4.3. Business capabilities

Access to, and the ability to use, ICTs are increasingly important for businesses of all sizes. In 2017, on average, around 12% of workers were in occupations involving a high frequency of ICT, underlining the high ICT content of these jobs. Furthermore, many additional jobs involve at least some ICT tasks. The share of workers in ICT-intensive occupations increased in almost all countries from between 2011 to and 2017. In the United Kingdom, the United States and Luxembourg, over 16% of workers are now in ICT-intensive occupations.

New technologies can augment workers’ capabilities. Cloud computing, in particular, is opening up an array of new business processes, by allowing firms, particularly young and small ones, on-demand use and payment for powerful computing services. Almost 30% of businesses in the OECD area reported using cloud services in 2018, up from 22% in 2014. The propensity to use cloud computing varies considerably across countries and sectors, as well as between small and large firms. On average, only 27% of small firms in the OECD area use cloud services, against 39% of medium firms and 55% of large firms.

The declining cost of data storage and processing have facilitated the collection of large volumes of data and the adoption of Big data analytics. On average, 12% of businesses in the countries for which data are available performed Big data analysis in 2018, with this share rising to 22% of businesses in the Netherlands and over 20% in Belgium and Ireland. Although the cloud, and the advent of easier-to-use analytical tools have made Big data analysis more attainable for all firms, large firms are still by far the biggest users of Big data analytics; 33% on average, and over half of large firms in Belgium and the Netherlands analyse Big data. Big data analysis requires access to a sufficiently large pool of data, and large firms are more likely to have such volumes of existing data at their disposal. Meanwhile, small and medium-sized firms are increasingly able to complement their own data with data acquired from other sources.

Exploiting the potential of Big data also requires access to specific skills, in terms of new analytical techniques such as parallel processing or visualisation tools. In many cases, the transition to Big data analytics also requires changes in the organisational practices of both enterprises and institutions, as well as the development of rules for data storage and exchange that comply with data protection rules (e.g. health records). Managers have a key role to play in leading adoption and their knowledge of technologies can be an important factor in businesses’ adoption and effective use of technologies such as cloud services and Big data analytics. For example, in Australia, insufficient knowledge of cloud computing services was found to be the most common factor-limiting uptake, affecting nearly one-in-five businesses (ABS, 2017).

Did You Know?

Almost 30% of OECD businesses reported using cloud services in 2018, with shares ranging from 65% in Finland to around 10% in Mexico, Poland and Turkey.

Definitions

ICT task-intensive occupations have a high propensity to include ICT tasks at work ranging from simple use of the Internet, through use of word processing or spreadsheet software, to programming. ICT task-intensive occupations comprise: business services and administration managers (ISCO occupation 121); sales, marketing and development managers (122); information and communications technology service managers (133); professional services managers (134); physical and earth science professionals (211); electrotechnology engineers (215); architects, planners, surveyors and designers (216); university and higher education teachers (231); finance professionals (241); administration professionals (242); sales, marketing and public relations professionals (243); software and applications developers and analysts (251); and database and network professionals (252); information and communications technology operations and user support (351), (see Grundke et al., forthcoming).

Firm size classes: are defined as small (10-49 persons employed), medium (50-249) and large (250 and more).

Cloud computing refers to ICT services over the Internet to access servers, storage, network components and software applications.

Big data analytics refers to the analysis of vast amounts of data generated by activities carried out electronically and through machine-to-machine communications.

Measurability

The ICT task intensity of jobs is assessed using exploratory factor analysis of responses to 11 items on the OECD Programme for International Assessment of Adult Competencies (PIAAC) survey, which relates to the performance of ICT tasks at work. See Grundke et al., 2017 for the detailed methodology.

Data on cloud services and the use of Big data analytics use are gathered through direct surveys of ICT usage by businesses. The questions used are typically generic and do not elicit details about the specific functionalities, tools or devices that respondents use. Surveys are generally carried out annually but are less frequent in some countries. The OECD actively encourages the collection of comparable information in this field through guidelines in the “Model Survey on ICT Access and Usage by Businesses” (OECD, 2015b).

Workers in ICT task-intensive occupations, 2017
As a percentage of all workers
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Source: OECD calculations based on European Labour Force Surveys, national labour force surveys and other national sources, December 2018. See 1. StatLink contains more data.

1. ICT task-intensive occupations are defined according to the taxonomy described in: Grundke, Horvát and M. Squicciarini (forthcoming), “ICT intensive occupations: A task-based analysis”, OECD Science, Technology and Innovation Working Papers, OECD Publishing, Paris.

ICT task-intensive occupations are defined by three-digit Groups of the 2008 revision of the International Standard Classification of Occupations (ISCO-08): Business services and administration managers (121); Sales, marketing and development managers (122); Information and communications technology service managers (133); Professional services managers (134); Physical and earth science professionals (211); Electrotechnology engineers (215); Architects, planners, surveyors and designers (216); University and higher education teachers (231); Finance professionals (241); Administration professionals (242); Sales, marketing and public relations professionals (243); Software and applications developers and analysts (251); Database and network professionals (252) and Information and communications technology operations and user support (351).

For Canada, data refer to 2016.

For Japan, data refer to 2015.

 StatLink https://doi.org/10.1787/888933929889

Enterprises purchasing cloud computing services, by size, 2018
As a percentage of enterprises in each employment size class
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Source: OECD, ICT Access and Usage by Businesses Database, http://oe.cd/bus, December 2018. See 1.

1. For Australia, data refer to the fiscal year 2015/16 ending 30 June.

For Brazil, data refer to 2017 and comprise an aggregation of four different items collected separately.

For Canada, data refer to 2012 and to enterprises that have made expenditures on software as a service (e.g. cloud computing). Medium-sized enterprises have 50-299 employees. Large enterprises have 300 or more employees.

For Iceland, data refer to 2014.

For Japan, data refer to 2016 and to businesses with 100 or more employees. Medium-sized enterprises have 100-299 employees. Large enterprises have 300 or more employees.

For Korea, data refer to 2015.

For Mexico, data refer to 2012.

For Switzerland, data refer to 2015 and to firms with five or more employees.

 StatLink https://doi.org/10.1787/888933929908

Enterprises performing Big data analysis, by size, 2018
As a percentage of enterprises in each employment size class
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Source: OECD, ICT Access and Usage by Businesses Database, http://oe.cd/bus, December 2018. See 1.

1. For Korea and the United Kingdom, data refer to 2016.

 StatLink https://doi.org/10.1787/888933929927

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