Digital transformation, proper data management, and collaboration are the foundation for moving toward more efficient and lower-risk supply chains , agreed specialists from the panel Toward Predictive, Intelligent, and Safe Logistics , organized within the framework of the #SoyLogístico Association ‘s Logistics Breakfast .

Ernesto Zavala, Director of Transportation at Waldo’s , shared the company’s experience implementing systems such as ERP, WMS, and TMS , which have led to tangible improvements in its operations.

“Today, we’ve reduced the time it takes for merchandise to arrive in stores to 72 hours and improved transportation availability by 15% with the same base of carriers. This translates into greater punctuality and a lower risk of delivery discrepancies,” he noted.

According to Zavala, complete traceability and the use of predictive models allow for optimizing service windows, reducing theft, and better negotiating with carriers thanks to shared data.

For Isaías Servín, International Operations & Service Manager at Hamilton Beach , no company can remain static in the face of technological changes and consumer habits.

“Anyone who isn’t thinking about digitizing and implementing advanced systems will suffer in their profitability. The goal remains delivering the product just in time and in the right quantity, and to do that, we need tools that allow us to anticipate disruptions,” he stated.

The executive emphasized that the quality of the information is just as important as the technology used, since “the success of the prediction depends on the data that feeds the systems.”

From another perspective, Enrique Vázquez, director of Recurso Confiable , emphasized that predictability should not be seen as a futuristic aspiration, but rather as a practical exercise in data management and logistics partners .

“Efficient operations translate into safe operations. Properly managing information allows for negotiations with carriers, anticipating restrictions at delivery points, and reducing risks. Ultimately, predictability equals lower risk ,” he stated.

The executive warned, however, that Artificial Intelligence (AI) has not yet replaced human decision-making. “AI models help analyze data, but the final decision remains with humans.”

The panelists agreed that the biggest challenge is not only technological, but also cultural. Employee adaptation, trust in the systems, and collaboration across departments and with external partners are crucial for any successful implementation.

“If we continue to operate in silos, no strategy will succeed ,” said Servín, emphasizing that generational transition and a change in mindset are part of the process toward truly intelligent logistics.

Comment and follow us on X:  @jenna_GH_  /  @GrupoT21

El cargo From reactive to predictive, the future of smart logistics apareció primero en T21.

Artificial intelligence (AI) is revolutionizing retail, both in customer experience and in optimizing internal operations, so Rander Souza , strategic director of digital and AI at Genesys, said this is especially true on the back end , with a notable impact in areas such as personalized recommendations, intelligent virtual experiences and the development of demand-based products.

“The key is how AI can analyze data in real time to offer hyper-personalized recommendations, which dramatically improves the shopping experience,” Souza said.

He added that AI integration not only benefits customer experience but also optimizes retailers’ internal operations.

Souza noted that AI has the ability to predict consumer trends and demand cycles , helping to reduce unnecessary inventories and prepare warehouses and points of sale for the next wave of consumption.

“This allows retailers to reduce operational costs and increase overall efficiency, although these improvements are not always directly visible to consumers,” he said.

The executive noted that this challenge for retailers lies in replicating digital personalization in physical stores .

“Empowering employees with AI-based tools allows them to provide more empathetic and contextualized care, achieving more meaningful interactions,” explained Souza.

He noted that this includes real-time recommendations based on customer preferences , ensuring that every conversation is orchestrated with empathy and understanding.

On the other hand, Souza warned that retailers that do not prioritize the adoption of AI technologies risk losing relevance in an increasingly competitive market.

“A negative experience can completely change the perception of a brand. Integrating AI can inspire loyalty and satisfaction, while failing to do so could result in customer loss and damage to the business,” Souza said.

Predictive analytics and real-time personalization

According to Souza, predictive analytics is one of the most powerful AI tools in retail , as it allows anticipating customer needs and behaviors, offering proactive solutions that improve both personalization and operational efficiency.

The specialist highlighted that the role of the predictive model allows retailers to interact with customers in real time, understanding risks such as shopping cart abandonment and mitigating potential losses.

“Building trust is critical. Retailers must invest in advanced security practices to protect customer data. Identity verification and multi-factor authentication methods are key tools to ensure security and foster consumer trust,” Souza said.

He also highlighted the importance of omnichannel to offer a fluid experience, so “retailers must implement integrated experience platforms that eliminate silos and allow for consistent interaction across all channels.”

Comment and follow us on X: @jenna_GH_  / @GrupoT21

El cargo AI as a transformative driver of retail apareció primero en T21.