Big data is watching


There are few workplaces that appear more unpredictable than the emergency department of a major hospital. But thanks to the Patient Admission Prediction Tool (PAPT), developed by the Australian E-Health Research Centre, the Gold Coast Hospital is now able to predict its daily workload with an accuracy of 94 per cent, and make rostering decisions accordingly.

The secret lies in the science of data analytics. And it has applications across a broad swathe of HR activities. According to the director of access and flow at the Gold Coast Health Service District, Dr James Lind, the traditional model for a hospital is to book in elective surgery and hope its emergency workload can fit around these bookings.

“We’ve turned that on its head and said the most predictable stuff is the emergency stuff, analysing and deriving value from the vast stores of data that many organisations hold, often in real time.”

Causing drop-outs

One of the most common applications of Big Data analytics is in highly structured environments such as call centres. The vice president for human capital management for APAC and Japan at US technology company Oracle, John Hansen, says his company has been using Big Data techniques to analyse the attrition rates at the call centre of its client Xerox.

Oracle’s technology matches different data points to indicate early signs that a worker might be considering leaving. Xerox can assess the contribution of that worker and implement programs to encourage them to stay.

Several Australian universities are using similar techniques to monitor student behaviour and alert administrators to early signs that a student may drop out.

According to IBM’s sales manager for business intelligence and advanced analytics, Alan Morgan, through working with one university his company uncovered some very different predictors of dropout rates than what the university had previously been monitoring.

“We were able to show using predictive analytics that it was another set of variables – a much wider set of variables – that caused [dropouts],” Morgan says.

This can be directly applied to workforce management. German software maker SAP’s national director for business analytics, database and technology in Australia and New Zealand, Ryan Blackwood, says Big Data can deliver a full view of an employee: “Not just their opinion and not just what is on paper, but how they are performing, so that we can identify ahead of time if there is a decline and take action before the employee has performance issues,” Blackwood says.

Identifying talent

With Big Data analytics, the more data that is fed in, the more useful it becomes. This can include everything about an employee from where they were recruited and their level of experience through to training, performance, and any other data recorded against them.

Oracle’s Hansen says by analysing the right data in the right way, it also becomes possible to identify top talent in an organisation.

“The opportunities are endless because we can look at the entire employee life-cycle,” Hansen says. “We need to understand that so we can identify those parts of the workforce that will be the longer-tenure employees we want to develop, and replicate that.”

Big Data can also assist HR departments in ensuring that their organisation is complying with staffing regulations.

But despite the promise, industry watchers agree that Australian HR departments have been relatively slow to embrace Big Data.

According to John Macy, founder of technology consulting company HR Cloud Solutions, HR has generally performed poorly when it comes to managing its data.

“Because HR people really don’t get involved themselves in the day-to-day data collection processes, they don’t really understand what’s available in the database,” Macy says. “And it is very rare that you would get an HR department that would devote a person to a data management job.”

Hansen agrees that most HR departments still lack the business-analysis skills to effectively design and implement Big Data programs.

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Big data is watching


There are few workplaces that appear more unpredictable than the emergency department of a major hospital. But thanks to the Patient Admission Prediction Tool (PAPT), developed by the Australian E-Health Research Centre, the Gold Coast Hospital is now able to predict its daily workload with an accuracy of 94 per cent, and make rostering decisions accordingly.

The secret lies in the science of data analytics. And it has applications across a broad swathe of HR activities. According to the director of access and flow at the Gold Coast Health Service District, Dr James Lind, the traditional model for a hospital is to book in elective surgery and hope its emergency workload can fit around these bookings.

“We’ve turned that on its head and said the most predictable stuff is the emergency stuff, analysing and deriving value from the vast stores of data that many organisations hold, often in real time.”

Causing drop-outs

One of the most common applications of Big Data analytics is in highly structured environments such as call centres. The vice president for human capital management for APAC and Japan at US technology company Oracle, John Hansen, says his company has been using Big Data techniques to analyse the attrition rates at the call centre of its client Xerox.

Oracle’s technology matches different data points to indicate early signs that a worker might be considering leaving. Xerox can assess the contribution of that worker and implement programs to encourage them to stay.

Several Australian universities are using similar techniques to monitor student behaviour and alert administrators to early signs that a student may drop out.

According to IBM’s sales manager for business intelligence and advanced analytics, Alan Morgan, through working with one university his company uncovered some very different predictors of dropout rates than what the university had previously been monitoring.

“We were able to show using predictive analytics that it was another set of variables – a much wider set of variables – that caused [dropouts],” Morgan says.

This can be directly applied to workforce management. German software maker SAP’s national director for business analytics, database and technology in Australia and New Zealand, Ryan Blackwood, says Big Data can deliver a full view of an employee: “Not just their opinion and not just what is on paper, but how they are performing, so that we can identify ahead of time if there is a decline and take action before the employee has performance issues,” Blackwood says.

Identifying talent

With Big Data analytics, the more data that is fed in, the more useful it becomes. This can include everything about an employee from where they were recruited and their level of experience through to training, performance, and any other data recorded against them.

Oracle’s Hansen says by analysing the right data in the right way, it also becomes possible to identify top talent in an organisation.

“The opportunities are endless because we can look at the entire employee life-cycle,” Hansen says. “We need to understand that so we can identify those parts of the workforce that will be the longer-tenure employees we want to develop, and replicate that.”

Big Data can also assist HR departments in ensuring that their organisation is complying with staffing regulations.

But despite the promise, industry watchers agree that Australian HR departments have been relatively slow to embrace Big Data.

According to John Macy, founder of technology consulting company HR Cloud Solutions, HR has generally performed poorly when it comes to managing its data.

“Because HR people really don’t get involved themselves in the day-to-day data collection processes, they don’t really understand what’s available in the database,” Macy says. “And it is very rare that you would get an HR department that would devote a person to a data management job.”

Hansen agrees that most HR departments still lack the business-analysis skills to effectively design and implement Big Data programs.

Leave a reply

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More on HRM