Human capital is one of the most vital factors of corporate success. It is, however, becoming more and more difficult to come by, with the employment market growing increasingly competitive. As skills fail to keep pace with evolving technology and processes, companies are being forced to fight to attract the best candidates while also retaining and optimizing the talent they already have. HR departments are having to work harder than ever to operate in this challenging climate, and many have turned to data in response to these challenges.
HR must be able to show credible data to evidence productivity, engagement, and performance if they want to become more proactive and make better-informed decisions. Yet while the rate at which data analytics is being adopted by HR departments has certainly increased over the past year or so, in comparison to other departments it is still some way behind in terms of maturity. There are a number of reasons for this. For one, human capital is one of the hardest assets to quantify. Data is also often unstructured, making it harder to process, held in disparate locations and handwritten.
These challenges have, to a degree, also caused - or been caused by, depending on your point of view - a certain dismissal of analytics from senior management. This has led to underwhelming levels of investment in the tools for HR to analyze data and staff capable of using them. In a recent survey of 398 of its members by the US Society for Human Resources Management (SHRM), 71% said that while their organization has data analysis roles within the accounting and finance department, just 54% have such roles in HR. Meanwhile, recent XpertHR research found that 95.5% of HR professionals have experienced problems gathering and analysing HR metrics data, citing poorly integrated data systems, a lack of resources to gather data, and uncertainty over what to measure.
This lack of analytical skills is not necessarily down to low investment however, it could also be a lack of willing skilled data practitioners. The perception that HR is behind the curve is not restricted to senior management, it also extends to data talent who may feel it is not the sexiest career for them and they won’t be respected or challenged. The SHRM survey also found that 78% of HR professionals had found it difficult or very difficult to recruit for data analysis positions in the preceding 12 months. HR teams need to work harder to recruit analytics talent by promoting the challenges of analyzing unstructured data and applying behavioral analytics to understanding the most complex system in the world - a person.
This situation is slowly changing, though. Dr Martin Edwards, author of Predictive HR Analytics and a statistics lecturer at King’s College London, argues that HR doesn’t have the tools to exploit analytics, noting: ‘If we look at the research that has been published in recent years, the perspective is that HR will fail to rise to the analytics challenge, that it will be a fad that passes us by. I personally don’t agree – it’s a developing field.’
Gustavo Canton, Senior Director of Research at Walmart, agrees. In a recent interview with us, he noted that: ‘Based on my interactions in conferences or meetings with other analytics experts and colleagues in the industry, it appears that more and more organizations are starting their journey or investing more in HR Analytics. There are several factors that contribute to this, including disjointed HR data systems. Traditionally, HR has been seen as a function which is tasked to recruit, retain, and develop talent. As a result, most of the analytics are built around basic reporting, ad-hoc requests and low complexity descriptive analytics. HR has the potential to become a revenue generator for those organizations that are able to leverage data and analytics in order to make better decisions for the business and allocate the right talent to the right part of the business at the right time. Departments such as Marketing, Technology, and Market Research, among others, have been using sophisticated modeling techniques for decades and are more familiar with analytics so are able to digest it easier, plus it gives them an advantage on how they influence c-suite executives on how to make decisions. We are on the right path in HR and the faster we start our journey, the faster we will achieve the next maturity level.
Dave Sachs, Manager of Workforce Analytics at Johnson Controls, meanwhile, has experienced a similar change in attitudes. He told us, ‘I think overall the attitude has improved in the sense that the demand is there from the business. Business leaders want a clear understanding of how many people they have and where they are. While these questions are often in reference to cost implications, it is the collective job of HR to help our leaders see beyond the cost and look at the potential return on investment and how that aligns to the business strategy.’
Last year certainly saw some significant leaps forward in the field. The 2016 Nobel Prize In Economics was awarded to Bengt Holmström of the Massachusetts Institute of Technology (MIT) and Oliver Hart of Harvard University for their work in Workforce Analytics, with their contributions to contract theory cited by the jury as ’a comprehensive framework for analyzing many diverse issues in contractual design, like performance-based pay for top executives, deductibles and co-pays in insurance, and the privatization of public-sector activities.’ It is not just a question of perception though. HR needs to be comfortable talking analytics if adoption is to gather pace. Sachs added that, ‘A workforce analytics team must spend as much time consulting and educating HRBPs as they are the analytics ambassadors which will ultimately drive the demand for your team and function. The greater the partnership and coaching, the better you are long-term as the demand will grow for your services.’ For HR analytics to be successful requires not only investment, it requires communication and collaboration. HR teams must work both with one another and other departments to get the necessary data and draw insights from it. Ultimately, all businesses want more productive employees. Wages are often a company’s biggest expenditures, and data is necessary to ensure that this is money well spent. HR analytics should get the respect it deserves.