How to hire using big data, mobile & cloud channels
6 step guide for global recruiters.
The future of work is under-going a radical change. Mobility, analytics, big data and machine-designed talent is driving the workplace narrative. Here’s a 6-step snapshot:
This century, it’s not the 9-to-5 office that’s driving demand. The future is supported by an “open talent economy” that taps into on-demand and on-tap talent, predicts the industry tracking firm, Deloitte.
The company’s comprehensive March report, Human Capital Trends 2015 says that an on-demand workforce enables companies to tap into extensive global networks. These include innovators, technical experts, and seasoned professionals.
This report draws on surveys and interviews with more than 3,300 business and HR leaders from 106 countries.
Talent management tools leveraging “people data,” analytics, and machine expertise is in play. Analytics address complex business and staffing needs, and offer deeper insights into the best fit for the job.
Moreover, social media helps build a more detailed profile around talent acquisition. These profiles go beyond standard-issue resumes or one-size-fits all recruitment profiles. This intelligence taps into the more personalised online posts, tweets, chats, or hangouts.
The barriers between work and life blur. Staff are “always on” or hyper-connected to their jobs using mobile apps.
Among the trends
1. People “on demand”
Companies are more sophisticated around how they manage all aspects of workforce planning. This includes the hourly, contingent or contract labour.
But to engage and retain staff, executives need a rethink about outdated HR programs and strategies. Moreover, analytics comes into focus to assess and manage full-time, contingent or part-time workers.
2. Potential of analytics
Despite the potential of analytics, few organisations are actively implementing analytics’ capabilities to address complex business or talent needs.
A more serious investment is needed to leverage data and make more clearly-defined “people decisions.”
People analytics, a strategy that’s evolved over several years, changes the dynamics around managing staff. But the potential of analytics is not fully-realised and organisations remain slow with embracing change.
3. Data everywhere, but is this clean?
Business can build on data strategies by harnessing and integrating third-party data about people. This is tapped from social media and digital channels.
“The explosion of external people data (data in social networks, recruiting networks, and talent networks) has created a new world of employee data outside the enterprise.”
It’s important to learn to view, manage, and take advantage of this data to better recruit, hire, retain and develop leadership.
4. Machines make decisions
Increasingly, computers and software automate and replace knowledge workers. This challenges organisations. They need to rethink how work is designed, and the skills needed for staff to get ahead.
The machine talent incorporates “cognitive computing.” This involves using machines to read, analyse, speak, and “make decisions.” This impacts work at all levels, and many jobs are being phased out.
5. Integrate technology and people
HR technology is a growing market, but the promise remains largely unfulfilled. There’s also a widening gap across areas like learning and development, engagement and culture, or leadership.
HR technology investment is critical. This market has grown by 50 percent into a US $10 billion industry over five years.
“But when it comes to critical issues like learning, engagement, and the work environment, HR organisations have not transformed fast enough.”
6. Why HR needs a makeover
Once a compliance function, HR needs to be agile, better integrated with business, data-driven, and deeply skilled around the ability to attract, retain, and develop talent.
HR technology platforms offer integrated systems and better access to data. This includes analytics and the science of assessment.
However, managers struggle with optimising analytics. Moreover, data quality is often a problem when it comes to information about people. Teams can enlist IT support early on, to build a program that cleans, rationalises and monitors the quality of data.