3 key issues HR must address with talent analytics

There are three important challenges that HR needs to address in developing and implementing an integrated and strategic talent analytics program

There are three important challenges that HR needs to address in developing and implementing an integrated and strategic talent analytics program, according to an expert in the area.

The three challenges: criticality, capability and credibility, are common to most organisations, however, they are unique for each business and should be addressed accordingly, said Aaron McEwan, HR advisory leader at CEB.

“Right now HR suffers from a credibility issue,” he said.

“Second only to marketing, HR data is the leased trusted source of data in the business.”

McEwan said 80 per cent of CEOs want to base important company decisions (for example, in managing staff productivity or labour costs) on insights from workforce data, but only a fifth say they get sufficient information from HR.

The HR function risks being blocked from C-suite discussions and business decisions as the slow adoption of talent analytics further jeopardises the function’s credibility and authority, according to McEwan, who outlined the implications of the talent analytics challenges facing HR:

1. Where should I focus HR analytics? (criticality)
Successful managers prioritise projects that are the most scalable ways to help managers hit strategic goals, rather than simply fulfilling on-demand data requests.

Focusing on well-defined, small, and easy analytics “showcases” in the first step to create awareness and appetite for analytics support with senior business stakeholders is a good start to show how critical good analytics can be.

2. How do I develop my analytics team? (capability)
On one hand, companies require skills of four role types in their HR analytics teams, which can come from different people or, if they’re lucky, all be provided by one person.

This might be a “business challenger” who is able to influence and work with stakeholders inside and outside of HR; an HR domain expert with the skills to analyse HR-related business needs, a programmer able to design databases and integrate different sources, and a data scientist with classic analytics abilities plus advanced big data analytics skills.

On the other hand, McEwan said companies also need to think about the adequate HR analytics tools and technology they might require from external vendors so that they don’t have to build-up all advanced analytics capabilities internally.

3. How can I increase the influence of HR analytics (credibility)
The best teams ensure they collaborate with stakeholders throughout the process of identifying which topics or projects the HR analytics team will work on, all the way through to interpreting the results.

McEwan noted that only about 50 per cent of HR organisations globally have a single dedicated talent analytics function within HR, and the percentage is smaller for Australia.

“Of more concern is that most talent analytics teams are not focused on strategic, value-adding activities,” he said.

“The most common talent analytics staff activities are creating talent data reports, and completing ad hoc data requests from the business and HR leaders.”

“They will soon come asking about the ROI and, ironically, HR may find itself struggling to provide an acceptable response”

Less commonly, McEwan said talent analytics staff are responsible for project-based modelling or analytics studies (74 per cent), workforce planning (49 per cent), HRIS or other HR technology management (41 per cent), and HR application and technology development (33 per cent).

“At the moment, these teams are relatively well funded and there is significant interest from the business (CEOs) in improving talent analytics capability across the organisation,” he said.

“But … they will soon come asking about the ROI and, ironically, HR may find itself struggling to provide an acceptable response.”

Ultimately McEwan said the business wants and needs talent related data that helps them to make important strategic decision about the future.

“For example, let’s say a company is looking to offshore their customer service division because emerging markets offer a more competitive labour cost,” he said.

“This cost-saving may evaporate quickly if it turns out that labour costs in that region are actually rising due to improving standards of living and a projected lack of talent moving forward.

“Additionally, improved call centre automation and technology improvements might mean that current local talent is well positioned to meet demand in the medium to long-term, ultimately making offshoring less attractive.”

McEwan said business leaders want these types of leading indicators to help them make evidenced-based decisions and course correct quickly.

“Right now, we are mostly providing lagging indicators which are helpful but don’t necessarily shape the most critical business decisions,” he said.

A recent CEB report, The State of Talent Analytics, 2017, which took in 212 talent analytics leaders and professionals from around the world, found that investing in better HR analytics has a proven, positive effect on talent management.

Compared to the average organisation, it found that those companies that range in the top quartile for the quality of their HR analytics achieve 12 per cent better performance in terms of succession management, their employee performance review system, the quality of the people they hire, and how engaged their employees are (see below chart).

 

“Our view is that there is no ‘ideal’ structure, rather it’s about developing analytics maturity with the ultimate goal applying the right analytics to the right issues,” said McEwan.

“As such, the structure should be built to support this end.”

McEwan gave the example of healthcare firm, Roche, which was facing high attrition rates in Asia that were jeopardising revenue growth targets.

Roche’s HR analytics team developed and tested 16 hypotheses to explain the attrition and was able to statistically prove the relevance of six factors determining the high fluctuation.

As well as working on the root causes, McEwan said Roche is now also developing an early warning system for similar situations based on analysis of unstructured (or “big”) data.

“This has contributed considerably to the success of the business,” he said.

“Business leaders across the board have placed a huge emphasis on the value of data”

McEwan observed that the majority of employees within HR have had little-to-no exposure to data analysis as part of their training.

“This means that as a whole, the function is under-equipped to deliver the talent insights that are critical to informing business decisions,” he said.

However, the CEB report found that just over one in 10 organisations report being effective, or very effective, at using talent analytics to inform business decisions.

Productivity, absenteeism and effort levels are just some of the key talent insights that can be identified using talent analytics.

“Business leaders across the board have placed a huge emphasis on the value of data,” said McEwan.

“Having the resources in place to effectively and efficiently track, analyse and present workforce insights will give HR a reason to talk directly to the C-suite and have a true impact on business outcomes,” said McEwan.

To help prepare staff for the HR function of the future, McEwan said organisations must invest in upskilling the capabilities of current HR employees, and use them to build a dedicated analytics division; creating a win/win for everyone.

“HR can’t evade talent analytics any longer and the function must be willing to adapt and evolve,” he said.

“As other parts of the business continue to invest heavily in their analytics capabilities, HR risks being pushed aside and overlooked by leaders who want to make accurate but agile decisions.”

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