Data Analytics: New Edge for Success
Digitizing the Enterprise by Leveraging Analytics and Modern...
Promise of Data Analytics
Business and Data Analytics to Achieve Productive Outcomes
Data as a Business Resource
Jamie Adams, CIO, Mspark
Data Analytics - Centralized or Decentralized?
Kim Wienzierl, Director of Data, Radio Systems Corporation
Tailoring Customer Experience
Abdel Rahman Ismail, Director of Ecommerce, Technology & Performance, Gourmet Egypt
Leveraging Data to Transform Business
Tanaquil Arduin, Msc Mpa, Chief Data Officer, Head Of The Centre Of Expertise For Data, Municipality Of The Hague
Thank you for Subscribing to CIO Applications Weekly Brief
Uses of Data Analytics in Digital Transformation
Advanced analytics are designed to become smarter, and thus, insights generated will become more precise and resilient for improved business decisions.
Fremont, CA: Digital transformation is a continuous process that companies need to follow to stay competitive. Analytics allows organizations to track the condition of their business at any time. The insights obtained from the analytics can help managers take the right actions to enhance business performance.
Making decisions supported by data is essential in digital transformation. Business data are vital when it is sorted, processed, and analyzed. Advanced analytics are designed to become smarter, and thus, insights generated will become more precise and resilient for improved business decisions.
Here are three uses of data analytics in digital transformation:
Enhance Sales Pipelines
Shorter sales cycles allow salespeople to improve their sales volume. But some deals take a longer time to close, which can be worth more in terms of profit.
Salespeople can enhance their efforts to increase sales volume and value with the help of Customer Relationship Management Systems (CRMS). CRMS are digital tools that enable the sales team to monitor every step of the sales process. It can provide users lead scoring features to evaluate the potential of conversions and value by analyzing past data and prioritizing leads with higher scores.
Simplifying Supply Chain Processes
Data Analytics is the backbone of the Just-in-time (JIT) systems as it allows companies to enhance every part of their supply chain with precision. JIT systems enable staff to monitor stock levels in real-time and automate the process. It also reduces inventory costs by resolving underproduction and overproduction problems.
Predicting Consumer Behavior
Advanced analytics can help enhance predictions. As machine learning models obtain more data, it can learn the scenarios multiple times and improve the prediction of the probable result.