Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.
Statistisk sentralbyrå Postboks 2633 St. Hanshaugen 0131 Oslo
Norway
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
9 March 2026
2.2. Metadata last posted
9 March 2026
2.3. Metadata last update
9 March 2026
3.1. Data description
Data on the Information and Communication Technologies (ICT) usage and e-commerce in enterprises are survey data. They are collected by the National Statistical Institutes or Ministries and are in principle based on Eurostat's annual model questionnaires on ICT usage and e-commerce in enterprises.
The legal basis for ICT enterprise statistics for survey year 2025 is Commission Implementing Regulation (EU) 2024/1883 of 9 July 2024 laying down the technical specifications of data requirements for the topic 'ICT usage and e-commerce' for the reference year 2025. Large part of the data collected is used to support measuring the implementation and monitoring of the EU’s digital targets for 2030, set by the Digital Decade Policy Programme.
Four of the key performance indicators (KPIs) of the current programme stem from the statistics for which the implementing and delegated acts are enclosed for adoption: Artificial Intelligence, cloud, data analytics and the digital intensity index (DII) - a composite indicator reflecting the digital transformation of business
The aim of the European survey on ICT usage and e-commerce in enterprises is to collect and disseminate harmonised and comparable information at European level.
Name of data collection
Data collection on ICT usage and e-commerce in enterprises 2025
Name in Norwegian: Bruk av IKT i næringslivet 2025
Click on the hyperlink below for more information about the statistics:
All economic activities in the scope of Annex of the Commission Regulation are intended to be included in the general survey, covering enterprises with 10 or more employees and self-employed persons. These activities are:
Section C - “Manufacturing”
Section D, E - “Electricity, gas, steam and air conditioning supply”, “Water supply, sewerage, waste management and remediation activities”
Section F - “Construction”
Section G - “Wholesale and retail trade; repair of motor vehicles and motorcycles”
Section H - “Transportation and storage”
Section I - “Accommodation and food service activities”
Section J - “Information and communication”
Section L - “Real estate activities”
Section M - “Professional, scientific and technical activities”
Section N - "Administrative and support service activities"
Group 95.1 - “Repair of computers and communication equipment”.
For micro-enterprises see the sub-concepts in the full metadata view.
3.3.1. Coverage-sector economic activity for micro-enterprises - All NACE categories are covered
Micro-enterprises are not included in the survey
3.3.2. Coverage sector economic activity for micro-enterprises - If not all activities were covered, which ones were covered?
Not applicable
3.4. Statistical concepts and definitions
The model questionnaire on ICT usage and e-commerce in enterprises provides a large variety of variables covering among others the following topics:
Access and use of the Internet
E-commerce sales
Data utilisation and analytics
Use of cloud computing services
Artificial intelligence
ICT and the environment.
The annual model questionnaires and the European businesses statistics compliers’ manual for ICT usage and e-commerce in enterprises comprise definitions and explanations regarding the topics of the survey.
As required by Annex of the Commission Implementing Regulation, enterprises with 10 or more employees and self-employed persons are covered by the survey.
For micro-enterprises see the sub-concepts below.
3.6.1. Coverage of micro-enterprises
No
3.6.2. Breakdown between size classes [0 to 1] and [2 to 9]
No
3.6.3. If for micro-enterprises different size delimitation was used, please indicate it.
Not applicable
3.7. Reference area
All the territory of the mainland country was included in the population. In other words, the survey covered all the counties in Norway. The islands Svalbard, Bjørnøya and Jan Mayen were not included. Neither was the Continental shelf included. The percentage of the target population not covered was 0.05. Data for a specific set of variables will be delivered on NUTS 2 regional level.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“.
Percentages of enterprises, Percentages of turnover, Percentages of employees and self-employed persons, Million euro (for selected indicators in some countries).
Where not specified the reference period is current situation (survey period in 2025). Year 2024 for the value or % of sales data and where specified.
6.1. Institutional Mandate - legal acts and other agreements
THE EUROPEAN COMMISSION,
Having regard to the Treaty on the Functioning of the European Union, Having regard to Regulation (EU) 2019/2152 of the European Parliament and of the Council of 27 November 2019 on European business statistics, repealing 10 legal acts in the field of business statistics (OJ L 327, 17.12.2019, p.1.), and in particular Article 7(1) and Article 17(6) thereof,
Whereas:
The topic ‘Information and Communication Technologies (“ICT”) usage and e-commerce’ provides data required by the Digital Decade Policy Programme to monitor the Union’s digital targets for 2030, such as the Digital Intensity Indicator for the digital transformation of businesses or the take-up of cloud computing services, big data (data analytics) or artificial intelligence. It also provides information for various other Union policies related to digital performance among which ‘A Europe fit for the digital age’ policy.
In order to allow to assess the quality of the data and to ensure that data on ICT usage and e-commerce are comparable and harmonised, metadata and quality reports are required to be provided before the data are released.
The measures provided for in this Regulation are in accordance with the opinion of the European Statistical System Committee,
HAS ADOPTED THIS REGULATION:
Article 1
For the topic ‘ICT usage and e-commerce’, as referred to in Annex I to Regulation (EU) 2019/2152, Member States shall transmit to the Commission (Eurostat) the data for the reference year 2025 in accordance with the Annex to this Regulation.
Article 2
The annual metadata report for the topic ‘ICT usage and e-commerce’ for the reference year 2025 shall be transmitted to the Commission (Eurostat) by 31 May 2025.
The annual quality report for the topic ‘ICT usage and e-commerce’ for the reference year 2025 shall be transmitted to the Commission (Eurostat) by 5 November 2025.
Article 3
This Regulation shall enter into force on the twentieth day following that of its publication in the Official Journal of the European Union.
Complementary national legislation constituting the legal basis for the survey on the use of ICT in enterprises: Link to the Norwegian Statistics Act: Statistikkloven
6.2. Institutional Mandate - data sharing
Statistics Norway (SSB) operates under the Official Statistics Act (Statistikkloven), which establishes the legal framework for sharing data for statistical purposes. The Act defines the conditions for granting access to data for the production of official statistics (§13), for statistical analyses and research (§14), and for the release of anonymous information (§15), while requiring strict confidentiality safeguards (§7). These rules also apply when data are shared with foreign statistical authorities, including other National Statistical Institutes (NSIs). Official Statistics Act: Lov om offisiell statistikk (Statistikkloven)[lovdata.no]
SSB’s internal Guidelines for Access to Data describe in detail what types of data may be shared, who may receive them, the required application procedures, rules for data minimization, obligations for secure handling, and the special procedures used when data are transferred to institutions abroad. They also outline standardized protocols for data linkage and confidentiality protection. Guidelines: Retningslinjer for tilgang til data fra SSB (PDF)[ssb.no]
SSB is also subject to a government-issued Main Instruction, which assigns the agency formal responsibility for international statistical cooperation. This includes collaboration and data exchange with Eurostat and other NSIs, ensuring methodological harmonization, adherence to international standards, and secure and coordinated international data flows. Main Instruction: Hovedinstruks for Statistisk sentralbyrå (PDF)[regjeringen.no]
In practice, SSB shares data through standardized international reporting systems (e.g., Eurostat deliveries), common statistical programs, and harmonized data formats. Publicly available datasets—including aggregated tables in the Statistics Bank and machine-readable API services—are accessible to foreign NSIs. For more sensitive microdata intended for research cooperation, platforms such as microdata.no provide secure, controlled access, with built-in confidentiality safeguards like minimum population requirements and statistical protection rules. Data sharing overview & tools:
Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4)) of 11 March 2009 (OJ L 87, p. 164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.
At national level:
Statistics Norway adheres to strict confidentiality rules: data must not be published in a way that allows identification of individuals or other statistical units. While exceptions may occur, no information shall be disclosed to the unreasonable detriment of any unit.
In line with European legislation, the international Code of Practice, and §7 of the Norwegian Statistics Act, all dissemination of official statistics must safeguard against traceability to identifiable entities.
To ensure compliance, Statistics Norway has established detailed procedures (see section 7.2) to prevent unauthorized disclosure, whether direct or indirect, of any economic entity or statistical unit.
7.2. Confidentiality - data treatment
Data are transmitted via eDamis (encrypted) and delivered to a secure environment where they are treated. Flags are added for confidentiality in case results must not be disclosed.
At national level:
As a general rule, data on groups with fewer than three units, or those dominated by one or two units, are not published. This has not posed challenges for national dissemination. To protect confidentiality, Statistics Norway applies measures and methods such as: Coarser categorization, Suppression: sensitive values are hidden and replaced with a colon. Additional values may be secondarily suppressed to prevent back-calculation. Perturbation: values are slightly altered using techniques like rounding or noise addition. Before transmitting data to Eurostat, any such breakdowns are flagged with C in the CONF_STATUS field of the final dataset. Related variables in the annex for standard error calculations are also flagged accordingly. These breakdowns are excluded from publication due to confidentiality concerns.
8.1. Release calendar
There is a release calendar for the national publishing. The calendar was updated in second quarter 2025 and it is publicly accessible. The release date for the ICT ENT 2025 was September 24th 2025
Statistics Norway ensures that no external users have access to statistics or analyses before they are officially published. All data is released simultaneously to the public at 8:00 AM on the statistics web site. To maintain transparency, the release schedule is announced at least three months in advance via the NSI statistics release calendar.
The organisation’s approach to communication and dissemination is guided by five core principles: Transparency, Accessibility, Comprehensibility, Independence, and Confidentiality.
Results for selected variables collected in the framework of this survey are available for all participating countries on Digital economy and society of Eurostat website.
The European businesses statistics compilers’ manual for ICT usage and e-commerce in enterprises provides guidelines and clarifications for the implementation of the surveys.
At national level:
The primary methodological reference for this survey is the European Business Statistics Compilers’ Manual for ICT Usage and E-commerce in Enterprises, provided by Eurostat. For detailed information on national statistics, including metadata, methodology, and summary, please refer to the section titled "About the statistics" via the following link: ICT usage in enterprises (ssb.no).
10.6.1. Metadata completeness - rate
Not requested
10.7. Quality management - documentation
Please see the description of quality management in section 11.2 Quality management - assessment
11.1. Quality assurance
The European businesses statistics compliers’ manual for ICT usage and e-commerce in enterprises provides guidelines and standards for the implementation of the surveys. It is updated every year according to the changed contents of the model questionnaires.
According to the letter of allocation, Statistics Norway shall oversee the monitoring of compliance with the requirements for quality in official statistics and establish a system for following this up. The statistics programme identifies 12 producers of statistics, all of which are involved in the quality assurance work. In consultation with the Committee for Official Statistics, Statistics Norway shall establish a quality system in the first half of 2021 to ensure that work on quality assurance can start in the second half of the year. An initial report on the quality of official statistics shall be submitted to the Ministry in the first half of 2022.
This memo describes a proposal for a quality system for official statistics. The system consists of four general elements:
A framework for the quality of official statistics consisting of the Statistics Act and the European Statistics Code of Practice. This is described in Section 3.
Methods and tools for measuring the quality of official statistics. Section 4 gives an assessment of established methods and tools, how these can be incorporated into a quality system, and what new methods need to be developed and applied.
Systems and processes for following up quality. Section 5 describes how the different elements of the system will interact and how quality can be assessed and followed up consistently.
Actors and their roles. Section 6 examines the responsibilities and roles of the different actors in the quality system for official statistics.
For more information, please click on the link to the documentation below:
At European level, the recommended use of the annual Eurostat model questionnaire aims at improving comparability of the results among the countries that conduct the survey on ICT usage and e-commerce in enterprises. Moreover, the European businesses statistics compilers’ manual for ICT usage and e-commerce in enterprises provides guidelines and clarifications for the implementation of the surveys.
At national level:
Official statistics of Statistics Norway are produced using a number of statistical methods. Statistics Norway has a department that supports the use of these and in some areas also further develops and researches methods.
Questionnaire methodology and user testing: Questionnaire methodology includes a number of different methods that are used iteratively. The field of study is based on a number of other academic disciplines such as social anthropology, psychology, linguistics and philosophy. The cognitive perspective on the response process is central to our work, and can be divided into four iterative phases: interpretation of meaning, retrieval of information required, assessment of information, and the selection of an answer. Our methods for user testing include: expert evaluation, focus groups, cognitive mapping, eye tracking and usability testing.
Sampling design: A sample survey is conducted when it is too extensive to ask the entire population. Sampling design is the planning of which units are to be included in such a survey. This includes analysing the population that is the basis for the sample, calculating sample sizes and determining the sampling method.
Data integration: Data integration is to combine data from different data sources, with the aim of producing new data sets that are the basis for statistics or research.
Data editing: Data editing is the control, scrutiny and correction of data. It includes editing of population, editing of obvious and systematic errors, selection of values with large deviations and high influence and control of aggregates to be published. The methods used for data editing range from logical control of valid value range to imputation of values with machine learning.
Estimation and weighting: Estimation is to find value for a population figure based on the information we have collected from the (sample) survey. We are usually interested in several figures - totals, averages, proportions and variances are most common - for several variables. Estimation often means that each unit in the sample is assigned a weight, this is almost always done for personal and household surveys. We can also base the estimation on a statistical model, which is common in business surveys.
Seasonal adjustment: Seasonal adjustment is to use statistical methods to remove systematic seasonal variations from a monthly or quarterly time series, so that the time series to the greatest possible extent expresses the real development over time. In addition, they try to remove the calendar effects that vary from year to year, such as Easter. When the data has been corrected for the seasonal conditions, one will be left with a clearer picture of the underlying development in the time series which consists of trend / cycle and irregular component.
Confidentiality: The Statistics Act § 7. Statistical confidentiality in the dissemination of official statistics requires that Statistics Norway does not publish statistics in a manner that allows statistical information to be traced back to individuals or other types of statistical units. Confidentiality can be ensured by using coarser categories, by suppression (hiding values) or by perturbation (changing values). Examples of coarser categories are counties instead of municipalities and age groups of five years instead of single years. Suppression means that some values are not published and are instead replaced by a colon. In addition to the values one wishes to protect via suppression, several other values in the table must be so-called secondary suppressed to prevent the possibility of recalculation from other published values (aggregates). When applying perturbation, the published value may deviate from the real value. Several methods can be used, including rounding and noise addition.
For more comprehensive information about overall assessment of the national methodology for quality management, please click on the links below:
At European level, European Commission users (e.g. DG CNECT, DG GROW, DG JUST, DG REGIO, DG JRC) are the principal users of the data on ICT usage and e-commerce in enterprises and contribute in identifying/defining the topics to be covered. Hence, main users are consulted regularly (at hearings, task forces, ad hoc meetings) for their needs and are involved in the process of the development of the model questionnaires at a very early stage.
User needs are considered throughout the whole discussion process of the model questionnaires aiming at providing relevant statistical data for monitoring and benchmarking of European policies.
National level :
Eurostat is an important user of the statistics. Ministries, Innovation Norway, Norwegian Digitalisation Agency, business organisations, research institutes, the media and international organisations such as OECD, UNCTAD are also main users of the statistics.
12.2. Relevance - User Satisfaction
European level :
At European level, contacts within the Commission, the OECD and other stakeholders give a clear picture about the key users' satisfaction as to the following data quality aspects: accuracy and reliability of results, timeliness, satisfactory accessibility, clarity and comparability over time and between countries, completeness and relevance. Overall users have evaluated positively (good, very good) the data quality on the ICT usage and e-commerce in enterprises.
National level :
Not available
12.3. Completeness
All mandatory and optional questions were included in the national questionnaire.
All the questions relating to the regional data will be provided on NUTS 2 level.
No deviation from questions/items in model questionnaire.
Micro-enterprises are not included in the national survey.
Turnover data and Total purchase data was collected from the last version of SBS. Employment and economic activity are collected from administrative register data.
Additional questions included in the national survey: "Use of government authorities’ data" (6 questions), and the optional questions relating to Web purchases 2024 also included.
Detailed information is available in “ Annex I. Completeness “ - related to questionnaire, coverage, additional questions, regional data.
Comments on reliability and representativeness of results and completeness of dataset
The overall accuracy of the dataset is assessed as high, based on a combination of methodological design, response rates, and sampling error estimates. The national survey is carefully designed to ensure coverage and consistency across the target population. A key strength of the dataset is the high unit-response rate, which ensures broad participation among eligible units. Additionally, the survey’s structure requires completion of all mandatory items before submission, resulting in a high item-response rate and a dataset with minimal missing information. These factors contribute significantly to the reliability, representativeness, and completeness of the results.
The comments reflect overall standard errors reported for the indicators and breakdowns in section 13.2.1 (Sampling error - indicators) and the rest of the breakdowns for national and European aggregates, as well as other accuracy measurements. The estimated standard error should not exceed 2pp for the overall proportions and should not exceed 5pp for the proportions related to the different subgroups of the population (for those NACE aggregates for the calculation and dissemination of national aggregates). If problems were found, these could have implications for future surveys (e.g. need to improve sampling design, to increase sample sizes, to increase the response rates).
Standard errors for the main indicators are well within acceptable thresholds. None of the selected indicators exceed 2 percentage points for overall proportions, and most subgroup estimates remain below 5 percentage points. However, some indicators do exceed 5 percentage points for some small subgroups. This is due to the implementation of new NACE breakdowns in 2021, several industries (activities) that were previously grouped together have been reorganized into separate, stand-alone categories. (See also section 18.1 B.) As a result, some of these new breakdowns consist of relatively few units in the target population, which has led to certain indicators having a standard error exceeding 5%. In 2025, there were no units in the target population corresponding to breakdown C19. Consequently, data for C19 is not available. Flagging has been carried out in accordance with Eurostat’s recommended criteria. Despite this, Statistics Norway (NSI) considers the published data and results to be accurate, reliable, and representative. Importantly, no single breakdown consistently shows high standard errors across all indicators. The occurrence of high standard errors in small subgroups is typically due to the limited number of units in the population. NSI has encountered similar issues with small groups prior to the implementation of the new NACE breakdowns. It is also worth noting that each subgroup with elevated standard errors represents less than 2% of the total population.
In summary, the combination of a well-designed survey, high response rates, and acceptable sampling error levels supports a strong assessment of accuracy. The dataset is suitable for dissemination and analysis at both national and European levels.
Detailed information is available in “ Annex II. Accuracy “ - related to European aggregates, comments on reliability and use of flag.
For calculation of the standard error see concept 13.2.1.1.
13.2.1. Sampling error - indicators
Standard error (for selected indicators and breakdowns)
Precision measures related to variability due to sampling, unit non-response (the size of the subset of respondents is smaller than the size of the original sample) and other (imputation for item non-response, calibration etc.) are not (yet) required from the Member States for all indicators.
Detailed information is available in“ Annex III. Sample and standard error tables 2025 “ – worksheets starting with “Standard error".
Various methods can be used for the calculation of the standard error for an estimated proportion. The aim is to incorporate into the standard error the sampling variability but also variability due to unit non-response, item non-response (imputation), calibration etc. In case of census / take-all strata, the aim is to calculate the standard errors comprising the variability due to unit non-response and item non-response.
Name and brief description of the applied estimation approach: Ratio model
Basic formula: yhi = ßhxhi + εhi , i = 1, 2, ..., Nh and var(εhi) = xhiσ2h
Main reference in the literature: Valliant, R., Dorfman, A.H. and Rouall, R.M. (2001). Finite Population Sampling and Inference: A Prediction approach. Wiley, New York.
How has the stratification been taken into account? Please see the detailed descriptions in section 18.1 B) and 18.5
Which strata have been considered? Please see the detailed description in section 18.5
13.3. Non-sampling error
See detailed sections below.
13.3.1. Coverage error
See concept 18.1.1. A) Description of frame population.
13.3.1.1. Over-coverage - rate
Concerning the proportion of units accessible via the frame that do not belong to the target population, the over-coverage rate is zero.
13.3.1.2. Common units - proportion
Not requested
13.3.2. Measurement error
No measurement errors were detected
13.3.3. Non response error
See detailed sections below.
13.3.3.1. Unit non-response - rate
See detailed sections below.
13.3.3.1.1. Unit response
The following table contains the number of units (i.e. enterprises), by type of response to the survey and by the percentage of these values in relation to the gross sample size.
Type of response
Enterprises
0-9 (or 2-9) employees and self-employed persons
10 or more employees and self-employed persons
Number
%
Number
%
Gross sample size (as in section 3.1 C)
100%
5617
100%
1. Response (questionnaires returned by the enterprise)
5576
99.27%
1.1 Used for tabulation and grossing up (Net sample or Final Sample; as in section 3.1 D)
5548
98.77%
1.2 Not used for tabulation
28
0.5%
1.2.1 Out of scope (deaths, misclassified originally in the target population, etc.)
0
0
1.2.2 Other reasons (e.g. unusable questionnaire)
28
0.5%
2. Non-response (e.g. non returned mail, returned mail by post office)
41
0.73%
Comments on unit response, if unit response is below 60%
13.3.3.1.2. Methods used for minimizing unit non-response
Alongside the web survey, respondents received an electronic notification containing key information about the survey, including the deadline and the legal consequences of non-response. If the initial deadline passes without submission, a warning is issued along with a new deadline. Should the survey still remain unsubmitted after the extended deadline, a compulsory fine is imposed. This fine continues to accrue until the survey is submitted or the maximum enforcement limit is reached.
Throughout the data collection period, the ICT ENT team was available to assist respondents with any questions related to the survey. In certain cases, the responsible statistician also sent additional reminders to key units. Unit non-response has not been a significant issue.
In previous years, over 98% of enterprises responded to the survey.
13.3.3.1.3. Methods used for unit non-response treatment
1. No treatment for unit non-response
X
2.1 Treatment by re-weighting: Re-weighting by the sampling design strata considering that non-response is ignorable inside each stratum (the naïve model)
2.2 Treatment by re-weighting: Re-weighting by identified response homogeneity groups (created using sample-level information)
2.3 Treatment by re-weighting: Re-weighting through calibration/post-stratification (performed using population information) by the groups used for calibration/post-stratification
3. Treatment by imputation (done distinctly for each variable/item)
4. Method(s) and the model(s) corresponding to the above or other method(s) used for the treatment of unit non-response. (e.g. Re-weighting using Horvitz-Thompson estimator, ratio estimator or regression estimator, auxiliary variables)
13.3.3.1.4. Assessment of unit non-response bias
More than 98% unit response rate. No need for assessment.
13.3.3.2. Item non-response - rate
There is no issue concerns the item non-responses, as most items in the national survey are mandatory and it enforces the respondents to complete survey before allowing submission.
13.3.3.2.1. Methods used for item non-response treatment
1. No treatment for item non-response
X
2. Deductive imputation An exact value can be derived as a known function of other characteristics.
3. Deterministic imputation (e.g. mean/median, mean/median by class, ratio-based, regression-based, single donor nearest-neighbour) Deterministic imputation leads to estimators with no random component, that is, if the imputation were to be re-conducted, the outcome would be the same.
4. Random imputation (e.g. hot-deck, cold-deck) Random imputation leads to estimators with a random component, that is, if the imputation were re-conducted, it would have led to a different result.
5. Re-weighting
6. Multiple imputation In multiple imputation each missing value is replaced (instead of a single value) with a set of plausible values that represent the uncertainty of the right value to impute. Multiple imputation methods offer the possibility of deriving variance estimators by taking imputation into account. The incorporation of imputation into the variance can be easily derived based on variability of estimates among the multiply imputed data sets.
7. Method(s) and the model(s) corresponding to the above or other method(s) used for the treatment of item non-response.
13.3.3.2.2. Questions or items with item response rates below 90% and other comments
Other comments relating to the item non-response
Additional issues concerning "item non-response" calculation (e.g. method used in national publications): Not available
Questions and items with low response rates (cut-off value is 90%) and item non-response rate: Not applicable
13.3.4. Processing error
No processing errors were detected.
13.3.5. Model assumption error
Not requested
14.1. Timeliness
See detailed sections below.
14.1.1. Time lag - first result
Not applicable
14.1.2. Time lag - final result
Data are to be delivered to Eurostat in the fourth quarter of the reference year (due date for the finalised dataset is 5th October). European results are released before the end of the survey year or in the beginning of the year following the survey year (T=reference year, T+0 for indicators referring to the current year, T+12 months for other indicators referring to the previous year e.g. e-commerce). The finalised dataset was delivered to Eurostat on 24th October 2025.
At national level:
Results were released at national level on 25th September 2025, with time lag T+0 for indicators referring to the current year, T+12 months for other indicators referring to the previous year.
14.2. Punctuality
See detailed section in the full metadata view.
14.2.1. Punctuality - delivery and publication
Data were delivered to Eurostat on 23 September 2025; 13 days before the deadline.
15.1. Comparability - geographical
The model questionnaire is generally used by the countries that conduct the survey on ICT usage and e-commerce in enterprises. Due to (small) differences in translation, in the used survey vehicle, in non-response treatment or different routing through the questionnaire, some results for some countries may be of reduced comparability. In these cases, notes are added in the data.
Detailed information on differences in the wording of the questions in the national questionnaires is available in “ Annex I. Completeness “ - worksheets related to questionnaire, coverage, additional questions.
Comparability between regions:
Data for specific set of variables were delivered on NUTS 2 regional level. There is no problem of comparability across the country’s regions.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“ – worksheets related to regional data.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable
15.2. Comparability - over time
See detailed section in the full metadata view.
15.2.1. Length of comparable time series
The length of comparable time series depends on the module and the variable considered within each survey module. Additional information is available in annexes attached to the European metadata.
The changes for the fixed modules/variables from previous years are considered small and should not impact the comparability over time of results delivered to Eurostat.
15.3. Coherence - cross domain
Not applicable
15.3.1. Coherence - sub annual and annual statistics
Not applicable
15.3.2. Coherence - National Accounts
Not applicable
15.4. Coherence - internal
Not applicable
Restricted from publication
17.1. Data revision - policy
Statistics Norway’s Data Revision Policy outlines the overarching principles and procedures for revising published statistics. Data revisions are a normal and necessary part of producing high‑quality official statistics. Revisions can be planned, e.g. due to new or improved data sources, methodological changes, new classifications, or seasonal adjustment updates, or they may occur when comparing short‑term statistics with annual data. The policy follows international standards, including the European Code of Practice (CoP) and the Quality Assurance Framework (QAF). SSB emphasizes transparency: users must be informed about why revisions occur, when preliminary figures will be updated, and the size and reason for adjustments. Major methodological changes must be communicated in advance. Revisions are categorized as:
Regular revisions: e.g., publishing final figures after preliminary estimates or seasonal adjustments.
Non‑regular revisions: e.g., major revisions to national accounts or specific statistics.
SSB also conducts regular revision analyses to continuously improve statistical quality and discusses revisions with users as part of its quality assurance process.
Once received, the data are reviewed and edited using dedicated tools and software by the responsible statistician at NSI. For further details, please refer to section 18.4
17.2.1. Data revision - average size
Not requested
18.1. Source data
A) Frame population description and distribution
For more information see concept 18.1.1.
B) Sampling design - Sampling method
Description of the sampling method used (e.g. stratified random sample, quota sampling, cluster sampling; one-stage or two-stage sampling) and information which variables were used to stratify, the categories of those variables, in particular for the NACE Rev. 2 categories related to the "possible calculation of European aggregates", and the final number of strata:
The sample is a stratified random sample. It was drawn from all legal units with at least ten employees and self-employed persons in the Central Register of Establishments and Units. It was stratified by industry and size of the units measured by employment.
Due to the implementation of new NACE breakdowns in 2021, several industries that were belonged to the same breakdown-group earlier have been subdivided into own stand-alone-groups. Some of these industries consist of relatively few units in their population. This was not an issue under the former classification before 2021 (due to these were belonged to the breakdowns that other industries also are included in the breakdowns) regarding to draw the sample, but since these small industries needed to be broken down into separate groups, hence, there was a need to modify the draw probabilities for these groups. The NSI have therefore examined the target population to identify which industries that have few units regarding the criterion for representative sample. Most of the industries have satisfying units in their population. However, there is an industry that has no unit (in-scope), and a couple industries have less than 20 units in the population. Therefore the NSI have modified the draw probabilities for the industries that have few units, before the stratified random sample. The modification was done in collaboration with experts from the methodological division in SSB.
The standardized draw probabilities (DP):
DP1. Applies to the NACE-groups with less than 20 employees and self-employed persons in the population: 100%, i.e. full count
DP2. Applies to the NACE-groups with 20-999 employees and self-employed persons in the population: Among units with 10-19 employees and self-employed persons the sample was 20 per cent, among units with 20-49 employees and self-employed persons the sample was 30 per cent, among units with 50-99 employees and self-employed persons the sample was 50 per cent, among units with 100-249 employees and self-employed persons the sample was 75 per cent and among units with at least 250 employees and self-employed persons all units were included in the sample.
DP3. Applies to the NACE-groups with 1000 or more employees and self-employed persons in the population: Among units with 10-19 employees and self-employed persons the sample was 7.5 per cent, among units with 20-49 employees and self-employed persons the sample was 15 per cent, among units with 50-99 employees and self-employed persons the sample was 50 per cent, among units with 100-249 employees and self-employed persons the sample was 75 per cent and among units with at least 250 employees and self-employed persons all units were included in the sample. The difference between DP2. and DP3. is that there are lower draw probabilities for the employment sized 10-19 and 20-49 in DP3. compared with DP2.
C) Gross sample distribution
Detailed information is available in “ Annex III. Sample and standard error tables 2025 “ (Worksheet: GROSS SAMPLE)
D) Net sample distribution
Detailed information is available in “ Annex III. Sample and standard error tables 2025 “ (Worksheet: NET SAMPLE)
18.1.1. Source data - frame population
A) Description of frame population
a) When was the sample for the ICT usage and e-commerce in enterprise survey drawn?
January 2025
b) Last update of the Business register that was used for drawing the sample of enterprises for the survey:
January 2025
c) Indication if the frame population is the same as, or is in some way coordinated with, the one used for the Structural Business Statistics (different snapshots):
SBS used a later snapshot. Otherwise, same definition of frame population
d) Description if different frames are used during different stages of the statistical process (e.g. frame used for sampling vs. frame used for grossing up):
The same frame was used for sampling and grossing up
e) Indication the shortcomings in terms of timeliness (e.g. time lag between last update of the sampling frame and the moment of the actual sampling), geographical coverage, coverage of different subpopulations, data available etc., and any measures taken to correct it, for this survey.
No additional known shortcomings.
B) Frame population distribution
Detailed information is available in “ Annex III. Sample and standard error tables 2025 “ (Worksheet: FRAME POPULATION)
18.2. Frequency of data collection
Annual
18.3. Data collection
See detailed sections below.
Survey Data Collection and Implementation Process:
The data for the survey was collected through a stand-alone web-based questionnaire. The model questionnaire was thoroughly translated into Norwegian by the responsible statistician, in collaboration with the Division for Methods at the National Statistical Institute (NSI). This translation process aimed to ensure that the questions were clearly worded and easy to understand, minimizing the risk of misinterpretation. Translation began in Q3 2024. Following the translation, the survey was programmed by developers from the Division for Enterprise Surveys. The programming was based on a technical specification provided by the responsible statistician, ensuring that the survey included both mandatory and optional questions, appropriate filtering logic, and technical functionalities such as automated validation checks, explanatory notes, and other user support features. The survey underwent thorough testing by multiple experts to ensure it was free of errors and technical issues.
The survey was sent out 28 February 2025. Respondents received an electronic information letter notifying them that the survey was available in the Altinn portal. The letter included details about the deadline and the consequences of non-response. If the initial deadline was missed, a reminder was sent along with a new deadline approximately ten days later. Failure to respond by the extended deadline resulted in the imposition of a compulsory fine. Throughout the data collection period, NSI provided support to respondents for any questions related to the survey. Turnover data and Total purchase was sourced from the latest version of the Structural Business Statistics (SBS). Employment and economic activity data were retrieved from administrative registers.
18.3.1. Survey period
Survey / Collection
Date of sending out questionnaires
Date of reception of the last questionnaire treated
General survey
28 February 2025
30 May 2025
Micro-enterprises
Not applicable
Not applicable
18.3.2. Survey vehicle – general survey
General survey - Stand-alone survey
18.3.3. Survey vehicle – micro-enterprises
Not applicable
18.3.4. Survey type
Self-administered web questionnaire.
The web survey was distributed through Altinn, which is an internet portal for digital dialogue between businesses, private individuals and public agencies. Altinn is also a technical platform that government bodies can use to develop digital services.
18.3.5. Survey participation
Mandatory
18.4. Data validation
The server-based validation tool embedded in EDAMIS4, provided by Eurostat, was used to validate the dataset. Due to the inclusion of the optional Web-purchase and regional data in SDMX format, Statistics Norway (NSI) conducted pre-testing via the EDAMIS Acceptance Portal prior to transmission. No actual validation errors were identified during testing—only a single type-related issue caused by the absence of one activity, which was due to the lack of units in the target population.
In addition to the automated validation, NSI performed thorough checks of both microdata and aggregated data, including regional breakdowns, at the enterprise level and across NACE classifications. Questionable units or missing variables were reviewed, and enterprises were contacted when necessary to confirm the accuracy of the submitted information. To ensure high-quality raw data, NSI invested significant effort in the design of the national survey. Most questions were mandatory, and technical controls were implemented to minimize non-response and illogical answers.
Microdata were reviewed using NSI’s internal revision tool, ISEE (Integrated System for Editing of Data), along with other software-based tools. Aggregated results were compared with nationally published figures, including year-to-year checks, prior to final submission. No imputation was performed for missing numerical values, and there was no treatment for unit non-response.
The validation report received from EDAMIS4 after transmission confirmed that no validation errors were present. On 23 September 2025, NSI received a notification from EDAMIS4 confirming the results of the year-to-year (Y2Y) indicator checks. NSI reviewed the microdata and the editing tools used to construct the variables and found no indication of errors related to measurement, survey design, or data collection. All observed changes were attributed to natural causes. A formal confirmation of the accuracy and reliability of the results was sent to Eurostat on 25 September 2025, and Eurostat confirmed that there is no need for further check of indicators day after. Errors were discovered in the coding of some Web-purchase variables in the transmission format on October 21. The finalized dataset, including correction of coding errors, was transferred to Eurostat on October 24.
18.5. Data compilation
Grossing-up procedures
The collected survey data has been weighted (grossed up) to ensure that the sample accurately reflects the characteristics of the target population. The primary objective of the weighting process is to adjust the sample so that it corresponds as closely as possible to the full population in terms of key variables.
Weights were calculated based on the relationship between the sample and the population within each stratum, taking into account any imbalances due to non-response. The grossing-up procedure was carried out in collaboration with the Methodology Division at Statistics Norway, as in previous years.
Stratification was based on two dimensions:
Enterprise size, divided into five employment groups: 10–19, 20–49, 50–99, 100–249, and 250+ employees and self-employed persons.
Industry classification, using 32 NACE Rev. 2 groups as specified by Eurostat.
This resulted in a total of 160 strata (32 industry groups × 5 size groups), aligned with the NACE breakdown outlined in the draft Commission Regulation (EU) concerning the transmission of data for the topic “ICT usage and e-commerce” for reference year 2025, in accordance with the EC Regulation.
The 32 NACE groups:
Group 1 = NACE 10-12 Group 2 = NACE 13-15 Group 3 = NACE 16-18 Group 4 = NACE 19 (zero unit in the targeted population) Group 5 = NACE 20 Group 6 = NACE 21 Group 7 = NACE 22-23 Group 8 = NACE 24-25 Group 9 = NACE 26 Group 10 = NACE 27 Group 11 = NACE 28 Group 12 = NACE 29-30 Group 13 = NACE 31-33 Group 14 = NACE 35 Group 15 = NACE 36-39 Group 16 = NACE 41-43 Group 17 = NACE 45 Group 18 = NACE 46 Group 19 = NACE 47 Group 20 = NACE 49-53 Group 21 = NACE 55 Group 22 = NACE 56 Group 23 = NACE 58-60 Group 24 = NACE 61 Group 25 = NACE 62-63 Group 26 = NACE 68 Group 27 = NACE 69-71 Group 28 = NACE 72 Group 29 = NACE 73-75 Group 30 = NACE 77-78 + 80-82 Group 31= NACE 79 Group 32= NACE 95.1
The weighted data represents the total number of units, turnover, and employment in the population.
18.5.1. Imputation - rate
Imputation was not used.
18.6. Adjustment
Not applicable
18.6.1. Seasonal adjustment
Not applicable
Problems encountered and lessons to be learnt:
No comment.
19.1. Documents
Questionnaire in national language
Bruk av IKT i næringslivet 2025
Questionnaire in English (if available)
ICT ENT 2025 survey in English
National reports on methodology (if available)
Information on methodology can be found in this website ICT usage in enterprises – SSB (please see "About the statistics")
Analysis of key results, backed up by tables and graphs in English (if available)
Data on the Information and Communication Technologies (ICT) usage and e-commerce in enterprises are survey data. They are collected by the National Statistical Institutes or Ministries and are in principle based on Eurostat's annual model questionnaires on ICT usage and e-commerce in enterprises.
The legal basis for ICT enterprise statistics for survey year 2025 is Commission Implementing Regulation (EU) 2024/1883 of 9 July 2024 laying down the technical specifications of data requirements for the topic 'ICT usage and e-commerce' for the reference year 2025. Large part of the data collected is used to support measuring the implementation and monitoring of the EU’s digital targets for 2030, set by the Digital Decade Policy Programme.
Four of the key performance indicators (KPIs) of the current programme stem from the statistics for which the implementing and delegated acts are enclosed for adoption: Artificial Intelligence, cloud, data analytics and the digital intensity index (DII) - a composite indicator reflecting the digital transformation of business
The aim of the European survey on ICT usage and e-commerce in enterprises is to collect and disseminate harmonised and comparable information at European level.
Name of data collection
Data collection on ICT usage and e-commerce in enterprises 2025
Name in Norwegian: Bruk av IKT i næringslivet 2025
Click on the hyperlink below for more information about the statistics:
The model questionnaire on ICT usage and e-commerce in enterprises provides a large variety of variables covering among others the following topics:
Access and use of the Internet
E-commerce sales
Data utilisation and analytics
Use of cloud computing services
Artificial intelligence
ICT and the environment.
The annual model questionnaires and the European businesses statistics compliers’ manual for ICT usage and e-commerce in enterprises comprise definitions and explanations regarding the topics of the survey.
As required by Annex of the Commission Implementing Regulation, enterprises with 10 or more employees and self-employed persons are covered by the survey.
For micro-enterprises see the sub-concepts below.
All the territory of the mainland country was included in the population. In other words, the survey covered all the counties in Norway. The islands Svalbard, Bjørnøya and Jan Mayen were not included. Neither was the Continental shelf included. The percentage of the target population not covered was 0.05. Data for a specific set of variables will be delivered on NUTS 2 regional level.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“.
Where not specified the reference period is current situation (survey period in 2025). Year 2024 for the value or % of sales data and where specified.
Comments on reliability and representativeness of results and completeness of dataset
The overall accuracy of the dataset is assessed as high, based on a combination of methodological design, response rates, and sampling error estimates. The national survey is carefully designed to ensure coverage and consistency across the target population. A key strength of the dataset is the high unit-response rate, which ensures broad participation among eligible units. Additionally, the survey’s structure requires completion of all mandatory items before submission, resulting in a high item-response rate and a dataset with minimal missing information. These factors contribute significantly to the reliability, representativeness, and completeness of the results.
The comments reflect overall standard errors reported for the indicators and breakdowns in section 13.2.1 (Sampling error - indicators) and the rest of the breakdowns for national and European aggregates, as well as other accuracy measurements. The estimated standard error should not exceed 2pp for the overall proportions and should not exceed 5pp for the proportions related to the different subgroups of the population (for those NACE aggregates for the calculation and dissemination of national aggregates). If problems were found, these could have implications for future surveys (e.g. need to improve sampling design, to increase sample sizes, to increase the response rates).
Standard errors for the main indicators are well within acceptable thresholds. None of the selected indicators exceed 2 percentage points for overall proportions, and most subgroup estimates remain below 5 percentage points. However, some indicators do exceed 5 percentage points for some small subgroups. This is due to the implementation of new NACE breakdowns in 2021, several industries (activities) that were previously grouped together have been reorganized into separate, stand-alone categories. (See also section 18.1 B.) As a result, some of these new breakdowns consist of relatively few units in the target population, which has led to certain indicators having a standard error exceeding 5%. In 2025, there were no units in the target population corresponding to breakdown C19. Consequently, data for C19 is not available. Flagging has been carried out in accordance with Eurostat’s recommended criteria. Despite this, Statistics Norway (NSI) considers the published data and results to be accurate, reliable, and representative. Importantly, no single breakdown consistently shows high standard errors across all indicators. The occurrence of high standard errors in small subgroups is typically due to the limited number of units in the population. NSI has encountered similar issues with small groups prior to the implementation of the new NACE breakdowns. It is also worth noting that each subgroup with elevated standard errors represents less than 2% of the total population.
In summary, the combination of a well-designed survey, high response rates, and acceptable sampling error levels supports a strong assessment of accuracy. The dataset is suitable for dissemination and analysis at both national and European levels.
Detailed information is available in “ Annex II. Accuracy “ - related to European aggregates, comments on reliability and use of flag.
Percentages of enterprises, Percentages of turnover, Percentages of employees and self-employed persons, Million euro (for selected indicators in some countries).
Grossing-up procedures
The collected survey data has been weighted (grossed up) to ensure that the sample accurately reflects the characteristics of the target population. The primary objective of the weighting process is to adjust the sample so that it corresponds as closely as possible to the full population in terms of key variables.
Weights were calculated based on the relationship between the sample and the population within each stratum, taking into account any imbalances due to non-response. The grossing-up procedure was carried out in collaboration with the Methodology Division at Statistics Norway, as in previous years.
Stratification was based on two dimensions:
Enterprise size, divided into five employment groups: 10–19, 20–49, 50–99, 100–249, and 250+ employees and self-employed persons.
Industry classification, using 32 NACE Rev. 2 groups as specified by Eurostat.
This resulted in a total of 160 strata (32 industry groups × 5 size groups), aligned with the NACE breakdown outlined in the draft Commission Regulation (EU) concerning the transmission of data for the topic “ICT usage and e-commerce” for reference year 2025, in accordance with the EC Regulation.
The 32 NACE groups:
Group 1 = NACE 10-12 Group 2 = NACE 13-15 Group 3 = NACE 16-18 Group 4 = NACE 19 (zero unit in the targeted population) Group 5 = NACE 20 Group 6 = NACE 21 Group 7 = NACE 22-23 Group 8 = NACE 24-25 Group 9 = NACE 26 Group 10 = NACE 27 Group 11 = NACE 28 Group 12 = NACE 29-30 Group 13 = NACE 31-33 Group 14 = NACE 35 Group 15 = NACE 36-39 Group 16 = NACE 41-43 Group 17 = NACE 45 Group 18 = NACE 46 Group 19 = NACE 47 Group 20 = NACE 49-53 Group 21 = NACE 55 Group 22 = NACE 56 Group 23 = NACE 58-60 Group 24 = NACE 61 Group 25 = NACE 62-63 Group 26 = NACE 68 Group 27 = NACE 69-71 Group 28 = NACE 72 Group 29 = NACE 73-75 Group 30 = NACE 77-78 + 80-82 Group 31= NACE 79 Group 32= NACE 95.1
The weighted data represents the total number of units, turnover, and employment in the population.
A) Frame population description and distribution
For more information see concept 18.1.1.
B) Sampling design - Sampling method
Description of the sampling method used (e.g. stratified random sample, quota sampling, cluster sampling; one-stage or two-stage sampling) and information which variables were used to stratify, the categories of those variables, in particular for the NACE Rev. 2 categories related to the "possible calculation of European aggregates", and the final number of strata:
The sample is a stratified random sample. It was drawn from all legal units with at least ten employees and self-employed persons in the Central Register of Establishments and Units. It was stratified by industry and size of the units measured by employment.
Due to the implementation of new NACE breakdowns in 2021, several industries that were belonged to the same breakdown-group earlier have been subdivided into own stand-alone-groups. Some of these industries consist of relatively few units in their population. This was not an issue under the former classification before 2021 (due to these were belonged to the breakdowns that other industries also are included in the breakdowns) regarding to draw the sample, but since these small industries needed to be broken down into separate groups, hence, there was a need to modify the draw probabilities for these groups. The NSI have therefore examined the target population to identify which industries that have few units regarding the criterion for representative sample. Most of the industries have satisfying units in their population. However, there is an industry that has no unit (in-scope), and a couple industries have less than 20 units in the population. Therefore the NSI have modified the draw probabilities for the industries that have few units, before the stratified random sample. The modification was done in collaboration with experts from the methodological division in SSB.
The standardized draw probabilities (DP):
DP1. Applies to the NACE-groups with less than 20 employees and self-employed persons in the population: 100%, i.e. full count
DP2. Applies to the NACE-groups with 20-999 employees and self-employed persons in the population: Among units with 10-19 employees and self-employed persons the sample was 20 per cent, among units with 20-49 employees and self-employed persons the sample was 30 per cent, among units with 50-99 employees and self-employed persons the sample was 50 per cent, among units with 100-249 employees and self-employed persons the sample was 75 per cent and among units with at least 250 employees and self-employed persons all units were included in the sample.
DP3. Applies to the NACE-groups with 1000 or more employees and self-employed persons in the population: Among units with 10-19 employees and self-employed persons the sample was 7.5 per cent, among units with 20-49 employees and self-employed persons the sample was 15 per cent, among units with 50-99 employees and self-employed persons the sample was 50 per cent, among units with 100-249 employees and self-employed persons the sample was 75 per cent and among units with at least 250 employees and self-employed persons all units were included in the sample. The difference between DP2. and DP3. is that there are lower draw probabilities for the employment sized 10-19 and 20-49 in DP3. compared with DP2.
C) Gross sample distribution
Detailed information is available in “ Annex III. Sample and standard error tables 2025 “ (Worksheet: GROSS SAMPLE)
D) Net sample distribution
Detailed information is available in “ Annex III. Sample and standard error tables 2025 “ (Worksheet: NET SAMPLE)
Annual
See detailed sections below.
The model questionnaire is generally used by the countries that conduct the survey on ICT usage and e-commerce in enterprises. Due to (small) differences in translation, in the used survey vehicle, in non-response treatment or different routing through the questionnaire, some results for some countries may be of reduced comparability. In these cases, notes are added in the data.
Detailed information on differences in the wording of the questions in the national questionnaires is available in “ Annex I. Completeness “ - worksheets related to questionnaire, coverage, additional questions.
Comparability between regions:
Data for specific set of variables were delivered on NUTS 2 regional level. There is no problem of comparability across the country’s regions.
Detailed information on the provision of data on NUTS 2 regional level is available in “Annex I. Completeness“ – worksheets related to regional data.
