Rocha’s Career Milestones

Since the beginning of my professional journey, I have always sought inspiration from notable leadership figures. Biographies of leaders like Jack Welch, with his comprehensive vision of management, recognition and future, captivated me and shaped my first steps in leadership. I learned the importance of well-defined processes and team appreciation.

This theoretical base solidified with practice and, mainly, with the continuous learning provided by other leaders and mentors I met along the way. Their guidance helped me to correct my course, improve skills and made me a more complete leader.

The experience in a global environment like Ipsos has provided me with invaluable learning. Living with different cultures and expectations allowed me to develop the flexibility and sensitivity necessary to lead global teams. In this context, I learned to delegate with confidence, empowering my team and encouraging collaboration in the search for the best solutions. I define goals clearly, but I allow the team to trace the paths to achieve them, fostering creativity and a sense of ownership.

Observing and learning from other leaders, seeking to adapt inspiring practices to my own management style, has been a constant. The feedback from my team is fundamental in this process, as it allows me to identify strengths, areas for improvement and direct my growth as a leader.

Another positive point I consider is a career built solidly, starting my career in an operational position and advancing steadily in increasingly complex and strategic roles, moving through technical areas until reaching more strategic positions. This well-constructed foundation allows me to navigate through different levels of the organization, often serving as a bridge between the operational and strategic level.

Cultural or Regulatory Barriers of Introducing Digital Solutions in Latin America

Generally, the main barrier is "resistance to change," which is part of being human. Jack Welch used to say that "in companies that have gone through many change processes, employees see it as colic, just wait a bit and it will go away on its own," but my point is that at the moment we are in a change and it is inevitable — it will happen. There's no use waiting, thinking that things will continue as they are.

Initiatives already approved, implemented and generating results in a certain country, when taken to another, face resistance at the time of implementation. We hear: "Here it works differently..." It's clear that often the new process doesn't fit like a glove; adjustments are necessary, but one thing is to adjust, another is to listen to "Here this doesn't work..."

At that moment, I always try to identify a Sponsor who is from top management and who believes in the idea to help in the implementation of the new process.

Alignment workshops before the implementation of new processes have worked well to break the resistance barrier, since in this phase we listen and remain open to suggestions. In many cases, minor adjustments can be made without delaying the delivery and it makes a great difference, since people feel heard and actively participate in the implementation.

I learned that each culture has its own time, rhythm and way of working, but at the same time, we are always seeking a way to meet the business needs within the necessary deadlines.

Balancing the Innovative Potential of AI-driven Initiatives with Business Practicality

I always start with a question: "What will be the return of this initiative? More operational efficiency? Competitive advantage? A differentiator for our customer?" It's important that the initiative responds to a company need and it needs to be well-identified so that its impact and return can be measured.

With that, we move to the next step: what is the best technology to meet that initiative? I assure you that it's not always AI.

I participated in some meetings to discuss needs and the person starts explaining: "I need AI for.......," "I think it will be simple, just use AI...," and in many cases, the need is an automation that does not involve AI. This needs to be well analyzed; otherwise, the company will invest a lot of money in AI unnecessarily. It's not because it's the subject of the moment that it should be used in everything.

Today, generative AI is an extremely powerful tool that is available in our options portfolio. It is considered and evaluated to know if it makes sense or not for that product and I can assure you that new products were built thanks to the availability of generative AI.

Managing Cross-Functional Collaboration

To effectively manage collaboration between technical teams, business units and regional stakeholders, we created a division focused on business innovation. This strategy helps us to better understand the needs of each project and promote fast and efficient execution.

Before the creation of this division, each country worked independently and often without the professionals with the necessary profile for the project.

With the creation of a regional division within the technology area, resources are optimized. In addition, we can transfer efficiency from one country to another proactively. For example, we developed a project for Brazil, where part of the team involved was from Mexico and they identified that Mexico had the same need. With that, we exported the same solution already developed for Brazil to Mexico with almost zero cost. And like this, we have several other examples at the LATAM level.

“It is important to understand what the real need is to analyze the available technologies and then select the one that best suits the need.”

This area working closely with the business manages to understand and share examples and efficiencies at a regional level. With that, we are not reinventing the wheel in each country and developing cross-country projects in an efficient and cost-competitive manner.

The optimization of resources also deserves attention since we began to work with a regional team and not individually in each country. According to the profile of the project, we know that we need to allocate resources from Brazil and Chile, for example, for another type of project. We know that we need to allocate resources from Mexico and Colombia. This multidisciplinary team is fundamental for good results.

With this, the business teams already know who to look for to analyze the need and suggest the best solution.

Key Digital Transformation Trends

There's no talking about the future without mentioning AI and recently Ipsos published the article "SYNTHETIC DATA: From hype to reality - a guide to responsible adoption," highlighting one of the trends for the future of market research.

Synthetic data are artificially created information that replicate the statistical characteristics of real data, without referring directly to specific events or individuals. These data are generated through algorithms, especially those powered by generative artificial intelligence, such as Generative Adversarial Networks (GANs) and Large Language Models (LLMs).

Generative artificial intelligence has transformed the production of synthetic data, making it faster, cheaper and more scalable compared to traditional data collection methods. This has opened a range of opportunities for market research, allowing for faster data collection, greater cost-effectiveness, flexibility in research design, optimization through simulations and a deeper understanding of consumers.

Of course, there are risks and challenges in using synthetic data. Without proper validation, this data can distort reality, leading to biased or incorrect information, in addition to not having the richness and diversity of real human data, which can lose nuances and generate repetitive information.

However, with responsible adoption, we seek to ensure that synthetic data accurately represent the target population and are appropriate for the intended purpose, through meticulous validation and testing.

Looking to the future, synthetic data offer a significant opportunity for market research. However, its responsible adoption requires careful assessment of the benefits and potential risks. Organizations like Ipsos, which have expertise in data science, domain knowledge and ethical AI practices, can help navigate this evolving landscape and fully explore the potential of synthetic data.

Tips for Leading Digital and AI Transformations in Organizations

There is no transformation without alignment, so the first step is to be aligned with the organization's goals.

Have a source of inspiration, whether it's a competitor or a case that you saw in a lecture or a workshop. This will help with arguments, in the first meetings and will be a model, a way to make clear where you can get and what results can be achieved. Sometimes it's easier to explain with a real example.

Find an executive who supports your idea. This will give you more confidence throughout the process.

Understand your target audience and adjust your speech to it so that no overly technical language is used in executive meetings, for example. It seems basic, but if it is not very clear who the audience is, it will be harder to sell the idea.

Making partnerships with internal areas is crucial. The transformation will directly impact processes and the more the internal areas are involved in the process, participating in the decisions and contributing to the construction of the new processes, the easier the implementation will be and the less resistance will be encountered.

In addition, it is important to understand what the real need is to analyze the available technologies and then select the one that best suits the need. The best technology is not always the most recent one and not always does the company need technology released this month. The best technology is the one that will meet the business need.