Using Analytics for Better Decision-MakingHarshdeep SinghBlockedUnblockFollowFollowingDec 1<a href=”https://www.freepik.com/free-photos-vectors/calendar">Calendar image created by Rawpixel.com — Freepik.com</a>The amalgamation of an increasingly complicated world, the vast proliferation of data and the pressing desire to stay at the forefront of competition has prompted organizations to focus on using analytics for driving strategic business decisions..Rather than “going with gut” when maintaining inventory, pricing solutions, or hiring talent, companies are embracing analytics and systematic statistical reasoning to make decisions that improve efficiency, risk management and profits.Data and analytics are disrupting existing business models and ecosystems..From using granular data to personalize products and services to scaling digital platforms to match buyers and sellers, companies are using business analytics to enable more faster and facts based decision making..Advanced statistical models are furthering this cause by providing valuable insights out of unconventional data sets and by enabling companies to explore new business territories..Therefore, business analytics enables managers to gain competitive intelligence on market conditions, target consumers more successfully and optimize processes.Using data to drive performance:While organizations spend considerable time analyzing consumer data and frontline monetization opportunities, it is equally imperative to focus on improving productivity and performance..Managers need to see risk analytics as an enterprise-wide approach and should develop ways to pull data across different organization levels and functions into one central platform..By establishing a standard baseline for measuring and managing risk, companies will be able to incorporate risk considerations into their core strategic decision making process and predict likely scenarios.Banks are leading this analytical space by discovering new ways to exploit transactional and behavioral consumer data..By capturing such massive data sets, banks are able to increase the accuracy, reach and predictability of their credit risk models..By becoming more risk intelligent, managers will be more adept at dealing with uncertainty and strategic at decision making.The conclusion:In this volatile environment of data driven disruption, business managers need to look through two lenses at the same time..By embedding data analytics into their core strategy, business managers can streamline internal business processes, identify unfolding consumer trends, interpret and monitor emerging risks, and build mechanisms for constant feedback and improvement.. More details