PaaS extensions, robotic process automation, predictive analysis and artificial intelligence will help HR ensure a great workplace experience in the future – PwC.
CHROs now have a wide range of technologies to help them drive efficiencies and insights for the business. Some have particularly been in the limelight this year, and promise to lay a stronger foundation for the future of HR. A report released by PricewaterhouseCoopers, lists out four technologies and the opportunities they provide that HR leaders cannot afford to miss.
PaaS extensions
Fragmented tools and solutions are now passé. A seamless experience is possible only through a single integrated platform, which is like a one-stop-shop allowing employees an easy access to everything that they need to work efficiently. Processes that require a manual work-around or ‘one-off’ application can now be automated and integrated as an extension of a cloud application, using PaaS extensions.
While the survey found that only 16 per cent of HR cloud customers are taking advantage of this today, PwC predicts that the development of HR functionality extensions using PaaS (platform-as-a-service) will play a role in nearly all projects, as more and more large enterprises—with unique and complex needs—adopt cloud technology.
Robotic Process Automation
Robotic Process Automation (RPA) is a software that lays the foundation for machine learning and future applications of artificial intelligence (AI). Where rules and logic can be applied, the software can conduct a task with far greater efficiency and with fewer errors. RPA is relatively easy to deploy and particularly useful for HR tasks related to the processes that span multiple systems.
For example, the action of on-boarding, transferring, or off-boarding an employee may trigger process steps in benefits, payroll, identity management and up to 50 other systems. An RPA application can be programmed to activate these steps to increase efficiency.
To maximise value with RPA, a few key implementation principles that HR needs to keep in mind are: Choose processes that maximise productivity or are front-end processes that would benefit from a reduction in human error; automate as much as possible; and aim for 100 per cent auditability.
Predictive analytics
Anything predictable is certainly easier to prevent, and proactive measures are always best when it comes to managing attrition. Reducing attrition by just one per cent in an organisation of 5,000 employees with an attrition rate of 10 per cent can save approximately $3.75 million. And that’s just one use of predictive analytics.
Building the statistical models to predict an outcome is a relatively easy task. What’s more difficult is the behavioural change needed to act on the predictions. Testing each model is important too. PwC says, pilot studies should be undertaken to review the validity of predictions against actual behaviour. Predictive analytics is a largely untapped opportunity today. According to the survey, only 24 per cent said predictive analytics is a priority for next year.
Artificial intelligence
Business leaders agree that AI will be a key contributor to gaining business advantage in the future. Applications in HR can range from avoiding gender bias in recruiting to predicting turnover or profitability through sentiment analysis of call records, social media data or other internal data. Most HR software vendors will soon release products that will help hiring managers decide which candidates to pursue for a given job, and what attributes in their profile might be a good fit. They’ll even suggest what interview questions to ask. AI will be able to do this by analysing the data of employees, who are already successful in the company and comparing their attributes with those in the candidate pool.
For the report, PwC had surveyed 307 organisations from over 30 different industries headquartered across 40 countries. The size of their workforces ranged from fewer than 1,000 employees to more than 300,000, and revenues ranged from less than $500 million to $5 billion-plus.
