This is not the latest documentation of the statistics.
Innovation: documentation of statistics
16.11.2024 valid documentation
Basic data of the statistics
Data description
Innovation statistics published every second year contain data on the generality and nature, as well as expenditure and structure, of innovation activity of enterprises employing at least ten persons in manufacturing, mining and quarrying and energy and waste management, and some service industries. Innovation activity refers to all developmental, financial and commercial activities undertaken by an enterprise, which aim or lead to innovations – either product innovations or process innovations related to business processes. Research and development activity is considered as innovation activity in its entirety.
In addition to innovation activity, the innovation survey also collects information on enterprises’ knowledge flows and development potential more widely. The survey results are published mainly by industry and enterprise size category.
The survey and statistics are EU harmonised (Community Innovation Survey CIS), and they are carried out and produced in all EU countries. The concepts of the statistics on innovation activity are based on international guidelines and recommendations (OECD, Eurostat).
In addition to innovation activity, the innovation survey also collects information on enterprises’ knowledge flows and development potential more widely. The survey results are published mainly by industry and enterprise size category.
The survey and statistics are EU harmonised (Community Innovation Survey CIS), and they are carried out and produced in all EU countries. The concepts of the statistics on innovation activity are based on international guidelines and recommendations (OECD, Eurostat).
Statistical population
The innovation survey and statistics cover enterprises employing at least ten persons in the industries B-C-D-E-G46-H-J-K-M71-M72-M73 (Standard Industrial Classification 2008). Innovation survey is not carried out for other sectors of economy.
Statistical unit
Starting from the statistical reference year 2022, the statistical unit is an enterprise (an enterprise unit). An enterprise is a unit with decision-making autonomy, which produces goods and/or services to be sold on the market. An enterprise may
comprise one or more legal units. Previously, statistical unit was a legal unit, in some cases a group or a domestic part of a group.
comprise one or more legal units. Previously, statistical unit was a legal unit, in some cases a group or a domestic part of a group.
Unit of measure
Share of enterprises, %
Number of enterprises
EUR thousand (EUR 1,000) or EUR million (EUR million)
Number of enterprises
EUR thousand (EUR 1,000) or EUR million (EUR million)
Turnover share, % of turnover
Reference period
Innovation activity is defined for a three-year period, which is also the research period of the innovation survey. The statistical reference year of the survey and data is the last year of the three-year period. The statistical reference year is always an even year.
The qualitative data of the inquiry are inquired for the whole three-year period, the quantitative data are collected only for the statistical reference year.
The qualitative data of the inquiry are inquired for the whole three-year period, the quantitative data are collected only for the statistical reference year.
Reference area
Information from the survey concern enterprises’ activity in Finland.
Nationally statistics on innovation activity are published only on the level of the whole country. Data on key indicators (such as innovation expenditure other than R&D expenditure, cooperation related to innovation activity, data on the novelty value of product innovations) for small and medium-sized enterprises (10 to 249 employees) are delivered to the EU also on the NUTS2 level.
Sector coverage
Innovation activity is an enterprise survey and statistics that cover enterprises employing at least ten persons in the industries B-C-D-E-G46-H-J-K-M71-M72-M73 (Standard Industrial Classification 2008). The innovation survey is not carried out for other sectors of the economy.
Time coverage
Data on enterprises' innovation activity have been collected since 1991 (piloting the topic 1989), since 1996 regularly at two-year intervals.
The data of the survey are not in all respects as such directly comparable between different survey periods. The lengths of the time series are affected by changes made to concepts and definitions, changes over time in the industrial classification and the coverage of industries in the survey as well as changes in and specifications to how the questions are presented. The contents of the survey also change partially every round (rotating questions or topical subjects for example).
The data of the survey are not in all respects as such directly comparable between different survey periods. The lengths of the time series are affected by changes made to concepts and definitions, changes over time in the industrial classification and the coverage of industries in the survey as well as changes in and specifications to how the questions are presented. The contents of the survey also change partially every round (rotating questions or topical subjects for example).
Frequency of dissemination
The data of the statistics on innovation activity are released every two years (in even years).
Concepts
Extramural research and development
Extramural R&D means R&D projects or services which have been acquired outside of the unit and which from the point of view of the service provider are its intramural R&D. Extramural R&D is characterized by the fact that the developer largely determines the implementation of the project content.
Innovation
A business innovation is a new or improved product or business process (or combination thereof) that differs significantly from the firm's previous products or business processes and that has been introduced on the market or brought into use by the firm.
Innovation activity
Innovation activity includes all developmental, financial and commercial activities, undertaken by a firm, which are intended to or result in an innovation.
Process innovation
A process innovation is a new or improved business process for one or more business functions that differs significantly from the firm’s previous business processes and which has been implemented within the firm.
Process innovations for business processes may be directed at methods for production of goods or services, logistics, delivery or distribution methods, information or communication systems, administration and management including business practices for organising procedures or external relations and methods of organising work responsibility, decision making or human resource management, and at methods of product and business process development.
Process innovations for business processes may be directed at methods for production of goods or services, logistics, delivery or distribution methods, information or communication systems, administration and management including business practices for organising procedures or external relations and methods of organising work responsibility, decision making or human resource management, and at methods of product and business process development.
Product innovation
A product innovation is a new or improved good or service that differs significantly from the firm’s previous goods or services and which has been implemented on the market.
Product innovations include significant changes to the design of products, and digital goods or services.
Product innovations exclude the simple re-sale of new goods, and changes of a solely aesthetic nature
Product innovations include significant changes to the design of products, and digital goods or services.
Product innovations exclude the simple re-sale of new goods, and changes of a solely aesthetic nature
Research and development activity
Research and experimental development (R&D) comprise creative and systematic work undertaken in order to increase the stock of knowledge – including knowledge of humankind, culture and society – and to devise new applications of available knowledge.
The five criteria for identifying R&D:
To be aimed at new findings (novel)
The aim of the R&D is to produce new knowledge and novelties. Mere application of the existing knowledge in development of new solutions, products or procedures is not R&D activity.
To be based on original, not obvious, concepts and hypotheses (creative)
Characteristic to R&D activity is creativity, setting and testing of new hypothesis and concepts. Routine activities in the development of products, processes or other procedures in not R&D activity.
To be uncertain about the final outcome (uncertain)
R&D involves uncertainty regarding outcomes and costs.
To be planned and budgeted (systematic)
R&D is conducted in a planned way, with records kept of both the process followed and the outcome. The purpose of the R&D project and the sources of funding for the R&D performed should be identified. R&D is often organized as a project, but it can also be goal-oriented activity of a person or a group.
To lead to results that could be possibly reproduced (transferable and/or reproducible)
An R&D project should result in the potential for the transfer of the new knowledge which also can be reproduced.
Distribution by type of R&D
Basic research is experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundations of phenomena and observable facts, without any particular application or use in view.
Applied research is original investigation undertaken in order to acquire new knowledge. It is, however, directed primarily towards a specific, practical aim or objective.
Experimental development is systematic work, drawing on knowledge gained from research and practical experience and producing additional knowledge, which is directed to producing new products or processes or to improving existing products or processes.
The five criteria for identifying R&D:
To be aimed at new findings (novel)
The aim of the R&D is to produce new knowledge and novelties. Mere application of the existing knowledge in development of new solutions, products or procedures is not R&D activity.
To be based on original, not obvious, concepts and hypotheses (creative)
Characteristic to R&D activity is creativity, setting and testing of new hypothesis and concepts. Routine activities in the development of products, processes or other procedures in not R&D activity.
To be uncertain about the final outcome (uncertain)
R&D involves uncertainty regarding outcomes and costs.
To be planned and budgeted (systematic)
R&D is conducted in a planned way, with records kept of both the process followed and the outcome. The purpose of the R&D project and the sources of funding for the R&D performed should be identified. R&D is often organized as a project, but it can also be goal-oriented activity of a person or a group.
To lead to results that could be possibly reproduced (transferable and/or reproducible)
An R&D project should result in the potential for the transfer of the new knowledge which also can be reproduced.
Distribution by type of R&D
Basic research is experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundations of phenomena and observable facts, without any particular application or use in view.
Applied research is original investigation undertaken in order to acquire new knowledge. It is, however, directed primarily towards a specific, practical aim or objective.
Experimental development is systematic work, drawing on knowledge gained from research and practical experience and producing additional knowledge, which is directed to producing new products or processes or to improving existing products or processes.
Research and development expenditure
Labour costs of internal R&D personnel
Share of R&D work in annual wages according to R&D person-years. Labour costs include actual wages, fringe benefits in actual value, holiday pay and holiday bonuses. They also include social security payments, contributions to unemployment insurance and compulsory and voluntary pension contributions.
Materials, equipment and other current expenditure
Materials and equipment needed for R&D activities including acquisition of machinery and equipment with operating life at most one year. Other current expenditure includes the share of R&D activity in cost items such as buildings and premises, information technology, travel and administrative costs (also labour costs of administrative and maintenance personnel, which are not included in the R&D wages).
Purchased services
Purchases of services integrated into enterprise's own R&D activities. Services that are produced by external personnel, but which are closely linked to the intramural R&D of an enterprise. They may include software services, consultancy and other planning services, which are not considered as intramural R&D activities from the point of view of the service provider.
Capital costs (acquisition of machinery, equipment, buildings and the like)
Acquisitions which serve R&D only are included in total, in other cases the share of R&D is estimated by the share of use for R&D purposes. Item covers also acquisition of software for R&D activities along with licence fees.
Share of R&D work in annual wages according to R&D person-years. Labour costs include actual wages, fringe benefits in actual value, holiday pay and holiday bonuses. They also include social security payments, contributions to unemployment insurance and compulsory and voluntary pension contributions.
Materials, equipment and other current expenditure
Materials and equipment needed for R&D activities including acquisition of machinery and equipment with operating life at most one year. Other current expenditure includes the share of R&D activity in cost items such as buildings and premises, information technology, travel and administrative costs (also labour costs of administrative and maintenance personnel, which are not included in the R&D wages).
Purchased services
Purchases of services integrated into enterprise's own R&D activities. Services that are produced by external personnel, but which are closely linked to the intramural R&D of an enterprise. They may include software services, consultancy and other planning services, which are not considered as intramural R&D activities from the point of view of the service provider.
Capital costs (acquisition of machinery, equipment, buildings and the like)
Acquisitions which serve R&D only are included in total, in other cases the share of R&D is estimated by the share of use for R&D purposes. Item covers also acquisition of software for R&D activities along with licence fees.
Classifications
Accuracy, reliability and timeliness
Overall accuracy
The main sources of error are measurement errors and non-response.
The accuracy and reliability of the survey results can generally be regarded as good with regard to the survey-specific variables. Based on the sampling design and answers, the possibility of errors is considered limited and no significant challenges have been detected in the interpretation of the questions during the data collection.
The accuracy and reliability of the survey results can generally be regarded as good with regard to the survey-specific variables. Based on the sampling design and answers, the possibility of errors is considered limited and no significant challenges have been detected in the interpretation of the questions during the data collection.
Timeliness
The statistical data of the statistics on innovation activity are published 16 months after the end of the statistical reference year (t+16), the requirement of the EU Regulation is t+18.
Punctuality
The data of the statistics on innovation activity have been published within the planned timetable.
Completeness
The data are available on all legislated or otherwise aggreed indicators by industry and size category according to the EU recommendation. Industry data are presented mainly on the 2-digit level with the exception of industries that for data protection reasons have been aggregated or covered, or a phenomenon is too rare to be presented at a detailed level.
Coverage error
Sample frame t-1, not covering new units in the target population in statistical year t.
No dublicates.
Observed over-coverage by collection round is around one per cent of the number of enterprises in the frame.
No dublicates.
Observed over-coverage by collection round is around one per cent of the number of enterprises in the frame.
Measurement error
Innovation can be defined as a concept only on a general level in connection with the survey. Its interpretation is subjective and depends on the respondent's view. The possibility of measurement error thus exists.
Unit non-response rate / A4
In the latest innovation survey, the response rate has remained under the target level of 70 per cent and unit non-response has grown to over 30 per cent. In the CIS 2022 survey, the unit non-response rate was 36.5 per cent. In the CIS 2022 there were 9,924 enterprises in the frame and 3,984 enterprises in the survey.
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| Industry group | Size category of personnel | Frame | Survey |
Coverage %/ |
Over-coverage | Respondents | Response rate, % |
|---|---|---|---|---|---|---|---|
| All industries | 10-49 | 7,693 | 2,531 | 32.9 | 53 | 1,450 | 58.5 |
| All industries | 50-249 | 1,840 | 1,062 | 57.7 | 12 | 737 | 70.2 |
| All industries | 250 or over | 391 | 391 | 100.0 | 3 | 299 | 77.1 |
| All industries | All enterprises | 9,924 | 3,984 | 40.1 | 78 | 2,486 | 63.5 |
| Manufacturing | 10-49 | 2,980 | 1,034 | 34.7 | 25 | 593 | 58.8 |
| Manufacturing | 50-249 | 875 | 525 | 60.0 | 4 | 372 | 71.4 |
| Manufacturing | 250 or over | 210 | 210 | 100.0 | 1 | 168 | 80.4 |
| Manufacturing | All enteprises | 4,065 | 1,769 | 43.5 | 30 | 1,133 | 65.2 |
| Services | 10-49 | 4,713 | 1,497 | 31.8 | 28 | 857 | 58.3 |
| Services | 50-249 | 965 | 537 | 55.6 | 8 | 365 | 69.0 |
| Services | 250 or over | 181 | 181 | 100 | 2 | 131 | 73.2 |
| Services | All enterprises | 5,859 | 2,215 | 37.8 | 38 | 1,353 | 62.1 |
Item non-response rate / A5
The key variables on the implementation of innovations and innovation activity are obligatory for data providers, which means there is no item non-response either.
In other respects, the item non-response of the data is small.
In other respects, the item non-response of the data is small.
Comparability
Comparability - geographical
The data of the statistics on innovation activity are produced according to Eurostat's recommendations and guidelines and are thus harmonised.
Comparability - over time
Data on enterprises' innovation activity have been collected since 1991 (piloting the topic 1989), since 1996 regularly at two-year intervals.
The data of the survey are not in all respects as such directly comparable between different survey periods. The lengths of the time series are affected by changes made to concepts and definitions, changes over time in the industrial classification and the coverage of industries in the survey as well as changes in and specifications to how the questions are presented. The contents of the survey also change partially every round (rotating questions or topical subjects for example).
Compared to the previous survey CIS 2018, the new themes and topics in the CIS 2020 were the importance of the factors relating to climate change for enterprise's business, the introduction and the implementation of innovations with environmental benefits, and as a national parts of the survey, competence areas required by the enterprises and the effects of corona pandemic.
Starting from the statistical reference year 2022, the statistical unit of the statistics on innovation is enterprise unit.
The adoption of the EU Regulation on European business statistics also includes describing the personnel data of the survey with the size of personnel variable, which covers self-employed persons and part-time and full-time wage and salary earners instead of the previous variable based on the definition of staff-years. The change has an effect on the size category definition of the survey and the number of enterprises in the target group, especially in the smallest enterprise size category.
The changes cause a break in the time series between the statistical reference years 2020 and 2022.
The data of the survey are not in all respects as such directly comparable between different survey periods. The lengths of the time series are affected by changes made to concepts and definitions, changes over time in the industrial classification and the coverage of industries in the survey as well as changes in and specifications to how the questions are presented. The contents of the survey also change partially every round (rotating questions or topical subjects for example).
Compared to the previous survey CIS 2018, the new themes and topics in the CIS 2020 were the importance of the factors relating to climate change for enterprise's business, the introduction and the implementation of innovations with environmental benefits, and as a national parts of the survey, competence areas required by the enterprises and the effects of corona pandemic.
Starting from the statistical reference year 2022, the statistical unit of the statistics on innovation is enterprise unit.
The adoption of the EU Regulation on European business statistics also includes describing the personnel data of the survey with the size of personnel variable, which covers self-employed persons and part-time and full-time wage and salary earners instead of the previous variable based on the definition of staff-years. The change has an effect on the size category definition of the survey and the number of enterprises in the target group, especially in the smallest enterprise size category.
The changes cause a break in the time series between the statistical reference years 2020 and 2022.
Coherence - cross domain
The statistics on innovation activity have a point of contact with the statistics on enterprises' research and development activities, because research and development is included in to innovation activity in its entirety and thus both statistics describe research and development activity and its expenditure. Even though the data collection methods differ from one another (a panel and complementing sample section in the statistics on research and development activity and a sample survey 10–249 and a total survey 250 or over in the innovation survey), R&D expenditure is recorded in a quite uniform manner both on the total level and in comparable industry groups.
Coherence - internal
The R&D expenditure included in the innovation activity data is mainly in line with the expenditure data included in the statistics on research and development. However, there may be individual differences between the data sets due to responding unit (enterprise/group) and how the questions and concepts are interpreted in the context of different data collections. In the innovation survey, research and development activity is part of a more comprehensive development entity, in the statistics on research and development R&D is the main target of the inquiry.
The content of innovation survey and statistics varies partly by survey. Also, the changes of international definitions and recommendations affect the content of different surveys.
Internal coherence of innovation data and statistics is guaranteed by (cross-)checking and editing the data in multiple ways.
The content of innovation survey and statistics varies partly by survey. Also, the changes of international definitions and recommendations affect the content of different surveys.
Internal coherence of innovation data and statistics is guaranteed by (cross-)checking and editing the data in multiple ways.
Source data and data collections
Source data
The statistics on innovation activity are based on data collection from enterprises.
The innovation survey covers enterprises employing at least ten persons in the industries B-C-D-E-G46-H-J-K-M71-M72-M73 (Standard Industrial Classification 2008). The size categories of the data are 10 to 49 persons, 50 to 249 persons and at least 250 persons.
The research frame is the Business Register/structural business statistics.
The survey is conducted as a total survey of enterprises employing at least 250 persons and as a sample survey of enterprises smaller than this. The sampling is based on simple stratified random sampling. The strata are industry and size category of personnel.
The sampling ratio is around 40 per cent by collection round.
The methodological recommendations issued by Eurostat are followed in the data collection and the planning of it.
The innovation survey covers enterprises employing at least ten persons in the industries B-C-D-E-G46-H-J-K-M71-M72-M73 (Standard Industrial Classification 2008). The size categories of the data are 10 to 49 persons, 50 to 249 persons and at least 250 persons.
The research frame is the Business Register/structural business statistics.
The survey is conducted as a total survey of enterprises employing at least 250 persons and as a sample survey of enterprises smaller than this. The sampling is based on simple stratified random sampling. The strata are industry and size category of personnel.
The sampling ratio is around 40 per cent by collection round.
The methodological recommendations issued by Eurostat are followed in the data collection and the planning of it.
Data collection
The data collection form for the innovation survey is compiled on the basis of the EU-harmonised questionnaire and national data needs. The EU-harmonised questionnaire is produced by Eurostat together with the Member States and other Commission departments. The harmonised questionnaire contains mandatory statutory questions and voluntary questions. Some of the questions, mainly statutory ones, remain on the form from one round to the next. The questions rotate to some extent and topical themes and related batteries of questions are always included on the form for each round.
Of the voluntary questions of the harmonised questionnaire, it is assessed which questions can be removed from the national survey and, in addition, it is charted which themes may be missing from the harmonised questionnaire but are related to data needed in national decision-making.
The data collection uses an electronic form.
The data collection includes at least two reminder rounds in addition to the actual survey. It is also possible to carry out more reminder rounds both by post and email.
Data collection unit is a legal unit although the statistical unit is an enterprise.
In addition to total rate, the response rate is monitored by size category and industry. In accordance with the methodological recommendations of the EU, the aim is a response rate of 70 per cent.
Of the voluntary questions of the harmonised questionnaire, it is assessed which questions can be removed from the national survey and, in addition, it is charted which themes may be missing from the harmonised questionnaire but are related to data needed in national decision-making.
The data collection uses an electronic form.
The data collection includes at least two reminder rounds in addition to the actual survey. It is also possible to carry out more reminder rounds both by post and email.
Data collection unit is a legal unit although the statistical unit is an enterprise.
In addition to total rate, the response rate is monitored by size category and industry. In accordance with the methodological recommendations of the EU, the aim is a response rate of 70 per cent.
Frequency of data collection
The data on innovation activity are collected every two years. The statistical reference year is an even year and the data collection year is an odd year.
Methods
Data compilation
The innovation data are edited in many ways
- the respondent unit and its background information are checked in the data, that is, it is ensured that the unit is a statistical unit corresponding to the Business Register/structural business statistics data, or in exceptional cases the structure of the unit is examined, the magnitude of the data in euros is checked and corrected
- missing data are located and corrected and supplemented, or are left to be imputed
- internal logical errors in the data and other possible errors are located and corrected, for example, impossible values are located
- data are checked and compared with control data, that is, research and development expenditure, for example, are checked by comparing them with data in the statistics on research and development.
Although there is an extensive number of editing rules, the processing of the data often has to be done case-specifically. The number of variables is high and there are numerous points of contact between them. Thus, in correcting and editing the single data value it is worth of utilising and analysing the whole response.
The distributions of data variables are monitored throughout the processing of data. They are also compared with data from earlier years.
Missing data that cannot be logically or otherwise supplemented with existing data are imputed after the actual editing phase. The imputation mainly uses industry-specific and size category-specific modes and medians, but the solution is not considered to bias the results, because the imputation rates are low. Quantitative data are imputed with ratios based on averages formed from turnover in the data.
There are no imputed values in the core indicators for innovation activity, because they are mandatory to answer on the form.
After imputations, a test weighting and macro checks are made. After analysing the test weights and weighted data, a final weighting is made, that is, the calculating and defining the final weights to be combined with the data.
Number of enterprises are used for weighting qualitative variables and turnover for data in euros. The weights for qualitative variables are obtained by dividing the total number of enterprises by the number of responding enterprises by strata and the turnover weights are calculated respectively by dividing the total turnover of the stratum by the turnover of the responding enterprises. Possible outliers are taken into account. These receive the weight 1.
Corrections for non-response or adjustment for non-response errors are not made. Strata are not changed either.
- the respondent unit and its background information are checked in the data, that is, it is ensured that the unit is a statistical unit corresponding to the Business Register/structural business statistics data, or in exceptional cases the structure of the unit is examined, the magnitude of the data in euros is checked and corrected
- missing data are located and corrected and supplemented, or are left to be imputed
- internal logical errors in the data and other possible errors are located and corrected, for example, impossible values are located
- data are checked and compared with control data, that is, research and development expenditure, for example, are checked by comparing them with data in the statistics on research and development.
Although there is an extensive number of editing rules, the processing of the data often has to be done case-specifically. The number of variables is high and there are numerous points of contact between them. Thus, in correcting and editing the single data value it is worth of utilising and analysing the whole response.
The distributions of data variables are monitored throughout the processing of data. They are also compared with data from earlier years.
Missing data that cannot be logically or otherwise supplemented with existing data are imputed after the actual editing phase. The imputation mainly uses industry-specific and size category-specific modes and medians, but the solution is not considered to bias the results, because the imputation rates are low. Quantitative data are imputed with ratios based on averages formed from turnover in the data.
There are no imputed values in the core indicators for innovation activity, because they are mandatory to answer on the form.
After imputations, a test weighting and macro checks are made. After analysing the test weights and weighted data, a final weighting is made, that is, the calculating and defining the final weights to be combined with the data.
Number of enterprises are used for weighting qualitative variables and turnover for data in euros. The weights for qualitative variables are obtained by dividing the total number of enterprises by the number of responding enterprises by strata and the turnover weights are calculated respectively by dividing the total turnover of the stratum by the turnover of the responding enterprises. Possible outliers are taken into account. These receive the weight 1.
Corrections for non-response or adjustment for non-response errors are not made. Strata are not changed either.
Data validation
The validation of the innovation data is performed during the microdata editing stage and during macro editing. The data received is checked by software and edited manually and by automatic editing and imputations. The responding unit and the statistical unit and its inclusion in the target population, the coverage of the response content and item non-response, measurement unit of quantitative variables as well as correctness of values in the data, and relational and routing errors between the variables and the questions, and other possible errors in the data are checked. Also the missing observations are localized.
Documentation on methodology
The implementation of the innovation survey follows the methodological recommendations issued by Eurostat, the Statistical Office of the European Communities.
The concepts are based, inter alia, on the OECD/Eurostat Oslo Manual.
The concepts are based, inter alia, on the OECD/Eurostat Oslo Manual.
Principles and outlines
Contact organisation
Statistics Finland
Contact organisation unit
Business Statistics
Legal acts and other agreements
The compilation of statistics is guided by the Statistics Act. The Statistics Act contains provisions on collection of data, processing of data and the obligation to provide data. Besides the Statistics Act, the Data Protection Act and the Act on the Openness of Government Activities are applied to processing of data when producing statistics.
Statistics Finland compiles statistics in line with the EU’s regulations applicable to statistics, which steer the statistical agencies of all EU Member States.
Further information: Statistical legislation
The innovation survey carried out every second year is part of the joint project Community Innovation Survey (CIS) coordinated by Eurostat and carried out in all EU Member States.
The survey makes use of an EU harmonised data collection questionnaire and uniform limitations and methods. The key concepts of the survey are based on the definitions of OECD and Eurostat (OECD/Eurostat (2018), Oslo Manual 2018: Guidelines for Collecting, Reporting and Using Data on Innovation,4th Edition, The Measurement of Scientific, Technological and Innovation Activities, OECDPublishing, Paris/Eurostat, Luxembourg. https://doi.org/10.1787/9789264304604-en). The implementation of the survey and the statistics follows the methodological recommendations compiled by Eurostat.
In addition to the Statistics Act, the regulations of the European Union in part require the collection of the data in question (Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics, Commission Implementing Regulation (EU) 2020/1197 and Commission Implementing Regulation (EU) 2022/1092).
In addition to questions that are mandatory under EU legislation, the EU harmonised form also contains questions with voluntary status. All these questions are not necessarily implemented in the national inquiry.
In addition to the contents of the EU, the survey and the statistics may also contain topical issues and questions considered nationally important. They are agreed upon separately with domestic data users.
Confidentiality - policy
7.1 Confidentiality – policy
The data protection of data collected for statistical purposes is guaranteed in accordance with the requirements of the Statistics Act (280/2004), the Act on the Openness of Government Activities (621/1999), the EU's General Data Protection Regulation (EU) 2016/679 and the Data Protection Act (1050/2018). The data materials are protected at all stages of processing with the necessary physical and technical solutions. Statistics Finland has compiled detailed directions and instructions for confidential processing of the data. Employees have access only to the data essential for their duties. The premises where unit-level data are processed are not accessible to outsiders. Members of the personnel have signed a pledge of secrecy upon entering the service. Violation of data protection is punishable.
Further information: Data protection | Statistics Finland (stat.fi)
Confidentiality - data treatment
Statistics Finland's official guidelines on the protection of tabulated business data are applied in protecting innovation survey data. As in sample surveys, the basis for publishing the data is to not publish data on the statistical units belonging to the sample. In terms of protection, compliance with the threshold rule (3) is the primary procedure. In addition, the dominance rule is applied to data in euros.
The data contain binary variables, ordinal-scale variables and quantitative variables.
As a rule, the data are released in basic releases so that separate protection is not needed (the released data contain enough observations and dominance does not occur). If exceptions are made to this by increasing the level of detail of tabulation, for example, the need to protect the cells to be published is re-assessed.
Industry-specific data are mainly published on the 2-digit level. However, some of the most sensitive industries from the point of data protection have been combined with other industries. If there is need for protection after possible aggregations, or for some other reason, the cells to be protected are hidden.
In the case of very detailed variables, the examined phenomenon may be rare, and the number of observations remains very small. Even though it in the case of binary variables is difficult to connect observations directly to the observation/statistical unit, the categories with few observations have been suppressed. In addition to primary protection, attention is paid to secondary suppression.
Innovation expenditure by industry is published on a more aggregated level than the classification used in the publication of other data due to a clear dominance problem in certain industries.
The innovation activity data are submitted to Statistics Finland's Research services for research use. The data do not contain identification data. The use of the data for scientific research and statistical surveys is possible only on the basis of a separate application for licence to use statistical data and in unidentifiable form.
In the tabulations submitted to Eurostat, sensitive cells are indicated as protected (also secondary protection), in which case Eurostat does not publish these data. However, the data can be used in calculating sum data at the EU level. Protection is indicated in accordance with instructions given by Eurostat.
The innovation activity data are also submitted to Eurostat's SafeCenter for research use. The data are submitted without identification data. Further information https://ec.europa.eu/eurostat/web/microdata/community-innovation-survey
The data contain binary variables, ordinal-scale variables and quantitative variables.
As a rule, the data are released in basic releases so that separate protection is not needed (the released data contain enough observations and dominance does not occur). If exceptions are made to this by increasing the level of detail of tabulation, for example, the need to protect the cells to be published is re-assessed.
Industry-specific data are mainly published on the 2-digit level. However, some of the most sensitive industries from the point of data protection have been combined with other industries. If there is need for protection after possible aggregations, or for some other reason, the cells to be protected are hidden.
In the case of very detailed variables, the examined phenomenon may be rare, and the number of observations remains very small. Even though it in the case of binary variables is difficult to connect observations directly to the observation/statistical unit, the categories with few observations have been suppressed. In addition to primary protection, attention is paid to secondary suppression.
Innovation expenditure by industry is published on a more aggregated level than the classification used in the publication of other data due to a clear dominance problem in certain industries.
The innovation activity data are submitted to Statistics Finland's Research services for research use. The data do not contain identification data. The use of the data for scientific research and statistical surveys is possible only on the basis of a separate application for licence to use statistical data and in unidentifiable form.
In the tabulations submitted to Eurostat, sensitive cells are indicated as protected (also secondary protection), in which case Eurostat does not publish these data. However, the data can be used in calculating sum data at the EU level. Protection is indicated in accordance with instructions given by Eurostat.
The innovation activity data are also submitted to Eurostat's SafeCenter for research use. The data are submitted without identification data. Further information https://ec.europa.eu/eurostat/web/microdata/community-innovation-survey
Release policy
Statistics Finland publishes new statistical data at 8 am on weekdays in its web service. The release times of statistics are given in advance in the release calendar available in the web service. The data are public after they have been updated in the web service.
Further information: Publication principles for statistics at Statistics Finland
Data sharing
Eurostat publishes the results of the countries on its own web pages https://ec.europa.eu/eurostat/data/database.
The results are also published in the OECD’s databases. Both the European Commission and the OECD use the innovation data extensively in their own analyses and reports.
Micro data on innovation activity are submitted without identification data for research use both to Statistics Finland's Research services and to Eurostat's SafeCenter.
The results are also published in the OECD’s databases. Both the European Commission and the OECD use the innovation data extensively in their own analyses and reports.
Micro data on innovation activity are submitted without identification data for research use both to Statistics Finland's Research services and to Eurostat's SafeCenter.
Accessibility and clarity
Statistical data are published as database tables in the StatFin database. The database is the primary publishing site of data, and new data are updated first there. When releasing statistical data, existing database tables can be updated with new data or completely new database tables can be published.
In addition to statistical data published in the StatFin database, a release on the key data is usually published in the web service. If the release contains data concerning several reference periods (e.g. monthly and annual data), a review bringing together these data is published in the web service. Database tables updated at the time of publication are listed both in the release and in the review. In some cases, statistical data can also be published as mere database releases in the StatFin database. No release or review is published in connection with these database releases.
Releases and database tables are published in three languages, in Finnish, Swedish and English. The language versions of releases may have more limited content than in Finnish.
Information about changes in the publication schedules of releases and database tables and about corrections are given as change releases in the web service.
Micro-data access
The innovation data are available to researchers both in Statistics Finland's Research Services and in Eurostat's SafeCenter.
Data revision - policy
Revisions – i.e. improvements in the accuracy of statistical data already published – are a normal feature of statistical production and result in improved quality of statistics. The principle is that statistical data are based on the best available data and information concerning the statistical phenomenon. On the other hand, the revisions are communicated as transparently as possible in advance. Advance communication ensures that the users can prepare for the data revisions.
The reason why data in statistical releases become revised is often caused by the data becoming supplemented. Then the new, revised statistical figure is based on a wider information basis and describes the phenomenon more accurately than before.
Revisions of statistical data may also be caused by the calculation method used, such as annual benchmarking or updating of weight structures. Changes of base years and used classifications may also cause revisions to data.
Relevance
The users of the innovation activity data are researchers and those engaged in the planning and monitoring of policy measures. The data are used both nationally and internationally, especially at the EU level. The innovation data are key data particularly in the planning and monitoring of the EU's innovation and economic policy.
The information needs of the EU are heard in the planning of the EU-harmonised questionnaire for each round. This allows the Commission departments to convey their data requests concerning the content of the survey. In Finland, the information needs of data users are charted before planning the content of the data collection for each round.
The information needs of the EU are heard in the planning of the EU-harmonised questionnaire for each round. This allows the Commission departments to convey their data requests concerning the content of the survey. In Finland, the information needs of data users are charted before planning the content of the data collection for each round.
User needs
The users of the statistics on innovation activity include those engaged in the planning and monitoring of policy measures both in Finland and internationally. Eurostat, the Statistical Office of the European Communities, as well as the OECD, uses the data of the innovation survey extensively. In Finland, for example the Ministry of Economic Affairs and Employment is using the information of innovation statistics.
The micro data on innovation activity are widely utilised among researchers both in Finland and internationally.
The micro data on innovation activity are widely utilised among researchers both in Finland and internationally.
Quality documentation
Quality assessment
A quality report according to Eurostat's guidelines is produced for each data set of the innovation survey. The essential corresponding quality aspects are also described in this quality reporting related to Statistics Finland's quality documentation.
Quality assurance
Quality management requires comprehensive guidance of activities. The quality management framework of the field of statistics is the European Statistics Code of Practice (CoP). The quality criteria of Official Statistics of Finland are also compatible with the European Statistics Code of Practice.
Further information: Quality management | Statistics Finland (stat.fi)
Similarly to other data, quality perspectives in the processing of innovation data relate to all stages of the statistical production process.
In the acquisition of innovation data, the aim is to attain an adequate response rate for the data to be representative and for high-quality answers. Data are corrected by various means, such as
- identifying deficiencies and internal illogicalities in the data as well as other possible errors and by correcting and supplementing them and
- by examining distributions of variables and comparing data and distributions with previous data and with existing comparison data (research and development activity and other business data
User access
Data are released to all users at the same time. Statistical data may only be handled at Statistics Finland and information on them may be given before release only by persons involved in the production of the statistics concerned or who need the data of the statistics concerned in their own work before the data are published.
Further information: Publication principles for statistics
Unless otherwise separately stated in connection with the product, data or service concerned, Statistics Finland is the producer of the data and the owner of the copyright. The terms of use for statistical data.