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Videocast DataTalks | Episode 3 with Alfredo Giménez (Innovation Director at FACTOR)
In this episode of DataTalks, we chat with Alfredo Giménez, Innovation Director at FACTOR Ingeniería y Decoletaje, who has over 20 years of experience applying agile methodologies in industrial environments, especially in the automotive sector, including companies such as Faurecia and Hitachi in Paris.
During the conversation, Alfredo shares his experience leading industrial innovation and organizational transformation initiatives in global and multicultural teams, focusing on something that is often underestimated: the importance of organizational culture, horizontality between departments, and the involvement of people.
Throughout the episode, concepts such as agile methodologies in industry, the role of data in the factory, change management and how to innovate with a real impact on production are addressed, avoiding projects that remain only in theory.
Why is it relevant for Industrial Directors and Innovation Managers?
During the episode, many of the common questions surrounding industrial transformation projects are addressed:
- Why do many projects fail despite having good technology?
- How can resistance to change be managed in industrial environments?
- Can agile methodologies be applied in industrial production without losing control?
- What role do data and real time play in industrial innovation?
- How can we break down the silos between technical and operational departments?
Alfredo draws on his solid experience in automotive and industrial innovation:
- More than 20 years leading industrial teams in highly demanding environments
- International experience in companies such as Faurecia and Hitachi
- Real-world application of agile methodologies in industrial contexts
- Leadership of global and multicultural teams in transformation processes
🔍 Episode highlights - Key ideas
Agile methodologies in industry for complex environments
Alfredo explains that agile methodologies in industry should not be seen as a model exclusive to the IT world, but rather as a way of organizing work in complex and changing environments.
In his experience, principles such as iteration, rapid learning, and team self-organization can also be applied in industrial production if they are adapted to the plant context.
The key is not to copy Scrum in industry literally, but to use its principles to move forward step by step, validate ideas quickly, and continuously improve processes.
Horizontal organizations to drive industrial innovation
One of the aspects highlighted during the talk is the importance of breaking down organizational silos and promoting more horizontal structures.
When departments such as production, engineering, quality, or IT work in isolation, industrial innovation projects move much more slowly.
On the other hand, when there is communication between areas and a shared vision of the ultimate goal (better customer service), the organization can adapt more quickly to technological and market changes.
Change management in factories: moving at the pace of people
Implementing new ways of working does not depend solely on tools or technology.
Change management in factories must take into account the natural pace of learning in organizations, which is often based on trial and error.
Hence the importance of introducing changes gradually, supporting teams and building trust so that new practices are adopted naturally.
Giving prominence to plant teams
In the industrial transformation projects he leads, Alfredo seeks to involve the teams themselves in the design of solutions.
From organizing work in manufacturing cells to introducing new digital tools, operators and technicians are often the ones who best understand the real problems in the process.
Therefore, involving them from the outset allows improvements to be identified more quickly and facilitates the adoption of changes in production.
Real-time data as a basis for improving processes
The conversation also addresses the role of real-time data in production.
In Alfredo’s own words, having operational data available allows deviations to be detected earlier, indicators such as OEE to be improved, and a better understanding of which factors really affect plant performance.
Access to reliable data not only improves subsequent analysis, but also allows action to be taken before problems impact production or quality.
Final tip
Agility is not speed without control, but rather learning quickly, correcting mistakes, and continuously improving. When people understand the purpose of change, technology becomes an ally.
📺 More episodes of DataTalks
At DataTalks, we talk to industrial, operations, and innovation directors about: Industrial digitization, Industry 4.0 in the plant, practical use of data, and, above all, real experiences without unnecessary theory.
Are you ready to take the leap into innovation with your plant 
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