[dropcap size=small]I[/dropcap]magine if your boss could take pre-emptive measures to retain employees who show signs of wanting to leave. Or if companies could get a handle on which potential hires would be the best fit – even before meeting them in person.

Sounds like the stuff of science fiction? Scenes like these are already playing out at some companies in Singapore, where a technological revolution is underway in the usually sedate field of human resources (HR).

While HR departments typically run on gut instinct rather than hard data, a growing number of companies are trying to apply a data-driven approach to managing staff.

Data analytics can help companies decide who to hire, tailor training programmes to suit staff requirements – even predict which employees are likely to leave. The data can come from a wide variety of sources, including employees’ leave applications, key performance indicator reports, email traffic, and social networking activity.

HR practitioners say “people analytics” – as these methods are called – have the potential to create better workplaces, boost employee-employer relationships and improve talent retention rates.

Even as these technologies gain popularity, however, concerns are emerging over the implications for employees’ data privacy.

How are data and technology helping companies manage talent and retain staff? And how far should employers go in their efforts to learn more about employees?

Growing interest

Tech giant Google was – of course – among the pioneers in people analytics. In a bid to “build better bosses”, Google embarked on a plan code-named Project Oxygen in 2009.

The data-mining giant hired statisticians to trawl through performance reviews, feedback surveys and nominations for top-manager awards.

This analysis yielded a list of common behaviours among the best managers: employees value bosses who are good coaches, do not micromanage, and take an interest in employees’ lives and careers, among other characteristics.

While the findings hardly seem earth-shattering, it made a big splash mainly because the insights were backed up by hard data – revolutionary in a field that has traditionally relied mainly on intangibles. Interest in people analytics has exploded in the years since.

HR analytics roles in the Asia-Pacific region have more than doubled in the past 10 years, according to data from professional networking site LinkedIn. It estimates that there are now almost 40,000 HR analytics professionals in the region. And in the Asia Pacific, Australia, New Zealand and Singapore have the highest penetration of data or analytics skills in HR functions, LinkedIn data says. In Singapore, close to half of HR professionals are equipped with data or analytics skills.

Companies are clearly starting to pay attention to the potential that analytics holds for people management. Deloitte’s 2017 Global Human Capital Trends report – which polled 10,400 business and HR leaders across 140 countries – found that 71 per cent of respondents see people analytics as a high priority in their organisations.

Recruiting is the No 1 area of focus, followed by performance measurement, compensation, workforce planning and retention, the report found.

“The types of decisions that can be made using data range from micro decisions like how to recognise staff and how often, to enterprise-wide considerations like whether or not to downsize a particular division and the likely impact on productivity,” says Leong Chee Tung, co-founder and chief executive of employee engagement platform EngageRocket.

The startup, which has worked with companies across a range of industries including construction, food and beverage, retail and financial services, has developed a cloud-based software which allows clients to analyse employee feedback in real time.

The technology gives managers an instant snapshot into their organisation’s health and allows them to take immediate action – for instance, improving their leadership styles or work environment, Mr Leong notes.

Companies can also layer information collected from these surveys on top of other data – for example, metadata from emails and in-company chats – to come up with various predictive models. These can be used to measure, for instance, the likelihood of an employee leaving the company – someone with an eye on the door might take more vacation or medical leave than average, or be less engaged with employee training programmes.

Privacy concerns

While the technology enables employers to track nearly everything employees do, the question that immediately arises is whether they should. Shades of Big Brother surface when we open the doors to surveillance of communications – from both within the office and without.

HR practitioners say companies must have a clear sense of what they hope to accomplish when they collect employee data. They also need to be forthcoming and transparent in their communication with employees.

“The trust between employee and employer cannot be breached,” says Lee Yan Hong, head of group human resources at DBS. DBS launched a digital overhaul of its HR operations in 2011 and has since started using big data to boost staff productivity, reduce attrition rates and recruit more effectively.

Among sales staff, for instance, the bank started tracking more than 200 factors – including training, leave patterns, pace and quantity of salary increases – to suss out which employees are at risk of packing up and leaving. Those at risk are flagged to managers, who can then sit down with them to find out what the issues are – salary, training or even just a lack of tender loving care.

OCBC too made a push in 2015 with similar goals – to help the bank retain talent and improve its recruitment process.

Jason Ho, OCBC head of group human resources, notes: “HR is seen as a function related to people and is usually based on experience and relationships. But data analytics helps to enhance and validate the information we get from the ground so it’s no longer just a qualitative discussion. It’s more objective and helps us make better decisions for colleagues in the organisation.”

OCBC uses data analytics to identify potential staff departures, customise training programmes, and make its executive recruitment process more efficient. The bank uses a dynamic dashboard with colours like amber and green, tracking a candidate’s progress along the recruitment pipeline. The system can also identify if hiring managers are taking too long to process an application or if information is missing from the candidate’s application.

United Overseas Bank uses data analytics for similar ends, and equips its HR staff with basic analytics skills through training and workshops.

The bank has also created an analytics dashboard for HR staff across various markets. “This will help them to draw insights on the status of hiring, attrition, performance, compensation and promotion and to help them in their decision-making on the ground,” says Jenny Wong, head of group human resources at UOB.

For instance, the bank’s data showed that within their first two years of working at UOB, many staff in Singapore who hold diplomas opt to pursue university degrees part-time. In response, the bank introduced the UOB Learning Journey Programme, a job rotation plan which allows staff to take on new assignments ranging from six months to a year, after which the employee can choose to remain in their new role or to return to their original one.

“In addition to deepening cross-team collaboration and understanding, this programme has improved talent retention by up to 5 per cent, while lateral transfers to other roles among branch employees have also doubled,” Ms Wong notes.

For these companies, the results of their “people analytics” show clear benefits. But they are careful to point out what they are doing to address the cost – the potential invasion of privacy.

DBS’ Ms Lee notes that a significant amount of HR data – including salary and performance information – is confidential and only a few are authorised to see it.

Should the bank want to start a new project that involves closer monitoring of employees, for instance, tracking their emails, permission must be sought from staff, she says.

“So far, this is not something we have tried. But if we want to experiment with something and look for patterns… we have to ask permission from employees and explain to them what we’re doing. We’re very clear about that.”

OCBC’s Mr Ho agrees: “We are mindful of the sensitivity and confidentiality of data. All the information we use is data that is readily available. We’re not looking at individual employee behaviour. Also, access to our database is tightly controlled and managed.”

In addition to complying with local laws and regulations related to the gathering and use of employee data, employers should also take measures to safeguard personal data in their possession against the risk of cyber-attacks, says Mayank Parekh, Institute for Human Resource Professionals chief executive.

(RELATED: Data protection firm Acronis’ head honcho gives tips on cybersecurity steps to take)

When it comes to companies deciding how far they should go in monitoring or predicting staff behaviour, EngageRocket’s Mr Leong says ethical arguments are still catching up with technology.

“Where the boundary is drawn between what an employee does on company time versus in their personal lives is getting fuzzier than ever,” he notes.

“I’d say that this boundary will be different for each company, but as a broad rule of thumb I’d say that as long as a company CEO is comfortable having the monitoring measures published on the front pages of a reputable publication like The Business Times, the measures are respectable and within boundaries.”

Lack of usable data a key challenge

Given the resources required, it comes as no surprise that financial institutions are Singapore’s people analytics pioneers. In practice, however, many HR departments are still struggling to implement such technologies. Adoption of people analytics among Singapore companies remains low, says Victoria Bethlehem, Asia Pacific human resources head at the Adecco Group.

“Typically, companies have some form of system in place to collect HR data for operational reporting. The challenge lies in shifting the focus from using the data tactically, to analysing it and using it in a more strategic manner, such as long-term planning, driving business performance and producing predictive models,” she notes.

Many existing HR systems and tools are not geared towards gathering usable data, says Mr Parekh.

Ms Bethlehem adds: “At many companies, HR data is either not well captured or not well managed. HR data may be incomplete, scattered, unstructured and disconnected from the rest of the business data.”

Mr Leong of EngageRocket says: “Building the data infrastructure within a company isn’t an easy task unless you have your own data science team in HR that can harmonise the data and run analyses on it.”

Small and medium-sized enterprises (SMEs) in particular could find it an uphill task. Fion Ngiam, a lecturer at Nanyang Polytechnic’s School of Business Management, says: “Many local companies, especially the smaller companies, may still be more concerned about meeting the daily operational demands, and may not have the resources and skills to implement structures to support HR analytics as this can be very time-consuming and complicated,” she notes.

Even larger firms could find it challenging to make the most of their HR data. “While the companies may have implemented some form of human resource information systems, they are lacking in the ability to effectively analyse and interpret the wealth of data residing within HR,” Ms Ngiam says.

Still, while data can be helpful, there is only so much it can do, says OCBC’s Mr Ho.

“Data lacks empathy. We cannot use only data to drive our decisions, we still have to be human in the way we look at human resources.

“We can use data to improve productivity and facilitate decision making, but it’s not the ultimate factor that we consider, it’s just one reference point,” he notes.


Hiring staff with the aid of a bot

A chatbot will soon be helping DBS screen some of the 300,000 candidates applying to the bank for a job every year.

The bot is just one tool DBS is employing in its bid to automate the tedious process of recruitment by using data analytics.

(RELATED: How corporations are tapping artificial intelligence for the future)

One of the early stages of the bank’s hiring process requires candidates to complete a quiz, which susses out their personality traits and personal qualities. The results from this quiz – called a predictive index – are then matched against an “ideal” profile for the role they are applying for. Candidates have to fit the profile before they move on to the next step in the hiring process.

Along the line, candidates could also be required to answer questions posed by a chatbot from April onwards, says DBS head of group human resources Lee Yan Hong.

The chatbot assigns scores based on their responses, as well as the competencies and work experience portions of their resumes – for instance, whether or not they have founded a startup.

This push to automate hiring is part of a wider overhaul of the bank’s approach to HR, Ms Lee says. These efforts, which started in 2011, have helped save DBS over 600,000 manhours, she adds. The bank’s HR team now includes four data scientists.

One of the biggest initial challenges was creating a “data lake” – a massive collection of employee data used as the foundation for all HR analytics projects. “The process took a year and was very painful,” says Ms Lee.

The “lake” includes data on employee compensation and benefits, demographic data such as marital status and children’s ages, as well as data on performance and day-to-day operations like the number of calls made by salespeople.

The bank has since collected 700 data points on each of its 10,000 employees in Singapore and hopes to complete similar endeavours in all of its other markets by this year.

Its first big-data model in 2014, code-named Project Marvel, helped identify problems – and potential outcomes – among a particular group of sales staff. For example, those who take frequent leave in the early months of the job are likely to quit, as are those who are not driven to take up more training.

The study also found that sales targets were pitched too high – which discouraged some new joiners – and that staff were taking longer than the three-month probation period to settle into their new roles.

In response, changes were made to the recruitment and candidate screening process. The probation period for sales staff was also extended to six months and sales targets were made more achievable.

Following the success of its early data science projects, Ms Lee’s department will be delving deeper into details – for instance, aiming to improve retention among employees from polytechnics, the segment with the highest turnover rates.

But using data to identify a potential problem is only the start. The real challenge lies in implementing solutions, Ms Lee says.

“Operationalising and deploying is the difficult part,” she notes. Some managers were hesitant about the predictive index, for example, because they didn’t think they needed to use big data to hire the right people.

“But when they saw that those who did not pass the predictive index all eventually left, they were convinced.

“Change management is not easy, we need to distil it down to a story, so people know how it impacts them and what they need to do.”


Public sector gets into the act

Technology is revolutionising human resources not just in the business world but also in the public sector.

The Singapore Land Authority (SLA), for instance, has turned to drones and virtual reality (VR) to give its recruitment efforts a boost.

In a bid to draw crowds to the statutory board’s booths at recruitment events, its HR department used drones and VR technology to create a video clip showcasing three of the state properties it manages.

“SLA doesn’t usually ring a bell with the man on the street because the work we do doesn’t really touch many people on the ground, so we wanted to give a unique experience to the people who visit our booth during career roadshows,” says director of human resources Er Chye Har.

The video clip is viewed through a VR headset. A total of 500 VR headsets have been made. The 2016 project was a HR team effort and cost less than S$5,000 in total.

“The vendors we approached were surprised that they got a call from HR – usually it’s marketing that will produce such videos,” says Ms Er. “The first time we brought the VR headset out, it drew a lot of crowds to our recruitment booth, which motivated us to do more tech-related projects.”

SLA’s HR team has also launched a number of other tech-related projects, including a mobile app game in 2016 used to induct and train new staff. New joiners play games on the app to learn about the organisation, and the games earn them points which can be redeemed for rewards and prizes.

“As we implement these technologies we are also mindful that we should not lose the human touch,” notes Ms Er. “Our HR induction programmes are high tech but also high touch. We incorporate some segments which require face-to face-interaction.”

For instance, one game in the app calls for new hires to take photos with members of the management team.

In 2016, SLA’s HR team also developed a separate mobile app which allows staff to access a range of HR services on the go, including transport claims submissions and vacation/medical leave applications.

The range of services available on the app will keep growing, Ms Er says. The app is also being scaled up to benefit other agencies in the public sector.


This story was originally published in The Business Times.

BT Photo Illustration: Simon Ang