John Baldino, the founder and CEO of Humareso, told Work Human that human resources department is part of art and part of science because it deals with both human and metrics to measure things.
Art in HR is the traditional approach to employee engagement such as vocal rewarding and recognition. Meanwhile, the scientific approach is about enabling data and metrics to measure the engagement in a more modern way such as using technology to measure data and create a strategy that works. And both sides, added Baldino, are important for human resources to really maintain and retain employees.
Another opinion from an internationally known HR thought-leader from Silicon Valley, Dr. John Sullivan agreed that human resources must have both parts to balance between real- and virtual-touch to organisations’ management. However, he argued that leaders must now realise the need for “becoming more scientific”.
Technology and AI have finally begun to drive HR, said Dr. Sullivan, which means the argument whether HR management is a science or an art is now over. The remaining of HR functions should soon willingly or unwillingly adapt data-driven “scientific human resources” approach in order to prosper.
In direct to this example is Google that has reinvented their HR approach to be more science. Google’s people management decisions are powerfully guided by people analytics with the goals to “bring the same level of rigour to people decisions that we (Google employees) do to engineering decisions”.
Therefore, if you want to grow together with your people just like what Google did, you need to strengthen your scientific side. The foundation to do this is by following these approaches.
Rather than just focus on aligning approaches with business goals, you need to focus on both human resources actions and resources to maximise direct and measurable impact on the result. For example, scientific human resources should focus on solving broad strategic business problems rather than tactical problems.
No more intuition and unprovable decision-making, to be scientifically savvy, you need to make a decision based on performance data. The latest data, the more reliable it is to measure success. In addition, you should use data and objective criteria to determine when needed work should be done by employees or using technology.
One of the prominent differences between traditional and scientific HR is its emphasis on experimentation. To prove that your approach is reliable and lead to success, you need to test your hypothesis with experiments – and during the experiment, you should carefully collect data to generate an actual result.
To drive change, technology must be a prime driver of HR change. Everything should be electronically accessible including information, processes, training, and development. By being fully digital, the input and output can be quantified in numbers and can result in real data collection.
It requires continuous learning and improvements to completely apprehend about the scientific approach. You should emphasis on collecting and reporting on performance data for human decision-making. Additionally, machine learning and automatic feedback are also critical for identifying key learnings. Developing problem-solving skills through the process should be your priority.
Read also: What It Takes to be an HR Data Analyst