From static to descriptive and finally predictive, HR analytics has come a long way. Now, we are positioned at the next bend, with conversations around prescriptive analytics and what it could do for HR. We share insights from Accenture’s report and consider what a business leader from Workday has to say.
In the last few years, analytics has emerged as a major buzz-word in the HR segment. From simply static reports, HR teams are now looking forward to deploying various analytics models and making better HR decisions. Among the different analytics techniques available today, descriptive analytics is probably the most common (it tells us why an event happened) and predictive analytics is the one most talked about (it sheds light on what will happen next). A third category and this is still in a nascent stage of discourse, is prescriptive analytics.
Prescriptive analytics combines the historical capabilities of static and descriptive models, with a forward-looking perspective. As a result, users can gain insights on not just what will happen next, but also on what they should do next. While this sounds promising on paper, research suggests that the discussion on prescriptive analytics is yet to take off.
What’s Holding back the Application of Prescriptive Analytics in HR
Prescriptive analytics is already being implemented in media and entertainment, by technology disruptors like Netflix and Spotify. The technology processes massive streams of consumer data and looks at past usage patterns, to predict future needs and preferences. The prescriptive layer then intervenes to suggest which recommendations should be displayed, how a particular promotion can be tailored, and if any specific messaging can be deployed to engage the user.
In HR, this can be translated into a data-driven workforce planning strategy where every element of allocation, optimization, and addition (hiring) is guided by a pre-defined roadmap. However, current workforce planning strategies often depend on insufficient data and legacy tools. The opportunity for applying prescriptive analytics is immense. It will help integrate new data streams, enabling employers to go beyond a holistic picture of what’s coming and actually identify future movements.
Given these benefits, companies should ideally be eager to early-adopt and explore how prescriptive analytics could transform their HR functions. But concerns around data quality and the sheer disruptive impact of this technology is holding back implementation. The garbage-in/garbage-out principle means that the insights generated through prescriptive analytics are only as good as the data feeding into it. Companies without the basic analytics capabilities as discussed above (static, descriptive, and then predictive) will find it difficult to take the leap.
Another issue is that the prescriptive analytics output must be carefully evaluated and fine-tuned to decide on the most relevant action areas. For companies lacking in-house data science capabilities or robust strategic talent, this can be a challenging process.
Key Use Cases and the Way Forward
In an enlightening study, Accenture found that applying prescriptive analytics could help companies find areas where its field workforce could perform better, contributing more to the bottom line. While it sounds simple on paper, the model analyzed over 4,500 field engineers, three million pieces of equipment and seven types of products to locate actionable insights in over 12,000 potential scenarios.
The scale and the specificity of this initiative are simply massive – prescriptive analytics has the ability to break down data stacks into its most granular details to suggest ideas for handling myriad workplace scenarios. From workforce planning to internal transfers, from shaping training programs to incentive packages, prescriptive analytics could turn every existing model on its head.
“Think of it like Netflix for business. It predicts a film based on what we’ve viewed in the past,” said Rob Wells, managing director of Workday, Australia and New Zealand. “And like the simplicity of Amazon or Netflix recommendations, all of these recommendations will be easily delivered to managers in a simple interface – without the assistance of IT or data analysts.” To make this vision a reality, overcoming the challenges detailed earlier, we need major strides in technology, innovation, and a focus on improving HR tech accessibility to employers of every size.