Artificial Intelligence Application to Staffing

Company: TGRG

Date: 12.12.2019

Industry: Artificial intelligence application to staffing

Tell us about the dangers of not identifying your culture as a company and the damage that the wrong employees can make to a company’s performance?

“Human performance is highly context-dependent, meaning that people perform at their best in a certain environment. This is also the case when it comes to work performance, for example, people who prefer to work in highly structured and process-driven work environments may not do well in a flat organisation structure with blurred communication lines and fluid work processes. If an organisation fails to identify their culture, increasing the chance of hiring people who may look great on paper, but who do not fit in with the work environment. Lack of cultural fit is one of the biggest drivers of employee turnover.”

Historically what are the challenges that companies face in being able to identify the soft skills in an individual or a team and aligning the soft skills of those teams or individuals to companies desired culture?

“It has historically been a challenge for companies to identify skills in general. However, soft skills are particularly hard to identify because they don’t always have a tangible impact that can easily be measured through KPIs or other direct performance measures. This also complicates the process of creating alignment between strategic or cultural objectives and the soft skills possessed by the employee population.  Soft skills are much closer related to personality than for example cognitive abilities, which tend to related to technical skills. The best way to align soft skills and culture is to identify the behaviours the organisation wants to see as a reflection of the desired culture and then map those behaviours into a personality or psychometric framework. It is then possible to do a diagnostic assessment and make any necessary intervention.”

Please tell us about the importance of data science and psychology in the consideration for AI interviews and how does the balancing act work?

“Psychology and data science have a lot in common in the sense that a lot of data science and AI work is rooted in cognitive psychology and neuroscience as well as human behaviour research. Data science is essentially a set of tools based on advanced mathematics that can be applied to the established sciences such as psychology, medicine and so forth. Data science can optimise how we measure and analyse behaviour in the workplace but it cannot explain the reasons for that behaviour. To do so you have to rely on psychological science and research.”

How do AI interviews add more value than interviews without?

“AI technologies have several advantages when it comes to interviews and the recruitment process in general, this platform specifically solves several recruitment issues.

  1. Psychometric questionnaires have used a self-report format that makes it possible for a candidate to manipulate their personality profile. Since the psychometrics on the on this platform operates outside the candidate’s awareness, it makes it very hard to manipulate the outcome.
  2. Traditional job interviews are often hampered by cognitive biases that interviewers unconsciously project unto candidates. An AI algorithm doesn’t care about your gender, skin colour, cultural heritage or whether you share anything in common with the people interviewing you. As such a well-designed algorithm can help eliminate bias.
  3. The recruitment process can often be a long drawn process, consuming a lot of resources. By condensing an interview and a psychometric assessment down to a 20-minute video session, the HR department can save time and money.

Please tell us about the five-factor model – OCEAN and why this is relevant?

“The five-factor model is widely recognised as the most valid and stable personality framework available. Since the 1950s thousands of studies have been conducted across cultures and contexts supporting the universality of the framework. The framework is highly predictive when it comes to understanding everything from eating habits to job turnover. At TGRG we use a modified Big 5 framework that is tailored to be used in the workplace.”

Please tell us about the culture fit that our clients can uniquely create and how the candidate’s soft skills can be used to identify alignment or lack of it?

“As mentioned previously, the fit between an organisations culture and its people is crucial to performance, engagement and employee loyalty. If the organisation understands its culture it can create a unique employer brand which can be used to hire the right candidates. That is candidates whose behaviour will reflect the values of the organisation and fit in with the cultural aspects of the company.”

Let us dive into the body language analytics, what is looked for during the interview? How are people’s movement assessed and what does this mean for an end suggestion?

“The algorithms our platform uses looks at a couple of hundred thousand individual inputs related to the tone of voice, body language and micro facial expressions. All the personality traits we measure have been coded according to changes in voice and tonality, body posture, eye movements, behavioural cues, head movements, emotional expressions among others.”

How about the voice? What is measured? Is it tones? Is it pauses? How do these suggestions provide actionable insights?

“Research has shown that there is a relationship between how we use our voice and our dominant personality traits. Introverts tend to speak more slowly than extraverts, they use pauses more when talking and their voices tend to have a lower volume and less fluctuation than an extravert. When we measure voice we look at several things such as speed, tonal frequency, pauses, variations in volume among others. We have made sure that our model can distinguish between the natural differences in voice tonality between men and women.”

What is the role of machine learning and how does this function add value to the future of AI analytics in staffing?

“Machine learning will continue to play a role in recruitment and staffing, and as the technology matures its impact will only grow. Besides applying machine learning to psychometrics and job interviews, it can be used to identify where the best candidates for certain roles are hired and what their motivations are in terms of work. This can then be used to tailor very targeted recruitment campaigns to similar candidates. It is also possible for recruitment algorithms to work together with larger people analytics solutions to suggest candidates to recruiters before managers need people. By analysing historical turnover data, it is possible to build predictive models about who may leave and pre-emptively create a candidate pipeline.”

Where else do you see AI developing in the staffing process?

“One of the areas I find particularly interesting at the moment is for AI to suggest jobs to candidates. By knowing a candidate’s personality, work interests, values and experiences it is possible to match these characteristics with organisations, teams and managers globally. Any time a job becomes available in an organisation with the culture, manager and team that is the best match for the candidate, he or she will be alerted.”