A lot executives say they want to use analytics, but when it comes right down to it, if the results conflict with their gut instinct, sometimes that can be a challenge, because they can trust their gut more than the data.
Getting executives to trust data rather than their instincts is just one of the challenges facing the growth of HR analytics, according to Beth McFarland, CAE director, foundation programs at the Society for Human Resource Management (SHRM) Foundation.
This is particularly true when the results produced by data analysis are counter-intuitive. Fast-food chain Wendy’s, for example, found that the high performing stores were not determined by the quality or the longevity of staff working there.
Instead, notes McFarland, data analysis revealed the key differentiator was having a “pre-shift huddle”, where managers and staff got together at the beginning of the shift and talked about priorities and issues for the day ahead. Stores that did that well saw a huge increase in sales. McFarland adds:
Sometimes it’s a very small thing that you can tweak and it makes a huge difference.
The SHRM Foundation has pulled together research from multiple sources to present a state of the nation look at HR analytics in its report Use of Workforce Analytics for Competitive Advantage.
While the report suggests that HR is sold on the importance of HR analytics, many firms are still “figuring out how to make it work in their business”, according to McFarland.
I think we also see that a company CEO will say they want to do analytics and the HR person is left to figure out what that means and how to approach it.
The HR team’s first instincts may be to immediately start analysing the data they have (data is one thing HR is certainly not short of). But rather than jump straight in with both feet, McFarland councils a more considered and cautious approach. HR needs to think about the specific business questions or challenges that really need answering:
Find a business question you need to answer and then find the data you need to answer that. Probably that’s going to be located in multiple departments and you’ll have to navigate that and pull things together to get the answer you need.
To do any kind of analytics takes time, resources and skills. And that is another of the major challenges impacting the uptake of analytics. Data scientists are rare beasts and while the likes of Google and other large firms may be able to attract and afford a team of data specialists, this isn’t an option for your average firm.
Educating and training existing HR staff is one option, but most people in HR (at least those who have been in the profession a while) do not have strong analytical skills. HR needs to both pull talent in from elsewhere in the company and begin to educate and nurture more HR people with analytics capabilities.
The fact that HR has tended to be a little bit behind their business cohorts in marketing and finance in analytics adoption can actually help here. It’s time to call in favors and use the expertise elsewhere in the company.
The data politics of analytics is a possible stumbling block here. Departments can be protective over their own data, whereas taking advantage of data analytics fully requires people working together across marketing, finance, HR and other departments.
While outsourcing is always an option if there really aren’t the skills in-house, this doesn’t build in-house expertise and it comes at a cost. Instead, it pays to think laterally for a solution, notes McFarland:
At a roundtable we ran, one company was telling us that what they did a lot was work with universities which is a low-cost option. They’ll find professors or even grad students who can help them out.
However the team is set up, it’s important that there is a mix of skills and experience. Otherwise there’s a danger of mistaking correlations for causation in the data – making assumptions and links without thinking about the wider context. McFarland says:
You’ve got to be careful you don’t have just the data scientists interpreting – you need the context, the HR perspective as well.
So if there is a central analytics team, it’s essential that it is formed of people from a lot of different disciplines rather than left entirely to the data scientists. McFarland explains:
So you don’t have just the technical people, you have someone who can be a story teller, who can interpret the data and tell the story about what it means.
Another issue slowing down the use of HR analytics is data confidentiality, she notes:
HR is always trained to protect employee data and keep it confidential and now they have to use that data and share it with other departments and that’s a challenge for them. There’s a tension between keeping things confidential and the ethical and legal boundaries.
For example, notes the report, will companies neglect employees whom analytics have deemed more likely to resign? And if analytics can pinpoint a correlation between performance and physical activity each day, how will they use it?
Clearly, there are many challenges in implementing HR analytics, but overall, McFarland is optimistic about the future of analytics in HR:
People are becoming aware of it and moving in the right direction. It’s a slow process, but we’re going to get there.
HR analytics is here to stay and gaining traction, but as this report highlights, there are challenges to its growth, particularly when it comes to lack of skills and cultural issues.
Workforce analytics is just one of three areas identified by SHRM and the Economist Intelligence Unit (EIU) affecting the future of work over the next decade. The second area is the evolution of the work and worker, as changing demographics, globilization and mobility affect working practices. Finally, the issue of integrating and engaging a global workforce will increasingly impact business.
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