In a data-driven future, many corporations or other legal entities have witnessed the explosive growth in the application of machine learning and data science, in many different business areas. Recent surveys demonstrate that big data in combination with data analytics evolution will have a significant effect on Research and Development (R&D) and innovation management.


INESIS involvement in the industry of Research and Development is threefold:

To perform R&D in the field of data science

INESIS is interested in participating and working comprehensively on any kind of technology development related to data science. Our philosophy is to utilize our knowledge on modern analytical methods and exploit our analytical and reasoning capabilities with strong quantitative background in solving data-science problems by offering innovative solutions and methods.

We are well aware of the fact that no-matter how strong our skills are, technology is moving at a fast pace and new challenges are constantly emerging in the field of data science. The increasing volume of generated and collected data in combination with the tremendous technological evolution force businesses to search for innovative solutions that will turn the massive amount of information they collect and store into actionable insights.

Our research interests cover a diverse set of activities, which aim at fulfilling the following goals:

  • Design and develop innovative methods and products in the field of data science based on the upcoming/foreseen needs of society, government and businesses.
  • Conversion of research results into commercial products
  • Advance the scientific knowledge and technical skills of our personnel

To provide data analytics services for the implementation of R&B policies

The key parameters in R&D, for the release of a new product or the enhancement of existing products or processes are: people, strategy, technology, and process integration. Recent surveys demonstrate that the rise in big data in combination with data analytics evolution will have significant implications for R&D and innovation management.

Before committing to an investment in R&D, a company needs to analyse a set of factors in order to decide whether or not to invest in R&D. Data analytics are here  to provide  insights for evaluating the need for the development of a new product, the upgrade of existing product, analysing costs and risk factors.

When the research product is ready to be launched in the market data analytics can contribute in the planning of market, sales, pricing and distribution policies.

Data analytics is promising for R&D companies in the following ways:

  • Predictive modelling can reveal targets for the product pipeline
  • Statistical tools can improve client recruitment and enhance monitoring
  • Data mining of public forums and social media sites can identify trends not formally reported

To apply data analysis techniques on actual R&D data

R&D and Intellectual Property Rights (IPR) data reflect the discrete stages of the whole technology lifecycle. Patents reflect the starting point, the invention, which through R&D, reaches market development and commercial diffusion, on which “industrial property rights” such Trademarks and Designs are granted, for the protection of innovative ideas on the industry and commerce sector.

INESIS has many years of experience in the design, implementation and statistical analysis of R&D and Community Innovation (CIS) Surveys of the European Commission. Furthermore, our data scientists have worked for years in the statistical domain of IPR data. Common types of IPR include patents, trademarks, industrial designs and copyrights.

Our expertise in the processing of R&D and IPR data, is to offer you gainful insights on technological and non-technological innovation, by analysing the data that provide information on the innovative technological and commercial advancements at worldwide, country and regional level.