Before I embark in explaining what is Analytics, as well as the different types of Analytics, let’s just talk for a second about Why Analytics. The field of Analytics was born with the goal of using data and the analysis of that data to improve performance in key business domains, which basically means having the ability to make better decisions, and to execute the right actions based on data insight.
So what is Analytics?
The field of Analytics involves all that is necessary to drive better decision making and add value, such as Data platforms (On Premise, On Private or Public Cloud), Access to Data (Structured and Unstructured), and Tools for Quantitative Analysis and Data Visualization. In other words, Analytics is all about turning data into insight which in the world of business means turning data into competitive advantage.
There are three main types of Analytics:
1- Descriptive Analytics help you understand “What happened?”. The goal of descriptive analytics like the name implies is to describe or summarize raw data and turn it into something that makes sense to the human eye – typically through presenting the data in tables or reports, or in visualizations or charts. They are very useful for understanding past behaviors, and how the past might potentially influence future outcomes. Basic statistics like averages, sums, percent change, or proportions fit into descriptive analytics. This is the simplest form of analytics but nevertheless it is extremely useful and necessary as a stepping stone into more sophisticated/valuable analytics.
2- Predictive Analytics help you understand “What could happen?”. There are two main goals: Finding relationships or patterns and predicting what could potentially happen. They help you try to understand the future while providing actionable insights based on data. Predictive Analytics don’t provide predictions that are 100% accurate, but provide estimates about the likelihood of a future outcome. They can be used throughout an organization to forecast sales or inventories, to detect fraud, to understand customer behavior, or in any scenario where relationships among data and “predicting the future” will help make better decisions. We are all familiar with our credit scores right? That is an example of predictive analytics where historical data on how well you manage your credit is used to predict a score that can then be used as a proxy for how much of a credit risk you might be.
3- Prescriptive Analytics help you determine “What should we do?”. Prescriptive Analytics are all about providing specific guidance about what to do. They make an effort to quantify the effect of future decisions looking at the possible outcomes of each scenario before the actual decisions are made. They use a combination of business rules, algorithms, and modelling procedures to provide possible outcomes. These are typically used in Supply Chain Management, Price Optimization, Workforce planning among others. They are very useful like the name implies to “prescribe” a direction after examining multiple possible scenarios.
In summary, Analytics help you turn your data into insight for better decision making and there are 3 main types of Analytics that you use depending on your goal. Descriptive analytics to understand what has happened in the past, Predictive analytics to understand relationships among data and provide predictions about what may happen in the future, and Prescriptive analytics to provide specific recommendations about what to do in specific scenarios.