With so many businesses relying on analytics to drive their talent choices, evaluations are sure to discover a business case as they are likely to provide impartial and reliable hiring process data, especially in a geographically diverse organization.

Fremont, CA: With the advent of modern technology such as machine learning, artificial intelligence, robotic process automation, gamification, natural language processing, speech recognition, crowdsourcing, social media, and big data analytics, assessments are undergoing a sea of change. These technology solutions profoundly challenge the manners and values of talent evaluations. Some early technological solutions are coming to the market that exploits these new approaches. This seems to polarize believers with non-believers further as the talent appraisal industry demonstrates its correlation with business outcomes and its efficiency and validity.

The solutions for talent evaluation can be loosely divided into solutions for pre-hire and post-hire assessment. The ideal assessment solution must find a balance between its user-friendliness and showing that the user is involved in the evaluation process while also ensuring that the outcomes of such an evaluation process are strongly associated with the output on the ground, thereby being able to justify the investment in the evaluation solutions. However, businesses also tend to use the evaluation systems as rejection tools rather than selection tools. The instrument also has to show that it is free of any prejudice in conducting its duties, and many coordinated players in this space concentrate mainly on this aspect in their efforts to gain a foothold in the industry.

With sourcing and recruitment leading much of the growth for most HR technology players, evaluation systems are more likely to be bundled into the entire sourcing model. The convergence of expertise, culture, and other forms of evaluations combined with the power of social, local, mobile, and AI is likely to radically change how businesses see the task of recruiting the right talent and determining its "fit" with the position and the company.

Many talent assessment solution providers provide data analytics as a service where the association between evaluation data and other parameters of the person, including performance data, is primarily intended to be established. To develop a predictive model, this emphasis on analytical-driven decision-making can only increase the use of evaluations in various sectors and companies.

Although many talent evaluation strategies usually concentrate on profiling or evaluating the employee, profiling or assessing the job background is equally critical. And some of the solution providers have made some progress in this field, but they are still behind in terms of the ubiquity and development of such solutions. This represents a massive opportunity for growth where employers can explicitly build an appraisal ready job background instead of job descriptions that lets them evaluate the "fit" of applicants applying for the position based on multiple scientifically analyzed criteria that go beyond just keyword searches.