A high performer can deliver 400% more productivity than the average performer.And as organizations today sail through multiple paradoxes to survive in this fierce competition; they are investing considerable time and resources to build world-class capabilities in their employees and they are also hiring outstanding talented employees. However, research suggests that one in five high performers intend to leave their companies in next six months.

However more often than not, high performers in one organization fail in another organization, even if it is the same size and/ or the same industry. Does the recruitment process have shortcuts that cause this to happen? Do resumes and interviews uncover clues regarding a candidate’s fit for the role and the culture of the company? 

While sometimes, the stepping stone to hiring the right candidate may not be correct, the business context post hiring makes the high performers take that extreme step. Let’s look at 3 common mistakes that lead to failure of high performers and also the workable solutions to solve them:

Mistake #1: Businesses are contextual but the hiring process overlooks this

As one of my closest aides says, “All seeds don’t grow in all soils”. The statement captures what global leaders understand very well, but still, the bias of getting a high performer from another company builds an aura of human bias which even the most adept functional and line managers fail to realize.

Solution: An ideal way to overcome the bias during selection is to use technology which will maintain a flavor of consistent objectivity. Moreover, now such technology solutions use AI based contextual analytics which analyzes applicant resumes and other social data contextual to business needs. These technologies place greater emphasis on predictive analytics using Talent Science rather than on past performance, making them a great recruitment asset.

Mistake #2: Feeling of caught in a ‘set-up-to-fail’ situation

According to a recent Forbes report, new employees feel lost in the shuffle when managers/seniors move them over for new projects irrespective of whether they are enjoying what they are currently working on or not.For talented innovators, this is often the primary reason for leaving a new organization, as it dampens their desire to contribute while having a voice in the process. The newcomer eventually feels caught in a ‘set-up-to-fail’ situation as a vicious cycle of withdrawal and confusion sets in and performance suffers.

Solution: The best solution to this mistake is to keep employees motivated by giving them opportunities to shine. When managers become aware of both the skills and strengths of employees, they are better able to engage and empower less productive employees, while retaining the enthusiasm of their top talent.

Analytics today can help map competence data to understand skill gaps, plan resources allocation/training and job rotations even across locations based on skill insights. HR managers can engage employees usefully and forge mentor-mentee relationships. Analytics, therefore, can help in increasing revenue/employee and optimize human capital deployment.

Mistake #3: Ineffective performance reviews

Another common mistake prevalent in most of the organizations is the failure to conduct periodic in-depth performance reviews that offer constructive evaluation and encouragement as well as explore future career avenues within the company for the employee. In a research by psychologists A. Kluger and A. Denisi, they conclude that at least 30% of the performance reviews end up in decreased employee performance. The performance reviews very soon become a tick in the box due to the paucity of time.

Solution: Moving beyond the limited tactical capability of most HR automation systems available today, contextual analytics has the ability to pinpoint, train and empower an employee with additional responsibilities, especially if within the context of a different corporate role, such as a promotion to supervisor or higher. It can help in suggesting which specific training employees need to prepare them for their new roles and also any upcoming organizational changes/restructuring. Such methodologies also place the power back in the hands of the employees to track their professional journeys within the company.

In this age of data science and machine learning, successful organizations are hacking their way to be predictive and prescriptive in nature by using AI to understand their talent pool in-depth.