In 2024, midsize companies spent the largest amount of time on training per employee, totaling roughly ** hours. Larger companies in the United States ********* their investment in staff training between 2017 and 2020, however these investments in training time have been ********** since then. The training industry in the United States Workplace training is the process of educating staff in the specific skills they need to perform the tasks required for their role. This can be developed and provided by in-house staff or by third-party training providers. Companies generally prefer to retain a high level of in-house control though, with fully outsourced solutions for most training services being rare and unlikely to increase in the future. This means the majority of expenditure within the industry is directed to the payment of wages for in-house staff. Training methods and expenditure The recent decrease in training hours provided by smaller companies still allowed for increased expenditure per employee. Moreover, spending per employee decreases in line with company size. This trend likely reflects the greater capacity that larger companies have to invest in large scale and/or technological training solutions able to serve a large number of employees simultaneously. For example, technological solutions such as online learning tools, once implemented, can provide training for a small or large number of employees at a similar overall cost. This hypothesis seems to be reflected in how large organizations make more use of virtual classrooms and less use of instructor-led classrooms as the sole method of training than small and midsize organizations.

Workplace learning and development spending per employee has seen fluctuations over the years, with a notable decrease in 2022. Despite this recent dip, the overall trend shows a commitment to employee growth, with spending reaching ***** U.S. dollars per worker in 2023. This investment in human capital reflects the growing importance of continuous learning in today's rapidly evolving work environment. Adapting to new technologies As companies navigate the integration of artificial intelligence into their operations, learning and development strategies are evolving. In 2023, U.S. companies planned to invest in online courses as a primary method for AI training, while also valuing face-to-face training and live events. This balanced approach to learning reflects the complex nature of new technologies and the need for diverse training methods. Interestingly, by 2024, AI had become a significant tool in human resources, with ** percent of HR professionals reporting its use in recruiting, interviewing, and hiring processes. (1413448, 1500122) Measuring impact and optimizing resources Organizations are increasingly focused on measuring the impact of their learning and development initiatives. In 2023, L&D professionals identified performance reviews as the most useful method for assessing the impact on overall business performance, followed by employee productivity metrics. This emphasis on measurable outcomes aligns with the need to optimize training expenditures, especially in light of fluctuations in corporate training budgets. For instance, U.S. corporate training expenditure decreased by almost **** billion U.S. dollars in 2024 compared to the previous year, highlighting the importance of efficient and effective learning strategies. (1472187, 788521)

This statistic shows the training and development days per employee trained in the United Kingdom (UK) in 2017, by size of establishment. Statistically, the larger the number of employees that an establishment had, the less time that was invested in each trained employee.

This statistic shows the average cost per learning hour used for learning and development (L&D) at organizations worldwide between 2010 and 2017. During the 2017 survey, each hour of direct learning used by employees cost an average of ** U.S. dollars.

This statistic shows the average direct learning expenditure per employee by organizations worldwide in 2017, broken down by industry. During the survey, companies in the management consulting industry reported the highest average expenditure at ***** U.S. dollars per employee.

Peru PE: Firms Offering Formal Training: % of Firms data was reported at 65.900 % in 2017. This records an increase from the previous number of 60.100 % for 2010. Peru PE: Firms Offering Formal Training: % of Firms data is updated yearly, averaging 60.100 % from Dec 2006 (Median) to 2017, with 3 observations. The data reached an all-time high of 65.900 % in 2017 and a record low of 57.700 % in 2006. Peru PE: Firms Offering Formal Training: % of Firms data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Peru – Table PE.World Bank: Company Statistics. Firms offering formal training are the percentage of firms offering formal training programs for their permanent, full-time employees.; ; World Bank, Enterprise Surveys (http://www.enterprisesurveys.org/).; Unweighted average;

Average expenditures (x 1,000) on specific innovation activities, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Innovation activities include research and experimental development; acquisition or development of advanced technology; design activities related to other organizations; employee training specifically for innovation projects; consultation activities with external experts or internal workgroups; activities related to the development and implementation of new marketing methods; market preparation activities directly linked to the introduction of new goods or services; and other innovation activities. Estimates refer to fiscal year 2017 (end date falling after January 1, 2017 and on or before December 31, 2017).

Argentina AR: Firms Offering Formal Training: % of Firms data was reported at 40.200 % in 2017. This records a decrease from the previous number of 63.600 % for 2010. Argentina AR: Firms Offering Formal Training: % of Firms data is updated yearly, averaging 52.100 % from Dec 2006 (Median) to 2017, with 3 observations. The data reached an all-time high of 63.600 % in 2010 and a record low of 40.200 % in 2017. Argentina AR: Firms Offering Formal Training: % of Firms data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Argentina – Table AR.World Bank.WDI: Company Statistics. Firms offering formal training are the percentage of firms offering formal training programs for their permanent, full-time employees.;World Bank, Enterprise Surveys (http://www.enterprisesurveys.org/).;Unweighted average;

This statistic shows the average adjusted number of employees per learning and development (L&D) staff member at organizations worldwide between 2010 and 2017. During the 2017 survey, there was an average of *** employees per L&D staff member.

Djibouti DJ: Share of Youth Not in Education, Employment or Training: Female: % of Female Youth Population data was reported at 27.979 % in 2017. Djibouti DJ: Share of Youth Not in Education, Employment or Training: Female: % of Female Youth Population data is updated yearly, averaging 27.979 % from Dec 2017 (Median) to 2017, with 1 observations. The data reached an all-time high of 27.979 % in 2017 and a record low of 27.979 % in 2017. Djibouti DJ: Share of Youth Not in Education, Employment or Training: Female: % of Female Youth Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Djibouti – Table DJ.World Bank.WDI: Employment and Unemployment. Share of youth not in education, employment or training (NEET) is the proportion of young people who are not in education, employment, or training to the population of the corresponding age group: youth (ages 15 to 24); persons ages 15 to 29; or both age groups.;International Labour Organization. “Labour Force Statistics database (LFS)” ILOSTAT. Accessed January 07, 2025. https://ilostat.ilo.org/data/.;Weighted average;

Labour force survey (LFS) Purpose and short description The Labour Force Survey (LFS) is a household sample survey, conducted throughout the year. It is based on the responses of approximately 110,000 persons aged 15-89. Its main objective is to classify the population of 15-89 years into three groups (employed, unemployed and inactive persons on the labous market) and to provide descriptive and explanatory data on every category. This survey is also carried out in the other EU Member States and is coordinated by Eurostat, the statistical office of the European Union. In Belgium, the LFS is organised by Statbel. The objective is to obtain comparable information at European level, in particular as regards employment and unemployment rates as defined by the International Labour Office (ILO), but also to collect and disseminate data that are otherwise not available, for example about the mobility of workers, the reasons for working part-time, the various forms of part-time employment, the occupation, the educational level of the working age population, ... . Survey population Members of private households aged 15-89. Sample frame Demographic data from the National Register. Data collection method and sample size Data are collected through face-to-face interviews for the first wave of the survey. Since 2017, there have been three (shorter) follow-up waves to which households respond online or by telephone. Households with only inactive persons older than 64 can also be interviewed by telephone. Every year, around 34,000 households take part in this survey. Response rate On average, the response rate in the first wave of the survey is around 68% and in the follow-up waves between 90% and 95%. Periodicity Quarterly Release calendar Results availability: around 3 months after the end of the reference period. Forms Labour Force Survey 2025 (PDF, 1 Mb) Definitions regarding employment and unemployment The survey is harmonised at European level. The definitions regarding employment and unemployment that are mentioned are those of the International Labour Office (ILO) to allow international comparison. People with a job (employed people) comprise all people who during the reference week performed some work ‘for wage or salary’ or ‘for profit’ regardless of the duration (even if this was only one hour), or who had a job but were temporarily absent. For example, one can be temporarily absent for holidays, illness, technical or economic reasons (temporary unemployment),.... Family workers are also included in the category ‘employed’. Since 2021, people who have been temporarily unemployed for an uninterrupted period of more than three months are counted as unemployed or inactive, and no longer as employed. The unemployed comprise all people who: (a) during the reference week were without work, i.e. were not in paid employment or self-employment; (b) were available for work, i.e. were available for paid employment or self-employment within two weeks after the reference week; (c) were actively seeking work, i.e. had taken specific steps during the last four weeks including the reference week to seek paid employment or self-employment, or who had found a job to start within a maximum period of three months. Please note: The ILO unemployment figures are unrelated to any possible registration with the VDAB, Actiris, FOREM or the ADG, or to the receipt of unemployment benefits from ONEM (National Employment Office). As a result, they cannot be compared with administrative unemployment figures. The labour force is made up of the employed and the unemployed. The economically inactive population comprises all people who were not considered as employed or unemployed. The employment rate represents employed persons as a percentage of the same age population. The employment rate as part of the Europe 2020 Strategy represents the share of persons employed in the population aged 20 to 64. The unemployment rate represents the share of unemployed people in the labour force (employed + unemployed) within a given age group. The economic activity rate represents the share of the labour force (employed + unemployed) in the total population within a given age group. The above indicators (employment rate, unemployment rate and economic activity rate) are the most important indicators for international comparisons of the labour market evolution. Low-skilled people are people who have at best a lower secondary education diploma. Medium-skilled people have obtained an upper secondary education diploma, but no higher education diploma. High-skilled people have a higher education diploma. Metadata Employment, unemployment, labour market (NL-FR) Labour force survey (LFS) (NL-FR) Survey methodology Modifications to the Labour Force Survey (LFS) in 2021 LFS: Methodological improvements to the Labour Force Survey 2017 (PDF, 99 Kb) LFS: Presentation of the survey until 2016 (NL-FR) LFS: Presentation of the survey from 2017 (NL-FR) Note on the occasion

Filtered data on the academy code of Montpellier A11 and Toulouse A16

This information is based on data collected as part of the national data collection operation on the professional integration of Master’s graduates.

_Data on 2020 graduates can be explored on the [MESR] website (https://data.enseignementsup-recherche.gouv.fr/pages/insertion_professionnelle_master/) _

2 new indicators were added for the 2020 session:

Employment rate: share of employed graduates among all active (employment or research) or inactive graduates Employment rate in France: share of graduates in paid employment in France among all active (employment or research) or inactive graduates The insertion rate, communicated for several years, does not take into account the inactive.

This investigation was conducted

• in December 2022, 18 and 30 months after graduation, among the Master’s graduates of the 2020 session;
• in December 2021, 18 and 30 months after graduation, among the Master’s graduates of the 2019 session;
• in December 2020, 18 and 30 months after graduation, among the Master’s graduates of the 2018 session;
• in December 2019, 18 and 30 months after graduation, among the Master’s graduates of the 2017 session;
• in December 2018, 18 and 30 months after graduation, among the Master’s graduates of the 2016 session;

• in December 2017, 18 and 30 months after graduation, among the Master’s graduates of the 2015 session;

• in December 2016, 18 and 30 months after graduation, among the Master’s graduates of the 2014 session;

• in December 2015, 18 and 30 months after graduation, among the Master’s graduates of the 2013 session;

• in December 2014, 18 and 30 months after graduation, among the Master’s graduates of the 2012 session;

• in December 2013, 30 months after graduation, among the Master’s graduates of the 2011 session;

• in December 2012, 30 months after graduation, among the Master's graduates of the 2010 session.

The insertion rate is defined as the percentage of graduates in any job out of all graduates in the labour market. It is calculated on graduates of French nationality, from initial training, who entered the labour market immediately and permanently after graduation in 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019 or 2020.

The information collected on the salary relates to the net salary, including bonuses. The wages displayed correspond to the median values on full-time jobs. On the basis of these values, an annual gross salary is estimated, on the basis of a flat rate of change from net to gross of 1.3 (average data on private sector salaries).

The survey was carried out by universities under a charter whose provisions aim to ensure comparability of results between institutions. The overall coordination and operation of the survey is the responsibility of the Ministry of Higher Education and Research.

Additional data sources:

% of graduate scholarship holders: observed data on the population of the labour market integration survey.

Regional unemployment rate: INSEE - 4th quarter 2012 for the session 2010, 4th quarter 2013 for the session 2011, 4th quarter 2014 for the session 2012, 4th quarter 2015 for the session 2013, 1st quarter 2017 for the session 2014, 4th quarter 2017 for the session 2015, 4th quarter 2018 for the session 2016, 4th quarter 2019 for the session 2017, 4th quarter 2020 for the session 2018, 4th quarter 2021 for the session 2019, 4th quarter 2022 for the session 2020.

Regional median monthly net salary: INSEE DADS 2010 for the session 2010, INSEE DADS 2011 for the session 2011, INSEE DADS 2012 for the session 2012, INSEE DADS 2013 for the session 2013, INSEE DADS 2014 for the session 2014, INSEE DADS 2015 for the session 2015, INSEE DADS 2016 for the session 2016, INSEE DADS 2017 for the session 2017, INSEE DADS 2018 for the session 2018, INSEE DADS 2019 for the session 2019, INSEE DADS 2020 for the session 2020 for 25-29 year olds employed full time in the socio-professional categories "Frames and higher intellectual professions" and "Intermediate professions.

Legend: nd = not available (no respondents) ns = not significant (number of respondents less than 30).

Source: 18- and 30-month job placement survey of university graduates 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019 and 2020 and 30-month job placement survey of university graduates 2010 and 2011

Collection: survey carried out by universities, treatments and synthesis carried out by MESR-SIES

Field: graduates of Master 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019 and 2020 from the universities of metropolitan France and the French overseas departments (excluding Paris-Dauphine and Gustave Eiffel University (for 2020 graduates)), of French nationality, from initial training, immediately and permanently entered the labour market after obtaining their diploma.

Introduction: In 2017, approximately 295,000 women died during and immediately following pregnancy and childbirth worldwide, with 94% of these deaths occurring in low-resource settings. The Dominican Republic (DR) exhibits one of the highest maternal mortality ratios in the region of Latin America and the Caribbean despite the fact that 99% of registered births in the country are reportedly attended by a skilled birth attendant. This paradox implies that programs to support healthcare worker knowledge and skills improvement are vital to improving maternal health outcomes in the DR. Helping Mothers Survive (HMS) is a provider training program developed by Jhpiego and global partners. The goal of HMS is to combat maternal mortality by contributing to quality improvement efforts that reinforce maternal health skills of local healthcare workers.Methods: An international, multisectoral group of stakeholders collaborated in the implementation of two HMS curricula, Bleeding After Birth (BAB) and pre-eclampsia & eclampsia (PE&E). Demographic information as well as pre- and post-training knowledge scores were recorded for each participant. Knowledge score improvement was assessed in order to support effectiveness of the program on knowledge acquisition of healthcare workers.Results: Three hundred and twenty healthcare workers participated in the HMS training workshops between October 2016–August 2020. Of the 320 participants, 132 were trained as master trainers. The majority of participants identified as attending physicians, followed by residents/interns, nurses, students, and “other.” A significant improvement in knowledge scores was observed for both the BAB and PE&E curricula, with a 21.24 and 30.25% change in average score (pre- to post-test), respectively. In response to COVID-19 pandemic restrictions, flexibility of the local team led to a PE&E virtual training pilot workshop in August 2020.Discussion/Conclusions: Simulation-based training improved the knowledge levels of healthcare workers for both HMS curricula. These results suggest that simulation-based workshops have an impact on knowledge acquisition and skills of healthcare workers immediately following training. For the PE&E curriculum, no significant difference in knowledge acquisition was observed between in-person and virtual training sessions. The ongoing pandemic poses challenges to program implementation; however, these preliminary results provide evidence that conducting virtual workshops may be a viable alternative to in-person training.

This statistic depicts the ratio of HR-expense-to-FTE in the United States in 2015 and 2017. During the 2017 survey, respondents reported an average HR-expense-to-FTE ratio of ***** U.S. dollars. The HR-expense-to-FTE ratio represents the amount of human resource dollars spent per full-time-equivalent employee in the organization.

Bolivia BO: Firms Offering Formal Training: % of Firms data was reported at 49.900 % in 2017. This records a decrease from the previous number of 57.100 % for 2010. Bolivia BO: Firms Offering Formal Training: % of Firms data is updated yearly, averaging 53.900 % from Dec 2006 (Median) to 2017, with 3 observations. The data reached an all-time high of 57.100 % in 2010 and a record low of 49.900 % in 2017. Bolivia BO: Firms Offering Formal Training: % of Firms data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bolivia – Table BO.World Bank.WDI: Company Statistics. Firms offering formal training are the percentage of firms offering formal training programs for their permanent, full-time employees.;World Bank, Enterprise Surveys (http://www.enterprisesurveys.org/).;Unweighted average;

Georgia GE: Share of Youth Not in Education, Employment or Training: Total: % of Youth Population data was reported at 24.758 % in 2017. This records a decrease from the previous number of 26.815 % for 2016. Georgia GE: Share of Youth Not in Education, Employment or Training: Total: % of Youth Population data is updated yearly, averaging 28.104 % from Dec 2012 (Median) to 2017, with 6 observations. The data reached an all-time high of 32.562 % in 2012 and a record low of 24.758 % in 2017. Georgia GE: Share of Youth Not in Education, Employment or Training: Total: % of Youth Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Georgia – Table GE.World Bank.WDI: Employment and Unemployment. Share of youth not in education, employment or training (NEET) is the proportion of young people who are not in education, employment, or training to the population of the corresponding age group: youth (ages 15 to 24); persons ages 15 to 29; or both age groups.; ; International Labour Organization, ILOSTAT database. Data retrieved in April 2019.; Weighted average;

This statistic shows the average percentage of direct learning expenditure by organizations worldwide for external services in 2017, broken down by company size. During the survey, companies with over 10,000 employees spent an average of **** percent of their direct learning expenditure on external services.

Sweden SE: Share of Youth Not in Education, Employment or Training: Total: % of Youth Population data was reported at 6.150 % in 2017. This records a decrease from the previous number of 6.490 % for 2016. Sweden SE: Share of Youth Not in Education, Employment or Training: Total: % of Youth Population data is updated yearly, averaging 7.530 % from Dec 2003 (Median) to 2017, with 15 observations. The data reached an all-time high of 14.170 % in 2005 and a record low of 6.150 % in 2017. Sweden SE: Share of Youth Not in Education, Employment or Training: Total: % of Youth Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sweden – Table SE.World Bank.WDI: Employment and Unemployment. Share of youth not in education, employment or training (NEET) is the proportion of young people who are not in education, employment, or training to the population of the corresponding age group: youth (ages 15 to 24); persons ages 15 to 29; or both age groups.; ; International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average;

This statistic shows the average percentage of direct learning expenditure by organizations worldwide for tuition reimbursement in 2017, broken down by company size. During the survey, companies with over 10,000 employees spent an average of 11.5 percent of their direct learning expenditure on tuition reimbursement.

Uruguay UY: Firms Offering Formal Training: % of Firms data was reported at 53.300 % in 2017. This records an increase from the previous number of 48.600 % for 2010. Uruguay UY: Firms Offering Formal Training: % of Firms data is updated yearly, averaging 48.600 % from Dec 2006 (Median) to 2017, with 3 observations. The data reached an all-time high of 53.300 % in 2017 and a record low of 24.500 % in 2006. Uruguay UY: Firms Offering Formal Training: % of Firms data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Uruguay – Table UY.World Bank: Company Statistics. Firms offering formal training are the percentage of firms offering formal training programs for their permanent, full-time employees.; ; World Bank, Enterprise Surveys (http://www.enterprisesurveys.org/).; Unweighted average;