If information is the confluence of data tributaries, analytics is one hell of river!
Imagine for a moment that the vice president (VP) of human resources (HR) schedules a meeting with you, the leader of a talent analytics team, to learn about the effectiveness of an HR initiative called Retain & Grow. The initiative began soon after your technology company acquired a smaller, company for its innovative processes, patents, and deeply skilled engineers. The program is also an extension of a failed program that was designed to stanch the loss of highly talented young employees who come to the company for a couple years of experience and depart for more lucrative jobs with better work/life balance.
Your company is facing a talent crisis, and the VP of HR is coming to you for solutions. She wants to know how you can help her identify high and low performers, identify competency gaps, provide technical skills, increase competencies, increase engagement, and reduce turnover. Her supervisors, the business leaders of the company, believe that improvements in these areas will lead to increased product quality, customer loyalty, improved sales, and increased revenue.
A week prior to the meeting, you spend several hours compiling the information you have about every aspect of the initiative. Your organization has invested heavily in HR technology, so you have access to a large variety of data. The results quickly become overwhelming, so you start to organize the ...