Employee attrition? Not if AI can help it
IBM’s artificial intelligence platform Watson can zero in on employees most likely to quit. Bibhu Ranjan Mishraand Debasis Mohapatraon how AI is transforming human resource practices
IBM’s artificial intelligence platform Watson can zero in on employees most likely to quit. BIBHU RANJAN MISHRA & DEBASIS MOHAPATRA on how AI is transforming human resource practices
Sometime last year, technology giant IBM launched an artificial intelligencebased pilot programme at its India unit to identify employees most likely to leave the company. It planned to use the information to take counter measures to try and retain them. The programme, called “predictive retention”, was conducted in two key divisions — services and infrastructure — which employ the bulk of its staff in the country.
As a result of the project, the company managed to reduce attrition rate in the sample group by two to three percentage points. Thanks to its success, IBM is planning to roll it out across all its divisions in India this year, before taking it to its units worldwide. IBM, or the Big Blue, as it is called, has 150,000 employees in India, which makes it the largest global IT employer in the country.
“We did this pilot in our services and infrastructure businesses, which account for 80-90 per cent of our total employee strength in India. After running the pilot, we have seen a dip in attrition by 2-3 percentage points,” says Chaitanya Sreenivas, vice-president and head of human resources for IBM in India and South Asia. “We are going to use it for the whole organisation now. And in another six months it will go global,” adds Sreenivas.
Watson, IBM’s cognitive and artificial intelligence (AI) platform, has found applications in healthcare, agriculture, weather prediction and even financial services. But this is the first time that it is being applied in the human resources (HR) space, including in employee hiring, retention, skilling, training and studying of behavioural patterns.
“With predictive retention, we can find out which employees are at risk. We can see their current skills, performance, engagement levels based on sentiment and aspiration analysis. This technology can tell you that out of 10 reportees, three are at the risk of leaving, so go and talk to them,” says Sreenivas.
Indeed, the HR domain as a whole is looking at personalised automation which can enable it to act in a predictive way. This is especially so in the case of the IT sector, which is one of the biggest employers globally and in India.
AI is changing HR, agrees Sreenivas. “We are using Watson, which is collating a lot of data from different places and bringing it together. This helps the HR manager take better and faster decisions. They can also take proactive measures from these insights,” he says.
According to the IT major, the use of the Watson platform has also made talent acquisition much more accurate and seamless. Watson helps match candidates according to job profiles, skill requirements, previous success stories and so on. In fact, HR managers are able to evaluate double the number of profiles for a specific job role with the help of AI than they could previously.
The platform is also helping IBM gauge a candidate’s interests, which in turn allows HR managers to design a job role matching his or her strengths. For example, fresh graduates from colleges can indicate their likes and dislikes and the sourcing manager can put them in a role matching their skills and aspirations. Even project managers are taking better decisions when it comes to retention, appraisal and reskilling with AI-enabled insights.
Industry analysts say one reason IBM is applying AI tools in its HR process is that the biggest raw material or input for any predictive analytics tool is data. HR provides a data-rich environment with a wide variety of data readily available from sources such as the HRIS (human resources information system), payroll and other systems which can be supplemented with personal identification information from social media, the internet and so on. All these provide the core data asset in which AI can flourish and add value.
“The AI pilot to identify employees who are at high risk of leaving the company is a great example of the way AI algorithms can combine predictive models with observed human behaviour to significantly reduce turnover for critical employees,” says Peter Bendor-Samuel, founder and CEO of research firm Everest Group. “Given IBM’s scale in India and its heavy use of highly skilled and mobile talent, it makes sense that they have piloted this in the Indian market. The learning from this and the resultant AI platform will be a highly attractive product which they can take to the global market,” he adds.
Other than hiring the right people for a job, predicting attrition and doing sentiment analysis of employees, IBM is also using Watson to improve employee engagement, map their skillsets and learning ability and enable them to take reskilling decisions. It has developed an AIbased cognitive learning platform called “YourLearning” which provides a personalised learning experience to each employee by mapping their profiles along with analytics such as their social media record. The mapping of the skillsets of every employee enables the platform to suggest internal job postings which match their needs and aspirations.
“A massive enterprise-wide transformation is happening around skills and training. Earlier, training used to be ‘one-size-fits-all’. Now, new technologies are being leveraged and training is becoming personalised and customised,” explains Sreenivas.
But it is not just about the effective use of technology — it is more about organisational change, points out Tom Reuner, managing partner, business operations strategy at HfS Research. “The use of AI in HR, especially in predictive retention, is probably missing the really challenging question: How digital and AI are changing the way we work?”
That AI is changing the way we work is beyond question. What remains to be seen is whether it throws up any significant downsides on the way.