Advanced Analytics: The Pillar of Business

What is advanced analytics and why is it so important for businesses?

We define advanced analytics as a set of techniques that use statistics and mathematical models to discover patterns, gain more knowledge about business aspects, and make better decisions. In the process, large volumes of information are analyzed and processed in such a way that it is possible to extract practical and valuable conclusions.

For companies, advanced analytics is an opportunity. It provides department heads with a global, broad, precise, and deep view of their operations, customers, markets, and competitors. As a result, more effective decisions are made that correct and anticipate failures, improve processes, and achieve greater profitability.

There are three areas that are currently key in the field of advanced analytics. They are as follows:

• Predictive analysis
• Machine Learning
• Conversational language models

Let's delve a little deeper into what the implications of each of these more specific areas related to advanced analytics are.

Three fields to master advanced analytics

Let's look at the details of each of the areas mentioned in the previous section and what impact they can have on your business.

Predictive Analysis

Predictive analysis positively influences competitiveness. This is a technique that can optimize an organization's activity to the maximum. For example, it allows for quick but well-informed decisions, better management of risks and uncertainties, and early detection of potential obstacles in business operations performance.

Additionally, it is a methodology that promotes customer retention and loyalty. How does it achieve this? Mainly, in three different ways:

• Pattern identification. By analyzing data predictively, it is possible to anticipate customer needs by revealing their behavior patterns. In this way, it is easier to launch marketing campaigns tailored to their preferences that increase their satisfaction and engagement with the brand, for example.
• Deep customer knowledge. Advanced analytics in its predictive form also reveals more data about each of the brand's customers. As a result, it is easier to provide more personalized customer service.
• Discovery of discontent. A customer may not be entirely satisfied and may not have yet considered changing providers or companies. Predictive analysis can detect signs that something is not going well, such as a decrease in orders or an increase in complaints filed with customer service.

When predictive analysis is done in the cloud, these and other benefits are achieved without the need to invest in and maintain a large infrastructure, in addition to gaining access to data from anywhere in the world.

Machine Learning

Another notable field is machine learning. Why is this technique so necessary in the world of advanced analytics? Thanks to artificial intelligence, it is possible to automate and optimize processes, as well as establish predictive models that are impossible to obtain with human processing. And most importantly, we achieve continuous improvement of processes.

To achieve a truly effective machine learning system, it is essential to work towards obtaining quality data, understanding the models, and efficiently implementing them in a company. Similarly, it is a technique that requires significant computational resources, so most companies rely on cloud infrastructure, which provides power and scalability according to their needs.

Among the main applications of machine learning are: image and video recognition, process automation (from logistics to production, including quality controls), or autonomous vehicles. Overall, machine learning drives innovation and efficiency in organizations, also enabling greater personalization and anticipation of market needs.

Conversational Language Models

We now address another revolutionary technology. The emergence of conversational language models is improving communications and reducing the workload in some key departments.

This technology, usually materialized in the form of a chatbot, is successfully applied in areas such as customer service and after-sales service, allowing for a smoother and more natural interaction. Similarly, conversational language models have the ability to personalize the customer experience, providing accurate and relevant responses to their queries and needs.

Finally, natural language models are capable of interpreting context and maintaining coherent conversations. Companies that apply such solutions adapt better to their customers and, at the same time, streamline the corresponding processes.

We have recently seen how conversational language models like ChatGPT have revolutionized the landscape of these systems, even surpassing the initially anticipated learning capabilities. We are witnessing a revolution that is already influencing the improvement and agility of any area of the company, not just customer service.

Advanced Analytics and Ethics: The Two Sides of the Same Coin

Ethics plays a fundamental role in the context of advanced analytics. As organizations use advanced data analysis techniques to obtain valuable insights, it becomes necessary to establish policies and practices that promote professional ethics in the use of these technologies while mitigating the effects of biases, which are often inherent in a wide variety of data sets.

Let's talk about three ways to make advanced analytics more ethical:

• Supervision. Automation is very beneficial, but systems must be rigorously inspected. As a result, this ensures that models adopt well-regarded qualities, such as fairness or impartiality, and avoid improper behaviors, such as discrimination.
• Data Quality. Another key point for achieving ethical advanced analytics is to ensure that data is accurate, complete, and reliable, avoiding the inclusion of biased information. Transparency in the data collection and storage process is essential to maintain trust and integrity throughout all subsequent phases of analysis and exploitation.
• Training and Education. Many of the mentioned technologies have just arrived. Despite this, their potential impact is extremely high. Therefore, they must be implemented responsibly. The way to achieve this is to raise awareness and train internal staff on the ethical aspects of advanced analytics. Teams must understand the potential impacts and risks, as well as adopt good practices in data usage and decision-making.

Advanced Analytics with SEIDOR is the Winning Proposal

Advanced analytics is becoming a true revolution, especially with the advent of astonishing technologies such as natural language models. Nowadays, any company will be able to make the most of data and make informed decisions. However, it is always essential to incorporate a series of best practices and reference methodologies to ensure success during and after the implementation of these innovative solutions.

The Data & Analytics team at SEIDOR has professionals prepared to tackle these new technologies and cutting-edge solutions and put them at the service of the business. We have over 25 years of experience, during which we have helped more than 2,500 clients. If you want to benefit from the advantages of advanced analytics and have the support of experts in the field, contact us. We will be delighted to help you make the most of your data's potential and lead your company to success in today's competitive business landscape.