Employment: Evidence-Based HR
- By Alevtina Borisova
- May. 26 2015 17:04
- Last edited 17:04
Partner, Head of People Services Group, Tax and Legal Department,
KPMG in Russia and the CIS
In the current economic environment in Russia companies need to adopt decisions rapidly at a time of significant uncertainty. The crisis is forcing management at many companies to cut personnel costs, and for this purpose unpopular decisions have to be taken on downsizing or a reconsideration of compensation packages. How can you be sure that you are taking the right decisions? How do you implement such measures and at the same time avoid the risk that employees might become demotivated?
Traditionally companies tend to use all kinds of sophisticated data for consumer profiling, manufacturing processes and other areas, but less so in HR. Today, more than at any other time in history, the technology is available to access data from many sources and provide predictive insights that will have a positive impact on the delivery of business strategy. I am talking here about evidence-based HR: or, put simply, using data, analysis and research to understand the link between people management practices and business outcomes such as profitability, customer satisfaction and quality.
Over the past few years HR analytics has become a global trend and Russia is no exception. Admittedly, interest in such a topic in Russia is only now gaining momentum, as demonstrated by the fact that this April the “2nd Annual HR Analytics Conference” took place in Moscow. By contrast, a similar event in the U.S. called “HR Metrics and Analytics Summit” will be held this September for the 14th time.
In Russia over the past few years, a number of companies have sought to implement international HR best practices, and not always successfully. In my opinion, this is in part due to the fact that every company is unique, has followed its own special development path, and established its own unique corporate culture. This does not mean that you should not adopt best practices. In fact, this can be done by using statistical methods, which are virtually on a par with scientific research, in order to analyze your unique situation and the situation at your company, and also the individual factors driving the success of your business.
Evidence-based HR can be extremely useful in pinpointing the direct relationship between employee and customer data. Evidence-based analysis does not simply determine how well people are performing; it can also be used to calculate how individual performance is linked to the consumer brand, establish and measure the link between employee, customer and revenue. A recent example involves a retail bank that was looking for ways to improve the performance of its branch network employed these techniques. Analysis of the bank’s HR and workforce data with financial performance and customer data showed that its higher-performing branches tended to have more part-time, but also more experienced workers. The bank leveraged these insights by, inter alia, changing its hiring policies and improving the product knowledge of its younger staff, which resulted in improved branch performance.
My own personal experience shows that it is far easier to win over senior management on the basis of figures. For example, our company recruits annually more than 500 university graduates and uses numerical and verbal intelligence tests for screening purposes. After thinking about ways to increase the effectiveness of the selection procedure, we applied statistical analysis to our extensive graduate recruitment candidate database. One of the conclusions of our analysis was that candidates, who have achieved high scores in the numerical test, subsequently turn out to be some of the top performers at work. This would appear to be a rather obvious conclusion that could have been drawn based on general logic, as they actually work as auditors and need to be able to think systematically and analyze large volumes of numerical information. However, when this conclusion is backed up by statistical analysis, which has been drawn from a sample of several thousand people, it acquires far more authority for management.
Based on my observations, the level of HR analytics at companies is low today for a number of reasons. Take, for example, the low level of automation of HR processes. It is understandable that in the case of business automation, the HR function does not take center stage. When the automation finally turns to HR, the selected solution does not always make it possible, within the framework of one system, to analyze both HR data and business performance indicators. At other companies HR data are decentralized significantly and such information may be located in several different places — thereby making it very hard to access or use the data in any meaningful way. For example, a lot of organizations keep individual training records in one learning management system, recruitment data in application tracking systems, data on absenteeism in a labor system and performance management information in the manager’s desk files.
The low level of HR analytics is also due to the inadequate level of qualifications. The HR function does not employ enough people with the right skills for this new era of evidence-based HR, such as mathematicians and data modelers who are not typical HR people (a number of our clients are recruiting data scientists to HR). More HR professionals with an advanced social science background are required — individuals capable of differentiating good and bad research. Moreover, existing HR people need to become more numerically proficient and be able to explain data insights, and communicate the business relevance of findings in a compelling way to senior management. To date, business schools have not responded adequately to employer demands, hampering the development of the necessary skills: analytics is still not taught in HR programs.
At the same time, despite all these objective reasons, there are serious grounds for assuming that most companies will soon make the transition to the era of evidence-based people management.
According to a survey conducted by the Economist Intelligence Unit in 2012, only 15 percent of respondents believed that the HR function at their company excelled at providing insightful and predictive workforce analytics. The 2014 survey found that this proportion had increased to 23 percent. In addition, the vast majority of companies (70%) are intent on increasing their focus on HR evidence over the next three years.
Organizations often say that people are their greatest asset. Evidence-based HR allows these organizations to drill down to the crux of that statement, and really understand the key business performance drivers. This is not about gut feeling and past intuition — this is all about leveraging decision-making data, and linking people data with business outcomes. It is not widespread today — however, we believe it is just a matter of time.