PricewaterhouseCoopers earlier this year released a report titled “What’s now and what’s next in human resources technology.” The report was based on a surveyed 307 organizations from more than 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.
From the research, PwC came up with a list of these four hot digital HR technologies:
1. PaaS extensions: While the survey found that only 16% of HR cloud customers were taking advantage of this today, we predict 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. As an example, one of our clients had a unique “team award” process where team members could nominate themselves and others, with a supporting business case, for monetary year-end awards. The process provided for numerous opportunities for approvers to review and revise before the final sign-off. Since this functionality was not part of the delivered cloud compensation application used by the organization, PaaS was used to build the needed functionality. A process that was going to require a manual work-around or “one-off” application can now be automated and integrated as an extension of the delivered cloud application.
2. Robotic Process Automation: Robotic Process Automation (RPA) is software that lays the foundation for machine learning and future applications of artificial intelligence. 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 is particularly useful for HR tasks related to the processes that span multiple systems. For example, the action of onboarding, 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 trigger these steps to increase efficiency. To maximize value with RPA, a few key implementation principles need to be kept in mind: Choose processes that maximize productivity or are front-end processes that would benefit from a reduction in human error; automate as much as possible; and aim for 100% auditability.
3. Predictive analytics: If you can predict voluntary attrition, you can prevent it. Reducing attrition by just 1% in an organization of 5,000 employees with an attrition rate of 10% can save approximately $3.75 million. And that’s just one use of predictive analytics. Building the statistical models to predict an outcome is the relatively easy task. More difficult is the behavioral change needed to act on the predictions. Testing each model is important, too. Pilot studies should be done to review the validity of predictions against actual behavior. Predictive analytics is a largely untapped opportunity today. In our survey, only 24% said predictive analytics is a priority for the next year.
4. Artificial intelligence: Business leaders believe that AI will be a key contributor to gaining a 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 analyzing the data of employees who are already succeeding in the company and comparing these attributes with those in the candidate pool.
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