Renata Mello Feltrin
Renata Mello Feltrin, executive director Latam CI&T and LinkedIn Top Voice, is a veteran in the field of technology and innovation, with more than two decades of experience. She has led innovation and digital transformation strategies across multiple sectors, including finance, retail, consumer goods, entertainment, industry and healthcare.
The ST-One team invited the executive to comment on the role of data intelligence in the digital transformation of industries, the benefits and challenges of this implementation and how constant renewal is essential for the success of consolidated corporations.
Renata highlights the importance of organizing the data pipeline and developing a data-driven management culture. She points out that “typically, industries generate a lot of data, but don’t use it in a structured way. If you don’t organize the data into an analytical architecture so that you can use it, you don’t have the foundation to start taking advantage of science technologies data.” For her, “it is essential that leadership learns to look at the process with the intention of continuous improvement and to ask the right questions, looking for gaps. Data will be great allies in bringing quick and accurate answers that will lead to evolutionary decisions .”
Renata also addresses the main benefits of applying data science technologies in the daily operations of industries. According to her, “what you don’t see, you don’t have. And what you don’t measure, capture, analyze, you don’t really see. And when you start to have that and see it more precisely, you can identify improvement gaps and earning possibilities and improving the entire process.”
Check out the full interview:
How do you see the role of data intelligence tools in the digital transformation of industries?
Renata Mello Feltrin: Fundamental. Without clear data that provides a precise view of opportunities for improvement, it is not possible to make truly significant improvements in efficiency, which is the first gain for those who bring data into the practice of data-oriented management. And then, secondly, combining this data with other data, often external, in order to enrich views and generate more intelligent and predictive analyses, leads to real growth results.
What are the main benefits that industries can obtain by applying data science technologies in their daily operations?
Renata Mello Feltrin: First, as I said, efficiency. What you don’t see, you don’t have. And what you don’t measure, capture, analyze, you don’t really see. And when you start to have this and see it more precisely, you can identify gaps for improvement and possibilities for gains and improve the entire process. Then, predictions based on intelligence models can anticipate much better and more assertive decisions, such as production planning, logistics routes and storage models, etc. The entire process and chain benefit from a data driven model, which comes from data science technology applied to the day-to-day process.
Could you share an example of how data intelligence improved operational efficiency on a project you worked on?
Renata Mello Feltrin: Of course. I have already participated in different projects in the area. One of them, from a large consumer goods industry, led to the development of a predictive product mix distribution model, considering production and sales histories, enriched by geographic and consumption data. This generated an uplift in sales of 8.5% in the first predictive analysis test. This is just one example; There is a lot of opportunity throughout the production and distribution chain for this type of solution.
What are the main challenges that industries face when implementing technologies that integrate data intelligence into their operations?
Renata Mello Feltrin: First, organize the data pipeline itself. Typically, industries generate a lot of data, but do not use it in a structured way. If you don’t organize data into an analytics architecture so you can use it, you don’t have the foundation to start taking advantage of data science technologies. The second point, and as important as the first, is to develop a data-driven management culture. Leadership especially needs to learn to look at the process with the intention of continuous improvement and learn to ask the right questions, looking for gaps. Data will be a great ally in providing quick and accurate responses that will lead to evolving decisions.
How do data intelligence technologies, such as IoT and Big Data, contribute to the process of making more assertive decisions?
Renata Mello Feltrin: There are many aspects. For example, there is the issue of real-time data collection. With sensors and IoT devices, you can collect real-time data about operations, environment, machine health and consumer behavior. This allows a continuous and updated view of operational conditions, which, combined with the collection and storage of large volumes of data from various sources, allows for a more complete and accurate analysis of available information. IoT data is also important for detecting anomalies, predicting equipment failures and optimizing preventative maintenance, reducing costs and improving efficiency.
With Big Data, it is possible to identify patterns, trends and correlations that would be difficult to detect manually. With this, machine learning and artificial intelligence algorithms can be applied to predict future events and optimize processes. Additionally, analyzing large volumes of data helps identify potential risks and develop proactive mitigation strategies.
Even from the point of view of new business development, which is a topic that I connect with a lot and where these technologies are super important: the combination of data generated by IoT devices and advanced Big Data analysis can reveal new business opportunities, development of new innovative products and services that meet emerging market demands.
Copyright: ST-One
Do you believe that some types of industry can benefit more than others from the application of data intelligence technologies?
Renata Mello Feltrin: I believe that everyone can, but those that have more scaled operations and complex logistical processes are those that have immediate advantages in adoption due to the quantity and complexity of the data they generate and the need for optimization and continuous innovation in their operations. These include: manufacturing, healthcare, financial services, logistics, energy, telecommunications and retail.
How can data intelligence help industries become more sustainable and environmentally friendly?
Renata Mello Feltrin: There are many ways, especially linked to avoiding waste. Real-time energy consumption monitoring, for example, can provide opportunities to identify anomalies and quickly correct them. Better management of natural resources, such as raw materials and water, is also possible. There is also the possibility of using sensors to measure air quality and pollutant gas emissions, allowing quick interventions to minimize environmental impacts. Ultimately, better waste management, better production planning and regulatory risk management – accurate collection of necessary data can go a long way toward complying with environmental regulations.
What skills do you believe are essential for professionals who want to work with data intelligence in industry?
Renata Mello Feltrin: A set of technical but also interpersonal skills. It is important to understand how machine learning and artificial intelligence systems work, to be able to help think about the data and correlations that can bring the results sought by the industry. But also critical thinking and problem solving, developing the ability to communicate insights and data analysis results in a clear and concise way to non-technical stakeholders, the ability to work in a team, especially in multidisciplinary teams, and most important of all: curiosity and desire to continually learn. It would also add specific knowledge about the industry in which it operates, be it manufacturing, healthcare, energy, etc.
How do you see the future of data intelligence in the industry? Are there emerging trends we should be aware of?
Renata Mello Feltrin: We’ve talked about a lot here already, but speaking of the future, without a doubt AI and ML algorithms are becoming more sophisticated, allowing for more accurate and predictive analyses. The evolution of machine learning, which automates the data modeling process, making it accessible to professionals with less technical experience, will also greatly accelerate the scaled adoption of these technologies in the industry.
Another very interesting topic is Digital twins, for simulation and modeling applications. In other words, virtual replicas of physical processes that allow detailed simulations and modeling to optimize performance and maintenance. The application of this ranges from manufacturing to smart city management. Imagine the potential of this for the near future?
– Interview carried out through the ST-One Press Office: assessoria-imprensa@st-one.io
