According to the CNI (National Confederation of Industry), industry investment in innovation and processes grew 33.4% between 2016 and 2019. At the end of this period, R$ 16.9 billion were invested, representing 69% of the total invested by all Brazilian companies.
This effort to seek more technology and innovation in industries is observed through various actions, such as the implementation of data culture. In the area of Research & Development (R&D), this ensures that the industry is up to date with market trends and that intelligent solutions are incorporated into production.
It is important to note that, among the different sectors of the industry, the one that invests the most in R&D is the pharmaceutical industry. According to the Talk Science website (2023), it holds the world record for investments, totaling US$ 138 billion. This investment allows the search for more efficient treatments, the development of new products, the discovery of new raw material suppliers and the improvement of the bioavailability of medicines.
However, the pharmaceutical industry is not alone. Other sectors are also investing in innovation to improve their products. According to the Ministry of Science, Technology and Innovation (MCTI), in the last decade, Brazil has invested R$ 24.2 billion in R&D in the food sector. According to Exame magazine (2023), in the article “R&D and the future of food“, positive advances in this area have many incentives. The main motivation is the search for alternatives to offer the same products in a sustainable way.
These efforts are made both to benefit consumers and the business itself, without losing sight of the possible future shortage of raw materials. In addition, according to the Uniemp Institute, the main innovations in the market are focused on the development of inputs, biotechnology, capital goods and packaging.
Creating and Enhancing Products from Data
Data culture is the practice of incorporating data collection and analysis into the daily lives of industries. This set of habits, when integrated into the operation, brings several benefits, especially in the decision-making process. With this, management is done strategically, always based on data.
It permeates all manufacturing levels, facilitating the understanding of standards and having a preventive character. This prevention feature can be used both to avoid problems and to identify opportunities for improvement.
Thinking about this last aspect, of exploring new opportunities, the culture of data is widely spread in the area of Research & Development (R&D). In daily processes, it is possible to analyze and manage data, encouraging innovation.
Within a pulp and paper industry, for example, using data science allows for accuracy in laboratory air conditioning. In this type of industry, it is crucial that there are specific rooms with temperature, humidity and other aspects intrinsic to certain types of experiments, such as illuminance. These aspects need to be ensured at all times, not only during the experiment, but also in advance, ensuring that the experiment will not be corrupted.
Due to the numerous variables that need to be checked, having a system that collects the necessary information from several pieces of equipment at the same time is a facilitator. In addition, having technology that records the history of this data certifies the quality and accuracy of the studies.
The PDCA cycle applied in R&D
The PDCA (Plan – Do – Check – Act) methodology is widely used in Research & Development to optimize operational efficiency, improve processes and drive innovation. It is carried out in four stages, in which data analysis plays a key role:
- Planning: In this stage, the specific and measurable goals to be achieved are defined. From data collection, it is identified which processes need to be improved and how this will be done.
- Execution (Do): This is the execution phase, where actions are carried out according to plan. Data recording and proper training of those involved are essential.
- Check: In this step, the results achieved during the execution are evaluated. The analysis of the collected data allows the identification of possible deviations and inconsistencies.
- Act: In the last step, the assignees implement changes based on the results of the verification. If performance is unsatisfactory, steps are taken to improve the process. In positive cases, the effectiveness of the plan is confirmed, standardizing the improvement.
The development of prototypes is also an integral part of the routine in this area. This practice allows industries to test their ideas before implementing them on a large scale, using the concept of Minimum Viable Product (MVP). In the process of creating the MVP, it is necessary to clearly define the value proposition, that is, to understand what problem the product proposes to solve. Then, the prototype is built using only the essential resources, and then performs the test and interprets the results. In R&D, this resource is used to avoid losses in the development of projects.
Advantages of Data Technology in Industrial Production
The use of data science in industry brings numerous advantages, such as:
- Improvement in supply management, by using inputs in the right quantity;
- Error prevention, thanks to the data history available whenever necessary;
- Greater assertiveness at work, due to easy access to data by the entire team;
- Improvement and quality assurance of products, experiments and processes, through continuous data monitoring;
- Decreased rework, resulting in faster processes;
- Strategic decision-making, based on data.
The positive impact goes beyond the procedural and also reaches the cultural and professional dynamics. The need to ensure professionals trained to work in the areas of R&D, technology and data science led to the creation of several specialization programs.
An example of this is the “Inova Talentos” program, created by the Euvaldo Lodi Institute (IEL) in 2015, which encourages innovation projects in industries. Those approved are entitled to technological development grants, with the objective of developing research, development and innovation (RD&I) activities. The benefits of this partnership include the acceleration of results within the organization for up to three years.
Technology that leads to Productivity and Innovation
Investing in technology and innovation is always beneficial. According to the article “R&D, innovation and productivity in Brazilian industry” (2015), innovative companies have a productivity level about 30% higher than that of non-innovative companies. This number tends to increase the more technology-intensive the sector is, proving that the relationship between technology and productivity is increasingly intrinsic.
With this connection in mind, ST-One technology acts in the transformation of the industry to a new level of productivity, improving its science with each new challenge. This makes it possible for digitalization present in different industry sectors, including R&D, to reach the next stage of digitalization and intelligence.