Business analytics is quickly turning into a practice that companies need to keep their competitive upper hand. Once a “good-to-have”, business analytics application, specifically predictive analytics, has become mission-critical. Business analytics is a skill that is gaining industry value due to the shorter turnarounds and shorter times for decision making. Gaining insights, foresight and inferences from the unorganised silos of raw transactional data (both internal and external) that many organisations now store (and will continue to store) in a digital format has become a necessity.
Decision Making and Business intelligence versus Business Analytics
Analytics organize data to magnify its value. The power of analytics is to convert large volumes of data into a much smaller amount of information that can be converted into actionable insight. BI mainly compiles historical data ideally in reports and graphs as a means for questioning and drill downs. But reports do not organise data nor magnify its value. They simply organise data silos so they can be consumed.
In contradiction to BI, decision making provides a starting point for analysis. Reverse engineer with the final decision as the central goal. Establish the decisions that make a difference to your organisation and the model that drive those decisions. By understanding the kind of decision to be taken, the type of analysis and its required silo data can be defined.
To keep clarity, BI absorbs stored information. Analytics produces fresh insights. Predictive analytics leverages data within an organisational function focused on analytics and carrying the mandate, proficiencies, and capabilities to drive efficient, faster, decisions and achieve performance oriented goals.
BI tools are simply used to answer primitive questions and categorise these answers into similar silos of information. Business analytics develops complex questions from categorised silos of information. Business analytics then answers these questions through complex problem solving and algorithm design. Finally predictive analytics demonstrates the possibility of probable outcomes based on the algorithms designed to answer these questions.
The application of predictive analytics was once the domain of scientists and mathematical geniuses developing models in their labs akin to solving rocket science problems. However, today it is being popularly adopted by organizations with the a firm belief that businesses will realize and utilize its potential value.
Application of Business Analytics - The Need of the Hour.
Today many businesses do not understand what potential predictive modelling, forecasting, design of experiments or mathematical optimization can bring to the success of the organisation. However, over the coming decade the use of these techniques will decide who stays ahead in the market. This is no different from applying financial analysis and market forecasting to businesses that are listed on highly competitive and regulated marketplaces like Stock Exchanges. Executives, managers and teams that can discern, decode and leverage these assets will lead their games.
"The application of predictive analytics was once the domain of scientists and mathematical geniuses developing models in their labs akin to solving rocket science problems. However, today it is being popularly adopted by organizations with the a firm belief that businesses will realize and utilize its potential value."