In a market that is constantly changing, it is necessary for companies and organizations to make timely decisions to improve and achieve their objectives. In this way, the different aspects of analytics become strategic allies for the successful development of projects.
Among descriptive, prescriptive, predictive and cognitive analytics there are differences, uses, advantages and benefits that align with the objectives of the organizations that implement them.
What is each state of the analytics?
This type of analytical allows to know the characteristics of diverse phenomena of interest, understanding the historical data. These analyzes investigate in the past to understand key indicators, patterns, contexts and trends that may have gone unnoticed by decision makers.
The great benefit of these analyzes is that, through statistical techniques, they allow to visualize data and identify measures of tendency to find insights in a simpler way for organizations.
It is based on advanced methods such as data mining, parametric statistical analysis and machine learning that allow the creation of forecast models and the probability of occurrence of an event to guide decision making. In this way, the analysis provide a degree of confidence regarding the possible scenarios. Although the results are favorable for organizations, care must be taken with the expectation of accuracy since the success of the predictions involved factors such as the context or the quality of the data.
The benefit it offers to organizations is in obtaining predictions that evaluate the propensity to a behavior or situation. This knowledge can be applied, for example, to avoid the desertion of high-value clients, strengthen cross-selling and up-selling strategies or the prevention of fraud.
Through simulation and optimization techniques, prescriptive analytics allows us to detect the best alternatives within a range of possibilities and points out the ways to achieve organizational objectives optimally.
These analyzes determine the incidence of variables, constraints, key elements of the processes to look for the best feasible results. In this way, the benefits offered are the optimization of resources, waste reduction, costs, time and a key address to address specific problems at the level of operations. Thus, its applications are reflected in the production cycles, the handling of inventories and distribution schedules, among others.
This type of analytical complements the previous states and is based on learning with natural language. From there arise abilities to interpret images, sounds, voices, texts and feelings. This is how it is sought that, in a natural way as humans learn, technologies have the ability to learn, reason and determine scenarios that respond to a need.
Cognitive analytics does not replace human knowledge, because these technologies require an expert to deliver relevant and quality information to generate knowledge, acting as a curator of content so that the cognitive system can ingest information and learn from it, through various iterations of questions, answers and adjustment based on the successes.
The applications of these analyzes range from medicine to treatment studies; customer service, in marketing; product designs, such as medications or advisory services; in education, to find ways of learning and decrease the desertion; to the analysis of musical compositions and the feelings they generate.
The analytical opens a way to support the man to solve problems. However, the added value does not emerge from technology, but from people. Therefore, it is not enough to have data that accumulate in the organization to generate information, decisions and actions, it is also important to accompany a team of consultants and experts who, working together with the people of the organizations, help them to move forward in its analytical path to become competitors in the matter.