The UIS is carrying out a new data collection on innovation statistics, the results of which will be released in mid-2014. Martin Schaaper, our expert on STI statistics, describes the steps required to produce these statistics by countries at all stages of development.
What is innovation?
Innovation refers to the implementation by a firm of a new or significantly improved product, production process, a new marketing method or a new organizational method. It is an ‘added value’ that, for instance, makes workers more productive or efficient in the production process and strengthens competitiveness.
Consider the example of a line of furniture. The company might introduce new software to improve the design of the furniture. This is innovation. Or the company might use new software to improve the shipping or the marketing of the product.
Innovation can also occur at the organizational level, whereby a company establishes new databases of best practices, lessons or other knowledge. These are just a few examples illustrating the importance of innovation.
How do you measure it? What are the key indicators?
Innovation occurs in both the public and private sectors. But for now, the UIS will focus exclusively on innovation in the business sector. The existing international guidelines to collect and analyse innovation data are restricted to this sector, which is easier to measure from a statistical point of view.
In this first round of the data collection, we are gathering data on innovation within the manufacturing industry. We are collecting data on the types of innovation, as well as on the activities and mechanisms used by firms in order to implement these innovations. The aim is to produce data that will help governments develop effective policies to stimulate and support innovation.
How do innovation statistics complement R&D data?
Research and experimental development (R&D) comprise creative work undertaken on a systematic basis in order to increase the stock of knowledge. Data on R&D also reflect the use of this knowledge to devise new applications.
Innovation is broader than R&D. For example, in addition to the firm’s own R&D activities, innovation statistics focus on activities such as the purchase of R&D, acquisition of machinery, technology transfer and staff training oriented towards a specific innovation in the firm.
These statistics shed light on where and how R&D activities take place. Based on this information, countries can collect more specific data on R&D. They also add to the coverage of the UIS Data Centre for developing countries, which is a major priority for the Institute. In many developing countries, it can be very difficult to collect R&D data because companies are generally reluctant to divulge information. For a variety of reasons, there seems to be greater transparency in developed countries.
What are the steps required to build a global data collection on innovation?
At the present time, around 100 countries collect innovation statistics. Europe—through the activities of Eurostat—is the leader in the field. Canada has also been conducting national surveys for the past 20 years. But, despite the obvious demand for this information, there is little data available on the subject. The United States, for example, released the results of its first innovation survey in 2010.
We wanted to develop an instrument that is specifically adapted for developing countries. At the same time, we must ensure that the data can be compared internationally so that countries can benchmark their progress and learn from the experience of others.
In order to develop this instrument, we had to identify the kinds of questions being asked in innovation survey questionnaires, as well as the main indicators being produced by countries. To do so, we collected as many questionnaires of national innovation surveys as possible. With this information, we created the UIS Catalogue of Innovation Surveys.
Next, we carried out a pilot data collection of innovation statistics. The questionnaire was designed based on the methodological guidelines and definitions of the Oslo Manual. This manual provides the framework to produce internationally comparable data on innovation. However, it was originally designed for developed countries. Thus, in 2005, the UIS and several partners produced a set of guidelines to help developing countries adapt the manual to conduct surveys in their own countries. These guidelines are now included as an annex to the Oslo Manual.
Important contributions to the design of the pilot survey were received from a group of experts representing regional statistical organizations and national statistical offices from around the world. The results of the pilot collection are available on the UIS website.
The next step was to carry out a metadata collection of innovation statistics. This information allowed us to identify in detail the methodological procedures of national innovation surveys. Consequently, we were able to better structure the questionnaire for the global data collection and anticipate some challenges in interpreting the results.
Is the Institute working with regional organizations during the first global data collection? Who are these partners?
Given their extensive experience, Eurostat and the Organisation for Economic Co-operation and Development (OECD) are key partners in this project. Eurostat has an extensive database on innovation for European Union countries, and the UIS will tap into this information. Other OECD countries received the questionnaire for completion.
In Latin America and the Caribbean, the UIS collaborates closely with the Network for Science and Technology Indicators – Ibero-American and Inter-American (RICYT).
The African Union also launched a major initiative in 2007, specifically designed to produce R&D and innovation data through its New Partnership for Africa’s Development (NEPAD). The UIS is a major partner in this initiative, and has access to the data collected.
What are you hoping to collect through the new survey and what are the practical limits?
Ideally, we want to collect data reflecting the diverse components of corporate innovation. What are companies hoping to achieve through innovation? How do they cooperate internally and/or externally to introduce successful innovations? With whom? Other companies? Universities?
As for the practical limitations, it must be noted that we are breaking new ground. The first challenge was the UIS questionnaire design. Innovation surveys are complex and wide-ranging. Countries do not necessarily cover the same industries. And, of course, some industries are more innovative than others. For example, the software and retail industry are not the same.
So we must be very precise in the UIS questionnaire in order to collect comparable data. At the same time, the UIS questionnaire must cover a limited number of subjects, otherwise countries will not respond. Therefore, we need to find a compromise between the political relevance of the data and the feasibility of collecting them.
The second challenge is the survey participation rate. For the global data collection, the participation rate will be a big challenge. Part of the answer lies in training. We need to provide national statisticians with the support and training required to effectively respond to the survey. And they, in turn, will provide invaluable feedback on how to improve the data collection over time.
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