Since the dawn of history, data has been the starting point for all the information surrounding the world, especially in recent years, when technological capacity at the infrastructure level has grown by leaps and bounds to support the storage of bytes up to tebibytes, and with the certainty that new measures will need to be invented. This is especially true in companies, where data, as a unit, has been the input that generates sources of information that allow the organization to create indicators and metrics for future decision-making.
Data analytics methods are extremely important in the digital transformation of companies, as they enable data to be transformed into concrete actions for the business. The analytical universe encompasses different levels of complexity depending on the value to be obtained from the data and the challenge this poses from a technological point of view.
Through this article, we will understand the approach of each type of analytics and its use case for companies:
Different types of analytics have made it possible to analyze the behavior of a process, examining past data using descriptive analytics and enabling a better understanding of the data through BI and data mining tools, understanding what happened.
Diagnostic Analysis
Data analysis allows us to answer why things have happened and identify behaviors and patterns that enable organizations to define a strategy for corrective or improvement action.
Predictive Analytics
Based on real-time information and using statistical modeling or machine learning tools, it allows you to predict the behavior of a process and anticipate the future in order to make decisions that may favor a specific business case.
Prescriptive Analytics
It seeks to generate an action plan or recommend other actions based on available resources and data, predictions, and other external variables, leveraging the use of combinatorial optimization algorithms called Operational Research.
Based on these concepts, we can see the importance of analytics as a driver of digital transformation within organizations at different points in time. It is a technological trend that helps us improve efficiency in the company and generate new customer experiences by improving a service or process, in accordance with the following key stages that management must take into account when implementing this type of project:
- The selection of Digital Analytics tools based on their cost-benefit ratio, field of expertise, and complexity of the business case.
- The processing of information collected using selected analytical models and the questions that need to be answered.
- Data-driven decision-making to meet the organization's strategic objectives as reflected in its KPIs.
During my experience as a Pre-Sales Software Architect within my organization, interacting with various clients and understanding their needs has allowed me to identify the great importance of Data Analytics, using it as the main input for tools that enable the analysis, collection, organization, and processing of what has happened in the past, what is currently available, including process improvement and the organizational culture composed of each of the company's members, as well as the future projection reflected in its vision, to help its customers solve their business problems. None of this will be possible if the sponsors or management roles within the organization are unclear about it.
Understanding that data is dynamic, as are business processes and interactions with people, will enable organizations to identify their roadmap to digital transformation.