Innovation: documentation of statistics
Basic data of the statistics
Data description
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
Statistical unit
Unit of measure
Number of enterprises
EUR thousand (EUR 1,000 in general in data collection) or EUR million (EUR million most often in publication)
Reference period
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
Sector coverage
Time coverage
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
Concepts
Extramural research and development
Innovation
Innovation activity
Process innovation
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
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
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
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 accuracy and reliability of the survey results can, however, 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
Punctuality
Completeness
Coverage error
Over-coverage by collection round is around one per cent of the number of enterprises in the frame.
Measurement error
Unit non-response rate / A4
<caption>
Industry group | Size category of personnel | Frame | Survey |
Coverage %/ |
Over-coverage | Respondents | Response rate, % |
---|---|---|---|---|---|---|---|
All industries | 10-49 | 6,888 | 2,295 | 33.3 | 53 | 1,402 | 62.5 |
All industries | 50-249 | 1,766 | 1,029 | 58.3 | 25 | 737 | 73.4 |
All industries | 250 or over | 381 | 381 | 100.0 | 0 | 306 | 80.3 |
All industries | All enterprises | 9,035 | 3,706 | 41.0 | 78 | 2,445 | 67.4 |
Manufacturing | 10-49 | 2,735 | 966 | 35.3 | 18 | 599 | 63.2 |
Manufacturing | 50-249 | 865 | 522 | 60.3 | 6 | 387 | 75.0 |
Manufacturing | 250 or over | 216 | 216 | 100.0 | 0 | 173 | 80.1 |
Manufacturing | All enteprises | 3,816 | 1,704 | 44.7 | 24 | 1,159 | 69.0 |
Services | 10-49 | 4,153 | 1,329 | 32.0 | 35 | 803 | 62.1 |
Services | 50-249 | 901 | 507 | 56.3 | 19 | 350 | 71.7 |
Services | 250 or over | 165 | 165 | 100.0 | 0 | 133 | 80.6 |
Services | All enterprises | 5,219 | 2,002 | 38.4 | 54 | 1,286 | 66.0 |
Item non-response rate / A5
In other respects, the item non-response of the data is small, for example around three per cent for the question on use of protection measures, for use of public financial support and for cooperation.
Processing error
Comparability
Comparability - geographical
Comparability - over time
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.
Coherence - cross domain
As weighted, the background information of the innovation activity data, i.e. personnel and turnover, differ somewhat from the corresponding data of the Business Register and the structural business statistics, due to data provider and statistical units differing from one another in some respects.
Coherence - internal
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 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
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, but the data provider can also respond with a paper form (the form is available at Statistics Finland's data collections pages).
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, email and phone.
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
Methods
Data compilation
- 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. Information on personnel and turnover, and on other possible business data are compared to Business Register and to data of structural business statistics.
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 and investment data of the structural business statistics.
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. The responses at group level (activity taking place in Finland) and possible outliers in the measured phenomenon are taken into account in calculating the weighting coefficients. These receive the inflating coefficient 1.
Corrections for non-response or adjustment for non-response errors are not made. Strata are not changed either.
Data validation
Documentation on methodology
The concepts are based, inter alia, on the OECD/Eurostat Oslo Manual.
Principles and outlines
Contact organisation
Contact organisation unit
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 (Decision of the European Parliament and of the Council (No 1608/2003/EC) and the Commission Implementing Regulation (No 995/2012)).
In addition to questions that are mandatory under EU legislation, the EU harmonised form also contains questions with more 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
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
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
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 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 micro data on innovation activity are widely utilised among researchers both in Finland and internationally.
User satisfaction
Actual user satisfaction polls have not been made concerning the statistics.
Quality documentation
Quality assessment
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 frameworks complement each other. 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 (target 70 per cent) 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 (checking of observation units, errors regarding thousands in the euro data and so on) 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.