Analytics for Decision Making: The Week in Tech

This week, Latin American insurance company INTERprotección announced an alliance with tech giant Google to boost insurance adoption in the region. Meanwhile, industry experts clarify how data scientists are developing better methodologies for businesses by implementing analytical methods, including business intelligence, statistics, simulation, mathematical optimization and machine learning. 

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INTERprotección and Google Cloud Ally to Penetrate Insurance Market

Both companies will use data-driven capabilities and analytics at scale to boost the insurance market in Latin America. Currently, only one out of every four Mexicans has insurance and both companies are working to address that problem by assertively connecting customers with products, opening up innovation in the insurance industry and implementing best practices. 

"We are not looking to transform the business but to give it an extra edge and anticipate the market’s needs. The alliance [with INTERprotección] has already started, we have been working on it, but the teams are already working on bringing security platforms forward," said Julio Velázquez, General Manager, Google Cloud.

How Data Scientists’ Methodologies Work

Modern organizations have to deal with vast amounts of information on a daily basis. Under these circumstances, decision making can be optimized through technological innovation, explained Jose Rivero, Director, Infor, to MBN. Rivero delves in the numerous methods available for data scientists and why it is important to use these tools to support real-life business decisions. 

“Data scientists use a rich collection of analytical methods, including business intelligence, statistics, simulation, mathematical optimization and machine learning. Every method excels at some specific task, but none of them solve complete business problems on their own. To build real-life decision solutions, the data scientist works with business users to investigate the problem and the available data, and then selects and implements the combination of methods that best fits the need and budget,” said Rivero.  

Traditional Methods are not Enough for Customs Anymore

Traditional methods can no longer handle the challenges that today’s customs face, explained Hector Cobo, Regional VP Mexico, Caribbean and Central America, SAS. It is vital for customs authorities to implement technological tools, he added. Analytics, artificial intelligence and machine learning are crucial to improve processes, ensure compliance and improve service for citizens and organizations.

“As supply chains and the flow of products across borders and ports normalize, customs must be more agile and resilient, while monitoring strict compliance with rules and regulations, as well as keeping an eye out for any attempts at fraud or crime,” said Cobo. 

Absence of Proper Personnel Training Affects Latin America’s Newest Data Centers

Companies face a shortage of trained personnel to man Latin America’s newest projects, warns Josue Ramírez, Regional Director Latam, International Data Center Authority (IDCA). Both the data centers and the companies involved in their construction are affected by the scarcity of well-trained personnel, including designers, installers, contractors, construction supervisors, commissioning agents and day-to-day managers of critical infrastructure. 

“In recent years in Latin America, there has been a large increase in new hyper-scale data center projects, as well as the expansion of many colocation data centers, leading to a great need for trained and specialized personnel,” said Ramírez.