Ms Purva, Customer Relationship Manager in a leading service industry, was great at handling customers and ensuring their needs were answered. She always out-performed in her monthly targets. All her team members and peers were happy to be associated with her in any project. The only challenge Purva faced was when she had to submit the report to HR in a prescribed format for their internal analysis and business visualization.

This is a common situation that many face when it comes to an efficient approach to data gathering, analyzing, processing and visualizing. Your data collection process will include attention to all the elements of your logic, what resources were available, what activities you actually provided, how many of each output you delivered and to what degree you accomplished your outcomes. In collecting data, you are likely to use one or more methods. While selecting the best method of data collection, you will consider the type of information you need, the validity and reliability, and how well the method fits your criteria

A well-defined criterion is one that answers all your business queries. In today's fast-paced technological world, organizations are leveraging on AI powered solutions to receive the expected outcome. Data Scientists bring in their knowledge and experience in working with data. The AI applications are fed with data collected from various sources in varied formats. The data is then streamlined and optimized by the AI systems to provide valuable insights on varied aspects of People, Project status, Working schedules, and more. The challenge is to prove the performance and efficiency of these AI-powered insights. A step-by-step development process is the answer to this challenge:

1. Information from various sources in different formats has to be gathered and processed to ensure efficiency in extracting the desired value
2. The various unstructured sources can be limitless - Project Data, Meetings, Digital Identity, Work Schedule, Audit Reports, etc
3. Organization approved AI-powered technical platform has to be leveraged for analysis and visualization
4. The structured business data can deliver a successful BI solution to meet business needs
5. The processed and classified data can be transferred into easy-to-interact dashboards
6. The end result is real-time monitoring of business workflows for better decision making

Having followed the right path of data analysis, Purva has finally got the ready-to-use data that will help her business/HR team to solve critical business issues and foster continuous improvement.