Have you wondered how data analysis is used in Mexico? Data has become a crucial resource for companies in Latin America, catalyzing strategic decisions and optimizing operational efficiency. In an increasingly digital environment, trends in data management and analysis are redefining the regional commercial scenario and the way in which each company .
In this new era of data valuation, countries like Mexico have chosen to accumulate data and information that is truly valuable to their business clients and partners.
Well, even though the vast majority of companies accumulate enormous volumes of relevant data about their operations, quality, logistics, equipment and customers, they face the challenge of protecting this data. Throwing them away is not an option, and even more critically, many companies are unable to capitalize on this information due to the limitations of the tools available.
This panorama only offers a preliminary look at the vast possibilities that Big Data opens up for the sector, although it is accompanied by significant challenges such as shortages, disruptions in supply chains, war conflicts and a shortage of qualified personnel.
However, these challenges do not diminish business interest in investing in innovation; In fact, companies are willing to allocate up to a third (33%) of their budgets to analytics, Big Data and data science projects, evidencing the potential and commitment to digital transformation in the region. Investing in data analysis in Mexico is necessary for your company to grow, with the support of consulting firms such as Codster.
How is data analysis used in Mexico?
In accordance with Oscar from Blue Tab Mexico, presents some key trends that are shaping the way companies in Mexico and Latin America conduct their operations, and some that are yet to come:
- Real-Time Data Analytics: Organizations are implementing real-time analytics tools to access instant operational insights, making it easier for them to make agile and informed decisions. This is crucial for optimizing supply chains and personalizing the customer experience.
- Application of Artificial Intelligence (AI) and Machine Learning (ML): These technologies are being used to analyze extensive data sets and anticipate trends, which has applications in market segmentation, personalized recommendations, and process automation.
- Privacy and Data Security: Given the growing focus on data privacy, companies are strengthening their security and compliance protocols, adapting to regulations such as the General Law on Protection of Personal Data in Mexico and other regulations in Latin America.
- Customer Experience (CX) Analytics: Understanding and meeting customer expectations is more crucial than ever. Data analysis helps improve products, services and loyalty strategies.
Looking ahead, there are other ways to use data analytics in Mexico:
- Employee Experience (EX): In parallel with CX, employee experience will come to the fore, using data to improve talent satisfaction and retention.
- Data Ethics: Ethics in data management will gain prominence, with transparent and responsible practices in the collection and use of information.
- Advances in Automation: RPA and cognitive automation will become more prevalent, optimizing processes and allowing employees to focus on strategic tasks.
- Machine to Machine (M2M) Collaboration: Direct communication between devices will drive automation in areas such as manufacturing, logistics and healthcare.
- Potential of Quantum Computing: With the promise of transforming data analysis, quantum computing will make it possible to manage and analyze massive volumes of data in record times.
But, these are not the only ways we could use data analysis in Mexico.
Optimizing business analysis to obtain valuable insights
At their core, business analytics tools transform raw data into meaningful patterns and concrete actions. Curiosity about “business analysis” has climbed 263% in the last decade. Data analytics platforms in Mexico, enriched with artificial intelligence and machine learning, provide vital insights for business users, helping to identify problem areas, detect emerging trends or discover new sources of income. Processes such as data mining, queries, reporting, and visualization are key components of an enterprise analytics ecosystem, exemplified by the use of visual analytics in these platforms.
A growing number of business leaders see data analytics in Mexico as essential for organizational survival and prosperity. Nearly a quarter of all organizations already employ business analytics, rising to 80% in entities with more than 5,000 employees. For example, Delta Airlines, with nearly 90,000 employees, has invested more than $14T1 billion in business analytics to optimize baggage handling, significantly improving the customer experience by reducing baggage issues and delays.
Business analytics prove invaluable in almost every phase of the customer experience, from improving the performance of marketing campaigns to creating buyer profiles and market segmentation, enabling highly personalized sales and marketing campaigns. Furthermore, in the manufacturing industry, these tools are crucial for digitalization, helping to optimize supply chains, prevent delays and boost profitability, offering manufacturers a data-driven approach to optimize production and maintain quality.
For effective data presentation, organizations rely on clear visualizations, with the popularity of “data visualization” remaining high. Platforms like Tableau offer various options for visualizing data, from graphs and maps to heat and tree maps, facilitating quick and deep understanding of data.
Exploring edge computing for real-time analytics
With the recent onslaught of data and the need for instant analysis, many companies are moving their data analysis to the edge, processing information directly on the generating device. By 2025, more than 50% of critical data is expected to be generated and processed outside of traditional data centers, adopting an edge computing approach. This change promises to reduce latency and improve efficiency in data analysis, crucial for speed-dependent sectors such as healthcare and manufacturing, and offers the additional benefit of increasing data privacy and security by preventing data transfer. to the cloud.
Analytics at the edge is vital for Industry 4.0, allowing immediate processing of critical data, such as temperature and humidity, directly at the generation site, optimizing operations without the need to send this data to the cloud. Notable examples include the United States Postal Service, which has dramatically improved efficiency in locating lost packages using edge analytics, demonstrating the power and practicality of this technology in real-world, everyday applications.
Implementing a Data Mesh Architecture
Another way to use data analytics in Mexico would be data mesh, which is an architecture that supports self-service analytics. Search interest for “data mesh” has increased almost 480% in the last 5 years.
It is an approach that advocates decentralizing data ownership and management, treating data as a product and establishing domain-oriented data teams.
The key idea behind data mesh is to distribute responsibility for data across different teams within a company. This allows teams to take charge of their own data domains and make data-driven decisions independently.
Governance is also embedded within domain teams rather than being imposed from the top down. Each team has the autonomy to govern and manage their data products based on their domain-specific requirements.
The use of tools and technologies varies by team and their specific domain due to the distribution of data throughout the company.
An example of a data mesh architecture in action comes from the financial industry, where data is incredibly valuable but sharing it carries inherent security and privacy risks.
JPMorgan Chase Bank built a data mesh solution in 2022 with the help of AWS. Before integrating data mesh, teams needed to extract and join data from multiple systems across multiple data domains to create reports. Investing in data analysis in Mexico is necessary for your company to grow, with the support of consulting firms such as Codster.
