Descriptive, Predictive, Prescriptive…Oh my!

If you search for the definition of analytics, it comes out something like this…Analytics is the systematic computational analysis of data or statistics.  Let’s add to that… which is used to interpret and/or communicate patterns in data.  There, that makes it much clearer.  Doesn’t it?  Analytics turns patterns and data into information that can be used to inform decision making. 

There are 3 main types of data analytics that are used in business to make sense of the mountains of data that is collected – Descriptive, Predictive, and Prescriptive. 

• Descriptive analytics is the interpretation of historical data to show what has happened in the past. Used by 90% of organizations. An example, summarizing sales or operations data. 
• Predictive analytics uses the findings from Descriptive analysis along with additional algorithms and machine learning to find trends to go beyond what happened to what might happen in the future. Uses include answering questions such as what will happen next if x condition is met or what if the existing trends continue?
• Prescriptive analytics builds on both descriptive and predictive analytics using historical data, trends, and algorithms to forecast what may happen in the future and or to predict the likelihood of a specific outcome.  It is often used in a credit scoring or to identify trends in retails sales and customer behavior.

Each type of analysis has a place in a business workflow depending on the maturity of the business. Each type builds on the last, becoming more complex, but increasing the value that each has a use in the decision-making process.