative Memory Perceptual Spatial A
ttentiveness
Verbal Oral Comprehension Written
Comprehension Oral Expression Written Expression
http//www.onetcenter.org/content.html
18
The ONET Database Version 15.1

• Occupation data
• Cross-Occupational Occupation Specific
• 230 variables
• Importance, level, frequency
• _at_ 500 ratings per occupation
• _at_ 3500 metadata per occupation

Scales Reference
Abilities
Content Model Reference
Skills
Educ, Trng Exp Categories
Survey Booklet Locations
Task Categories
Educ, Trng Exp
Task Ratings
Interests
Task Statements
Job Zone Reference
Supplemental Files
Work Activities
Job Zones

• Related Occupations
• Crosswalks
• Detailed Work Activities
• Emerging Tasks
• Lay Titles
• Tools and Technology
• ONET-SOC 2000 to ONET-SOC 2006
• Tasks (Release 5.1 File Layout)?
• Work Needs

• Crosswalks
• Detailed Work Activities
• Emerging Tasks
• In-Demand Occupations
• Lay Titles
• Related Occupations
• Tools and Technology
• Work Needs

Work Context Categories
Knowledge
Work Context
Level Scale Anchors
Work Styles
Occupation Data
Occupation Level Metadata
Work Values
19
The ONET Database Metadata

• Occupational Level Statistics
• ONET-SOC Establishment Response Rate
• ONET-SOC Employee Response Rate
• ONET-SOC Case Completeness Rate
• Total Completes for ONET-SOC

• Ratings Level Statistics
• Confidence Intervals
• Lower and upper 95 bounds
• Standard Deviation
• Standard Error
• Sample Size
• Flags
• Not Relevant for the Occupation
• Recommended Suppression

• Occupational Level Distribution Statistics
• Data Collection Mode
• Current Job Tenure
• Industry

20
ONET Data Availability

• 874 occupations
• Comprehensive data
• 359 second update
• 100 occupations
• Description, task list, lay titles
• Majority also have interests, work values, and
  tools technology

21
ONET Data Publication Goals

• New database released annually
• Minimum of 100 occupations updated
• Average currency of all occupations 2.59 years
• Priority established by DOL
• Maximum 5 years-old
• Bright Outlook
• Green occupations
• Linked to technology, math, and science,
  computers, engineering, and innovation

22
ONET Data Currency
23
ONET Data Collection Program
24
ONET Data Collection Overview

• Proven successful and cost effective methodology
  designed to collect and yield high quality
  occupational data
• Multi-method approach to provide flexibility
  within a framework of standardized procedures
• Establishment, Occupational Expert, Supplemental
  Frames, Analyst Ratings, Web-Based
• Minimizes public burden and costs
• Approved by Office of Management Budget (OMB)

25
ONET Data Collection Overview

• Continuous data collection since June 2001
• Three successful OMB Clearances
• Comprehensive update by job incumbents and
  occupational experts of the 2006 ONET-SOC
  Taxonomy
• Transition to 2010 ONET-SOC
• New Emerging occupations
• Unparalleled partnership between Department of
  Labor and private/public community
• 40,000 business/organizations
• 160,000 job incumbents/experts
• 450 National Associations

26
Data Collection Overview (cont.)

• High quality data from a national sample of job
  incumbents/occupational experts
• Strong business participation
• 76 plus response rate
• Strong employee participation
• 65 plus response rate
• Strong occupation expert participation
• 82 response

27
Data Collection Overview (cont.)

• Web-based case management system used to control
  all sampling and data collection systems
• Case management, BL contacts with establishments,
  questionnaire and informational mailings,
  questionnaire processing, inventory control, etc.
• Finely tuned procedures, systems and
  infrastructure capable of surveying multiple
  occupations simultaneously
• Capability developed, tested, and enhanced over
  11 years

28
Sources of Occupational Data

• Job Incumbents and Occupation Experts
• Education, Job Titles, Knowledge, Tasks, Work
  Activities, Work Context, Work Experience, Work
  Styles
• Occupation Analysts
• Abilities, Skills
• Web-based Research
• Detailed Work Activities, Green, Tasks, Tools and
  Technologies (T2)

29
Establishment Method

• Two stage sample
• Business establishments - POC
• Job incumbents within business establishments

30
Establishment Method (cont.)

• Job incumbents complete one of three survey
  questionnaires (25 -30 minutes)
• Generalized Work Activities, Knowledge/Work
  Styles, or Work Context
• Task List
• Background Info
• Incumbents choose response option
• Paper-and-pencil
• Web-based (approximately 25)

31
Design of Collection Waves

• Identify 50 primary occupations to target in a
  sample wave
• Wave X.1 Designed to get 34 of sample
• Wave X.2 Designed to get 33 of sample
• Wave X.3 Designed to get 33 of sample
• Wave X.4 Sample residual

32
Design of Collection Waves (cont.)

• Each wave is a cluster of similar occupations
• Secondary occupations which are found across
  industries are also included to maximize
  efficiency
• Multiple sub-waves allow for greater precision
• Locating occupations
• Controlling public burden and project resources

33
Stage One Sampling

• OES data from BLS used to determine the initial
  industry distribution for each occupation
• Sample business establishments selected from
  database of business locations

34
Stage One Sampling (cont.)

• OES data from BLS used to determine the initial
  industry distribution for each occupation
• Indicates which industries occupations are
  employed in and the share and distribution of
  occupational employment across industries
• Does not contain information on establishments

35
Stage One Sampling (cont.)

• Industry information for each occupation is
  refined by ONET Center analysts
• Review and face validity checks
• For example, religious institution sub-section
  removed from service industry if sampling for
  bartenders
• Determine industries to include based on overall
  distribution and population coverage goals
• Refined/target by experience from previous
  updates, when available

36
Stage One Sampling (cont.)

• Sample business establishments selected from a
  frame of business locations
• Dunn Bradstreet (DB) database
• 15 Million establishments
• Info obtained from multiple sources
• Tax records, credit reports, telephone
  directories
• Updated continuously on a monthly basis
• Links to SIC and NAICS industry information

37
Population Coverage

• Gather data on the core of the occupation
• Where the majority of incumbents employed
• Average coverage level is 85

38
Population Coverage (cont.)
39
Stage Two Sampling

• Led by highly qualified ONET Business Liaisons
  (ONET BL)
• Full time staff working in dedicated call center
• Educational and work experience criteria higher
  than typical telephone interviewer
• The sampled establishments Point-of-Contact
  (POC) works with the ONET BL to identify the a
  list of eligible employees
• Identification Profiles (ID Profile) are used
  when asking POC if occupations are present
• Helps ensure accuracy in matching employees to
  occupations

40
Stage Two Sampling (cont.)

• Automated, random selection of job incumbents
  from the POCs eligible list
• Limits placed on POC burden
• No more than 5 occupations sampled
• Never more than 20 employees selected
• Can only be included within the data collection
  once each year
• Selected employees
• Asked to complete the questionnaire on their own
  time
• Responses remain anonymous and confidential from
  both the employer and the public
• Complete via the web or mail back directly
• All individual identifiers removed

41
Model-Aided Sampling (MAS)

• Innovative sampling approach that reduces data
  collection cost and burden to the public by
  preventing occupations from greatly exceeding
  their targeted sample
• Builds on existing sampling paradigms
  traditional and model based
• For each occupation, a targeted sample size for
  specific demographic domains is modeled
• Census region
• Establishment size
• Industry division
• Data collection is halted in a MAS cell when the
  targeted respondent sample size is projected to
  be achieved

42
Summary of Establishment Method Sample Selection
Process
42
43
Establishment Method Data Collection Protocol
43
44
Other Key Features

• Incentives
• Employer
• Toolkit for Business
• POC
• Clock, Certificate of Appreciation
• Employee
• 10
• Outreach to professional/trade associations
  increase awareness
• Endorsement list provided to POC

45
Supplemental Frame Method

• Multiple strategies to augment the establishment
  data collection
• Supplemental Frame Incumbent
• Job incumbents are directly accessed via an
  association listing to complete the data
  collection
• e.g. Industrial Organizational Psychologists
• Supplemental Frame Establishment
• Targeted employer sample developed via expert
  contact/associations where the sampling frame
  coverage is significantly high but is not
  adequate by itself
• e.g. Freight and Cargo Inspectors
• Special Frame Establishment
• Targeted employer sample completely developed via
  expert contact/associations where coverage is
  extremely high
• Normal establishment method is bypassed
• e.g. Nuclear Power Reactor Operators Flight
  Attendants

46
Occupational Experts (OE) Method

• Used when occupation is difficult to locate in
  establishments
• Small employment size
• Job incumbents inaccessible due to work in remote
  locations
• New and emerging occupations

47
OE Method (cont.)
47

• Data collected from experts in target occupation
• Supervisors, trainers, others with extensive
  knowledge of occupation
• Identify appropriate source organizations (e.g.
  professional associations)
• Good coverage of occupation
• Can identify members who are occupation experts
• Willing to provide lists of experts

48
OE Method (cont.)
48

• Select sample from membership lists
• Contact, screen, and survey OEs directly no
  establishment or POC
• OEs complete all three domain questionnaires,
  background and task questionnaires
• OE incentives clock, Certificate of
  Appreciation, 40

49
OE Method DataCollection Protocol
49
50
Analyst Ratings Method

• Occupational Analysts Rate the Ability and Skill
  Domains
• Updated occupation information collected from job
  incumbents used to describe occupation and assist
  with the rating process
• Extensive training and quality assurance
  procedures

51
Analyst Rating Process
52
Stimulus Material

• Occupation title and definition
• Job Zone
• Important knowledges
• Mean importance of core and supplementary tasks
• Mean importance of GWAs that
• Mean gt 3.0 for occupation
• Require the targeted ability/skill to be
  performed
• Mean rating of work context statements that
• Mean gt 3.0 for occupation
• Require the targeted ability/skill to work in
  that context

53
Data Collection

• Two groups of eight analysts
• Both groups first given same 10 occupations
• Rate importance and level of 52 abilities and 35
  skills
• Ratings compared and discussed if warranted
• Batches of five occupations/week different
  occupations to each group of 8
• Evaluate agreement (SEM) facilitate discussion
  if SEM gt .51 for importance

54
Analysts Qualifications

• 16 Trained Analysts
• 5 years work experience
• Currently work for diverse organizations
• Marriott, FedEx, SAS, DDI
• Not internship, assistantship or summer job
• Masters or PhD degree in I/O psychology,
  vocational psychology, human resources (business
  department) or industrial relations
• Graduate level job analysis course (or something
  comparable)
• Graduate level research methods course (or
  something comparable)

55
Analyst Training

• 1 ½ days
• Hands-on exercises, quizzes, and rating practice
• Module 1 History of ONET
• Module 2 Overview of Stimulus Materials
• Module 3 Making Your Ratings
• Module 4 Recording Your Ratings
• Refresher training

56
Web-Based Method

• Trained analysts collect and process more
  specific occupational information from industry,
  professional, labor, and educational
  organizations
• Scan internet for existing information linked to
  ONET-SOC
• Collect tasks and detailed information
• Compile data, analyze data/expert review
• Organize using standardized taxonomies
• Generate final output

57
Special Projects
58
Revision of Data Collection Instruments

• Variety of cognitive methods used to evaluate the
  content and design of the initial ONET data
  collection surveys
• Expert evaluation (cognitive forms appraisal)
• Expanded interviews with individual respondents
• Focus group interviews
• Results led to significant enhancements to the
  instruments while maintaining comparability to
  the theoretical underpinnings of the variables
  and taxonomies, as well their psychometric
  qualities
• Simplification of instructions and layout
• Reduction in the number of items and scales per
  item
• Wording changes to specific variable definitions
• Current item response rate range 96-99

http//www.onetcenter.org/reports/Data_appnd.html
59
ONET Integration Projects

• Occupational Code Assignment
• Formal request of an assignment of a
  job/occupation to the ONET-SOC Taxonomy
• Lay titles
• 50,000 titles
• Average of 57 titles linked per occupation
• Crosswalks
• Military Occupational Classification (MOC)
• Registered Apprenticeship Partners Information
  Data System (RAPIDS)
• Classification of Instructional Programs (CIP)
• Dictionary of Occupational Titles (DOT)
• Standard Occupational Classification (SOC)
• ONET Online Applications
• Browse by Career Cluster
• Browse by Bright Outlook
• Browse by Industry

60
ONET Career Exploration Tools
http//www.onetcenter.org/tools.html
61
Tools and Technology (T2)

• Machine, Equipment, Tools, and Software workers
  must be able to use for optimal functioning in a
  high performance workplace
• This is what employers refer to as Hard Skills
• Emphasis placed on cutting edge technologies and
  emerging workplace practices
• http//online.onetcenter.org/link/summary/17-2081.
  00

62
Tools and Technology (T2)

• 620 occupations populated
• All green occupations
• 43,000 objects
• 76 objects per occupation on average
• Range 12-300

63
T2 Development

• Internet based data collection
• Build on previous ONET project tasks (i.e., task
  development)
• Trained analysts
• Strong proficiency in Internet searching
  procedures
• Strong background and training in occupational
  analysis

64
T2 Development (cont.)

• Data classification
• United Nations Standard Products and Services
  Code classification system (UNSPSC)
• Quality control
• Customer input
• Feedback via ONET Online ONET Resource
  Center http//www.onetcenter.org/t2/
• Transactional analysis of DOLs Job Description
  Writer

65
ONET New Emerging (N E) Project

• 154 New Emerging Occupations Identified
• Significantly different work from existing
  ONET-SOCs
• Not adequately reflected in current
  classification
• Significant employment
• Positive projected growth rate
• Education, credentialing, certification programs
• Related professional associations
• http//www.onetcenter.org/reports/NewEmerging.html

66
ONET N E Project (cont.)

• Investigated 17 In-Demand Industries

• Advanced Manufacturing
• Aerospace
• Automotive
• Biotechnology
• Construction
• Education
• Energy
• Financial Services
• Geospatial Technology

• Green
• Health Care
• Homeland Security
• Hospitality
• Information Technology
• Nanotechnology
• Retail
• Transportation

67
ONET N E Project (cont.)

• Extensive Web Search Conducted by Trained
  Occupational Analysts
• Industry Associations and Organizations
• Educational Programs
• Job posting sites
• Information Gathered, Documented, and Detailed
  Criteria for Inclusion Applied

68
ONET N E Project (cont.)

• Trained occupational analysts conduct extensive
  web searches to investigate each industry
• Background of industry (i.e., when industry
  started changing)
• Major innovations in industry
• Employment trends
• New products
• Government regulations (e.g., Automotive
  Emissions Standards)

69
37 New Health Care ONET-SOCs

• 13-1199.02 Patient Representatives
• 19-3039.01 Neuropsychologists and Clinical
• Neuropsychologists
• 21-1019.01 Genetic Counselors
• 29-1069.01 Allergists and Immunologists
• 29-1069.02 Dermatologists
• 29-1069.03 Hospitalists
• 29-1069.04 Naturopathic Physicians
• 29-1069.05 Neurologists
• 29-1069.06 Nuclear Medicine Physicians
• 29-1069.07 Ophthalmologists
• 29-1069.08 Pathologists
• 29-1069.09 Physical Medicine and Rehabilitation
• Physicians
• 29-1069.10 Preventive Medicine Physicians
• 29-1069.11 Radiologists
• 29-1069.12 Sports Medicine Physicians
• 29-1069.13 Urologists
• 29-1129.01 Low Vision Therapists, Orientation and
  Mobility Specialists, and Vision
  Rehabilitation Therapists

• 29-1199.05 Clinical Nurse Specialists
• 29-1199.06 Critical Care Nurses
• 29-1199.07 Nurse Anesthetists
• 29-1199.08 Nurse Practitioners
• 29-2099.01 Cytogenetic Technologists
• 29-2099.02 Cytotechnologists
• 29-2099.03 Electroneurodiagnostic
  Technologists
• 29-2099.04 Hearing Instrument Specialists
• 29-2099.05 Histotechnologists and Histologic
  Technicians
• 29-2099.06 Ophthalmic Medical Technologists
  and Technicians
• 29-2099.07 Orthoptists
• 29-2099.08 Nurse Midwives
• 29-9099.02 Midwives
• 31-9099.01 Anesthesiologist Assistants
• 31-9099.02 Endoscopy Technicians
• 31-9099.03 Speech-language Pathology Assistants

70
Greening of the World of Work

• Investigated the implications for the ONET
  System
• - Current ONET-SOC Taxonomy
• - N E Occupations
• Green Economy
• economic activity related to reducing the use
  of fossil fuels, decreasing pollution and
  greenhouse gas emissions, increasing the
  efficiency of energy usage, recycling materials,
  and developing and adopting renewable sources of
  energy.

71
Green Economy Sectors

• Renewable Energy Generation
• Transportation
• Energy Efficiency
• Green Construction
• Energy Trading
• Energy and Carbon Capture
• Research, Design, and Consulting Services
• Environment Protection
• Agriculture and Forestry
• Manufacturing
• Recycling and Waste Reduction
• Governmental and Regulatory Administration

72
Greening of Occupations

• The extent to which green economy activities and
  technologies increase the demand for existing
  occupations, shape the work and worker
  requirements needed for occupational performance,
  or generate unique work and worker requirements

73
Greening of Occupations (cont.)

• Green Increased Demand Occupations
• increase in the employment demand for an existing
  occupation
• changes in work context
• few if any significant changes in work (tasks)
  and worker requirements of the occupation
• Green Enhanced Skills Occupations
• significant changes in work and worker
  requirements
• essential purposes of the occupation remain the
  same, but tasks, skills, knowledge, and external
  elements, such as credentials, have changed
• may or may not result in an increase in
  employment demand for the occupation
• Green New Emerging Occupations
• impact of green economy activities and
  technologies creates unique work and worker
  requirements, which results in the generation of
  a new occupation relative to the ONET taxonomy.
• The new occupation could be new or born from an
  existing occupation

74
ONET Green Results

• Green Increased Demand Occupations
• 64 ONET-SOC occupations
• Geological and Petroleum Technicians Locomotive
  Engineers Architectural Drafters Chemists
  Natural Science Mangers Agricultural Inspectors
• Green Enhanced Skills Occupations
• 60 ONET-SOC occupations
• Power Plant Operators Electrical Engineers
  Heating and Air Conditioner Mechanics and
  Installers Roofers Nuclear Engineers
  Construction Managers Farmers and Ranchers
  Hazardous Materials Handlers

75
ONET Green Results (cont.)

• Green New Emerging Occupations
• 91 N E Occupations (13 waitlisted)
• Logistic Engineers, Fuel Cell Engineers, Energy
  Auditors, Precision Agriculture Technicians,
  Photonics Engineers, Robotics Technicians,
  Manufacturing Engineering Technologists
• Wind Turbine or Farm Engineers, Wind Turbine
  Service Technicians, Biofuels Plant Operators,
  Solar Power Plant Technicians, Solar Sales
  Representatives/Assessors, Weatherization
  Technicians/Installers, Carbon Credit Traders

76
Detailed Work Activities (DWAs)

• Detailed job behaviors required across multiple
  occupations
• More detailed and more specific to a finer set of
  occupations than Generalized Work Activities
  (GWAs)
• Linked to and organized by GWAs
• Less specific than unique occupation tasks
• 2000 statements
• 30,000 linkages

77
Original DWA Development

• 2000 to 2002
• Original statements developed to help clients
  perform skills matching
• Oregon State
• Classification of Instructional Programs, OES
  data, DOT data
• Transactional data from employers in Oregon
• Statements linked to ONET occupations, new
  statements added to increase coverage, increase
  consistency, reduce redundancy
• Labor Exchange Skills Project sponsored by DOL
• Rational review by occupational analysts
• Further refinement and enhancement of statements
• National Center for ONET Development
• Rational review by occupational analysts

78
Current DWA Project

• Develop new DWAs statements with direct linkages
  to tasks statements and GWAs
• Occupational analyst rating project
• Builds on previous database
• Identify new Green and Healthcare related DWAs
• Populate the 2010 ONET-SOC taxonomy
• ONET New and Emerging occupations
• Other new occupations and changes

79
Spanish Translations of ONET Questionnaires

• Now available along with the previously available
  generic, customizable versions in English
• Can be used as a starting point to collect
  occupational data in support of a wide range of
  economic/workforce investment activities and
  human resource management functions
• http//www.onetcenter.org/questionnaires.html

80
ONET Toolkit for Business

• Information of the features of ONET and its many
  uses for human resource professionals and
  businesses
• On-screen and print version
• http//www.onetcenter.org/toolkit.html

81
ONET Products Tools
82
ONET Products Tools

• Where Can ONET Products Tools be found?
• ONET Resource Center (www.onetcenter.org)
• Databases
• Classification Crosswalks
• About ONET ONET Content Model
• Career Exploration Tools
• Incorporated within Private, Not-for-Profit, and
  Government tools and systems

• Toolkit for Business
• Questionnaires
• Research Technical Reports
• Links to Related Sites

83
ONET Products Tools

• ONET Database (www.onetcenter.org)
• Core Database
• Supplemental Files (e.g., lay titles, DWAs,
  crosswalks)
• Production versus Development
• ONET OnLine (www.onetonline.org)
• Variety of search options
• Detailed occupation information
• My Next Move (www.mynextmove.org)
• Easy-to-use search and career overviews
• Web-based Interest Profiler
• ONET Code Connector (www.onetcodeconnector.org)
• Occupational coding assistant

84
ONET Products Tools (Cont.)

• ONET Career Exploration Tools
• Interest Profiler
• Work Importance Profiler/Locator
• Ability Profiler
• Training and E-Learning (http//www.onetacademy.co
  m/)
• 60,000 registered participants
• Technical Assistance
• Testing Assessment Guides
• Implementation guidance
• Customer Service
• onet_at_ncmail.net

(www.onetcenter.org)
85
ONET Widespread Use
ONET Downloads Jan 2002 Dec 2010
86
ONET Widespread Use (cont.)
ONET Website Statistics - 2010
87
Who uses ONET?

Job Seekers
Students and Youth
Training Specialists
International
Military
Employers
Educators
Community Development
Career Counselors
HR Professionals
Government Officials and Policy Makers
Researchers
88
Sample of ONET Users

• Manpower
• Microsoft
• American Foundation for the Blind
• Booz, Allan, Hamilton
• IBM
• ACT
• Torque
• Bill and Melinda Gates Foundation
• The Boys and Girls Club of American
• Catholic Community Services
• Community Preservation and Development
  Corporation
• Arizona State University CRESMET Center
• Colorado State University Department of
  Psychology
• Harvard Business School
• Lehigh Carbon Community College
• Temple University
• Seattle Washington Public School
• Army Research Institute
• Federal Reserve Bank of New York

• National Institutes for Health
• Alabama Department of Rehabilitation
• California Employment Development Department
• Connecticut Department of Labor
• U.S. Department of Labor, Employment and Training
  Administration
• Main Department of Labor
• NCESCJob Connector
• State of Montana Human Resources Division
• Texas Labor Market and Career Information
  Department
• USAID
• Cornell University
• Canadian International Education Development
  Company
• E-Career Guidance.Com (Ireland)
• NKOKA (South Africa)
• Technical Education and Skills Development
  Authority (Philippines)
• JNET ( Japan)
• U21 Global (includes 21 Universities in 11
  countries)
• UK Commission for Employment and Skills (United
  Kingdom)

89
Employers Using ONET

• Human Resources Personnel
• Business Forecasters
• Industry Analysts
• Organizational Consultants
• Workforce and Economic Development Specialists
• Curriculum Developers
• Researchers

90
Individuals Using ONET

• Career exploration
• Career development
• Job search
• Employment transitions

91

• Department of Labor Employment Training
  Administration
• mySkills myFuture
• Americas Career InfoNet and CareerOneStop
  E-Tools
• Foreign Labor Certification
• Apprenticeship

92

• One-Stop Partners
• Career Counselors
• Interviewers
• Rehabilitation Counselors
• Veterans Representatives
• Training Providers
• Business Consultants

93
Questions, Feedback, Additional
Input? www.onetcenter.orgonline.onetcenter.org
orCustomer Service National Center for ONET
Developmente-mail onet_at_ncmail.net