Using Analytics and AI to manage Talent Lifecycle and Employee Attrition
By Joel Stransky, co-founder of Pivotal Talent
It is currently tough for young South Africans to find employment, but for those who are lucky enough to be entering the workplace for the first time, many believe that this milestone marks what is hopefully the start of a long career.
However, the fact of the matter is that a person’s career path begins long before they begin the journey of gaining formal employment. Plotting a career path must start at a grassroots level, when a learner is at the appropriate age and still in the education system, as this is when the foundation for a sustainable career is defined and nurtured.
It is therefore essential that learners are adequately assessed and assisted in identifying the career at which they will most likely succeed and find happiness. Without this early intervention, it’s not uncommon for individuals to pursue a career that is incongruous with their abilities. This is counterproductive and more than likely sets individuals up for failure, and the consequences of a failed and unhappy career can be hugely damaging.
The career-planning process must therefore begin at the earliest appropriate age with the identification of a person’s talents, potential and preferences. This should include identifying attributes such as critical thinking, good judgement and decision-making, and the ability to solve complex problems, along with other key competencies that can predict performance in a potential job role.
This information can then be combined with other factors such as the individual’s interests to inform the subjects that learners select in high school and to guide their tertiary education choices in accordance with their intended career path.
And the ability to adequately identify talent also greatly improves outcomes. Firstly, individuals who pursue a career in a field in which they know they have the potential to excel at and have the innate ability to progressively learn, acquire more advanced skills and improve at their job, are more likely to succeed.
Furthermore, individuals who enter formal on-the-job training programmes or apprenticeships in fields that align with their talents are more likely to excel. That’s because talent is an inherent trait – it cannot be taught. Skill, on the other hand, is an acquired trait that can be developed when talented individuals are given the right forms of education and training.
The key to producing engaged and efficient workers therefore hinges on our ability to align a person’s unique combination of talents with the right industry and job role, and to provide the appropriate education and training, which makes accurate testing and analysis vital.
In this regard, the capabilities offered by artificial intelligence (AI)-based talent management solutions help learners identify the skills they should acquire through formal education and specific and relevant development programmes to shape a career trajectory that plays to their strengths.
AI solutions achieve this by using a predictive model that identifies performance, irrespective of field of study. This could include skill sets, competencies, personality traits, or characteristics and attributes that relate to a specific job role.
This scientific-based predictive model can also be applied to specific workplace environments, using an organisation’s specific cultural and environmental factors to find the ideal fit between a candidate and the company.
These data-driven systems help employers understand the inherent potential in a prospective employee and where their talent and skill set is best suited, and the system can do this better than any other form of psychometric testing or neuro-scientific assessment currently available.
Importantly, the implementation of this technology can be used to break the pervasive practice employed by many companies of hiring based on track record alone, and not considering potential. While this practice is understandable given the uncertainty that accompanies hiring inexperienced job-seekers, technology is capable of taking the guesswork out of finding those with talent and potential. This approach would give more learners an opportunity to secure gainful employment when they leave university.
In terms of its application in the recruitment process, AI-enabled talent management solutions augment the role of Human Resources (HR), rather than extricates them from the process. As such AI, at least in the context of TAMI, Pivotal Talent’s talent management solution, denotes augmented intelligence.
During this process the technology uses the client’s selection data or criteria to accurately inform recruitment procedures. In this regard, the highly predictive scientific model integrates different fields of study, accurately assesses and screens candidates, shrinks shortlisted applicant pools by accurately selecting candidates according to narrowly-defined criteria and matches candidates to specific job roles within an organisation.
Three factors are utilised in this process, namely job tasks, company culture, and specific performance criteria, which can be different across organisations for the same job, in the same industry. All factors are considered to determine the type of person needed, with predictors of performance analysed and tested using a sophisticated algorithmic model.
The AI solution also delivers cost and operational efficiencies by shifting from standardised assessments and testing to a multidisciplinary, automated process that makes more accurate selections, thereby reducing financial losses associated with hiring the wrong person.
By aligning one or more of these factors to specified organisational requirements in the hiring process, companies can also leverage AI to improve workplace diversity. This can be a highly impactful function as recruiting for cultural fit often perpetuates and entrenches a homogenous workforce. This is an important function in a multi-cultural society such as South Africa’s, because by limiting diversity a company stands to miss out on a great deal of potential talent.
However, the application of AI-enabled talent management solutions doesn’t end at the recruitment stage. That’s because successful organisations, regardless of sector, need to do more than merely hire the right people in the right positions – they must continue to invest in their employees to retain their talent.
AI solutions perform this function by using talent retention tools to periodically test and analyse staff using surveys, questionnaires or formal assessments, to track employee performance, satisfaction and engagement.
The information helps to build a detailed profile of each employee, which is used to understand staff wellness. This offers insights into what the organisation needs to provide to keep the employee happy and engaged. With consistent feedback, the system then continues to learn based on engagement, performance and attrition data to ensure continuously improved retention management.
This functionality is paramount in mitigating employee attrition as it gives HR teams the opportunity to identify adverse changes to an employee’s individual profile over time. This could signify a dip in satisfaction, which reduces commitment, or a lack of engagement, which indicates a higher risk of attrition.
Staff attrition has a significant financial impact on a business with added costs such as recruitment fees associated with replacing that employee, the loss of productivity whilst a replacement is sought and up-skilled, and also during the period when the ‘checked out’ employee was not performing at their best.
The changes that are identified therefore enable line managers to rectify the situation with an appropriate intervention that will resonate with the employee. As such, AI talent management solutions can help to mitigate employee attrition to deliver significant benefits to the business.
However, as much the AI engine assists in defining the required actions, it is still up to the HR team and management to implement those appropriate actions to the get the desired outcome. AI in the talent management space is primarily a form of technology that augments the human aspect of HR, but it has the potential to greatly improve the role and effectiveness of HR staff and management within any organisation.