The easiest argument for using data analytics is that they provide you thousands of eyes and ears into your business and your environment. While all this information is available in different systems and sources, Data Analytics is about bringing all these information together such that it is accessible and usable across the enterprise in real-time, with proper security permissions in place. In essence, it is a comprehensive sensory system for your company.
From Hindsight to Foresight
Currently, 96% of organizations use descriptive or diagnostic analytics; however, just a paltry 4% use predictive or prescriptive analytics. One of the reasons for this disparity is that the vast majority of companies use multiple, unrelated tools to manage their talent, which makes it difficult for predictive and prescriptive solutions to glean accurate data.
Prescriptive analytics solutions take predictive to the next level by providing a desired outcome. Rather than relying solely on predictions based on educated guesses and past results, prescriptive analytics provide pattern-seeking machine algorithms that provide resolution.
The goal of prescriptive analytics is to see what the effect of future decisions will be, which helps to adjust decisions before they are actually made.
Need of Data Analytics
- Data centric companies are collecting a lot of data in various ways. ERP, CRM, Social Media (Apis) etc.
- Customer expectations are now at an all-time high and competition is always increasing.
- Businesses are under constant pressure to increase efficiency and improve results.
- Companies are always looking for ways to increase the bottom lines.
- Sleeping data/Raw data is one very big asset for any organization
Using Data, companies can improve their bottom lines: