With the market becoming increasingly dynamic and turbulent, managers want more than anything to predict the future. After all, they need to know more about what is happening in their company in order to plan their next steps and actions. Predictive data analysis has emerged to meet this need.
Applying this concept brings a series of benefits, such as increased visibility of information to generate a better understanding of the business and more security for the company's processes.
If you want to learn more about this subject, check out this article!
What is predictive data analysis?
Predictive analysis consists of organizing and extracting valuable information from historical data in order to decide on the best actions that can predict possible success scenarios for the business. This is done using data science, statistics and artificial intelligence methods. In other words, powerful computational tools and robust mathematical models.
It is one of the main analyses carried out by data science, the others being: descriptive, which aims to clarify what is happening; diagnostic, which seeks to explain what has been shown by the description; and prescriptive, which tries to explain the consequences of certain future actions.
Prediction is based on identifying patterns, which define the correlation between facts. It basically works like this: if, in a scenario, when X happens, the direct consequence is always Y, it is possible to predict with a certain level of certainty (the probability) that the next time X occurs, the company can already prepare for Y.
With the emergence of the concept of Big Data, even more robust and capable tools are being required to analyze and process this immense amount of information.
What is the importance of predictive analysis?
Today's market is unstable. Various variables arise, different scenarios are created and actions have to be adjusted all the time to adapt to this. This is precisely the importance of prediction: generating knowledge to enable safe and accurate decisions.
With forecasting, it is also possible to optimize the use of resources and identify possible opportunities to increase profitability.
What are the benefits?
In this topic, we'll look in detail at the main benefits of this type of predictive investigation.
Optimize marketing campaigns
One of the effects of this analysis is to improve marketing strategies. After all, with effective predictions on large amounts of data, it's easier to predict customer behavior and reactions, and therefore align marketing actions with them.
Once the company gets to know its consumers better, marketing begins to be more effective in making suggestions and recommendations, for example. This has an impact on the relationship and facilitates public loyalty.
Detecting fraud
It is also possible to perceive risks and fraud with analysis, which can determine the likelihood of this happening. In this way, the company can avoid certain actions or concessions that could result in future problems, favoring business security.
Managing demand and supply
Another major benefit is more reliable management of the relationship between demand and supply, which drives any business. Predictions make it possible to know in which period there will be an increase in demand for a given product, for example, and so the company can prepare for this and align production with customer expectations.
Reducing the risk
Investments in opportunities or specific areas are risky. That's why it's always a good idea to have tools that assess the degree of risk involved and aim to reduce it.
Computer systems can benefit from predictive analysis to see patterns that will help predict threats or malicious attacks, for example. This makes it possible to know the degree of vulnerability in order to implement corrective measures.
In other words, prediction is fundamental to helping companies plan their day-to-day activities and improve internal strategies. But it also favours clarity of information, which generates knowledge for managers and organizes the flow of information within companies, enabling integration between different sectors.
If you enjoyed learning more about predictive data analysis, follow us on social media. We're on Facebook, LinkedIn and Twitter.
Leave a comment
See also:
iT.eam Copyright 2024 - Todos os direitos reservados.
Acesse nossa Política de Segurança da Informação. | Acesse nossa Política de Privacidade da Informação. | Acesse nossa Política Antissuborno e Anticorrupção. | Canal de Ética
[...] can be used for, for example, predictive analysis, which aims to offer forecasts about the future based on correlations of historical data. With [...]