We’ve often heard companies trumpet the line, “At our company, people aren’t just a number; they’re our greatest resource.” In many ways, management theory has for a long time proclaimed that companies that are less personal deliver worse results and that analytics and great people cultures are mutually exclusive.
However, in recent years, advances in machine learning and in technology that allows us to gain access to the kind of data that was previously unattainable, there has been a big move to analytics in other parts of the organization. Thus far, the shift to analytics as a necessary business function has been particularly acute in the marketing, purchasing and sales functions. For example, we can point to tools such as Google Analytics which has overturned conventional marketing theory and established direct cause and effect on campaign where such data was once much more speculative.
It was natural that eventually analytics would play a bigger role in HR although for a long time, that “people vs numbers” debate was sure to be a stumbling block for organizations. But this view is now starting to turn and advances in Artificial Intelligence could be just the thing to bring them into the spotlight.
Why It’s Taken So Long
There are fundamentally a couple of reasons why people analysis is a bit late to the party. On a general level, we should first understand that many small and medium organizations still have not graduated to the sophistication (or assigned budgets) where they even consider using people management tools. In many small and medium organizations in particular, investments in performance management tools are already a heavy lift even before getting into HR analytics.
Second, we are only now starting to see a concerted push toward HR embedding themselves within business units and being used to solve commercial issues via people strategy. This is embodied by the growth of the role of HR Business Partner. For the first time, HR specialists are also gaining knowledge in a lot of operational areas too.
Finally, that both HR and operations were viewed as specialized fields resulted in a near-silo mentality where operations viewed that area as their domain while HR did the same. As both sides saw their superiority in their chosen field and their lack of understanding in the other area, they tended to defer to each other when in fact a shared disciplinary approach could yield huge benefits to the whole organization.
HR Analytics to the Rescue
With the growth in marketing and production analytics, things have changed a lot. Managers and C-Level employees are becoming more used to seeing a more disparate range of measures in the form of dashboards. By becoming more data-driven, they are now able to process a wider-range of data to make day-to-day decisions. Just as marketing was at one time a “black box” in terms of determining cause and effect, C-Level employees are now starting to expect that sense can be made of every part of the organization through data.
There is also a greater sense that just as HR is now being able to solve problems in multiple disciplines, the flip-side is also possible. Through this, proficiency in the technical aspects of organization management as held by HR professionals are now being matched with operations people and data analysts bringing entirely different expertise. Organizations can now tap into the best of both worlds and develop insights that are deeper and more relevant to solving real problems.
Too Much Data, Too Little Time
Of course, the world today is full of data and that by itself can often overwhelm even the most diligent of managers. In recent times, performance management software has helped a lot in organizing performance measures in one place. In addition, HR teams have become more adept at reading the mood of both employees and employers through online surveys that can quickly provide some measures of overall happiness and areas for improvement.
Beyond that, countless new measures are now in place through organizational tools to gather insights that we never thought possible. For example, companies using productivity suites like Office 365 can measure how much time people are spending in meetings, their work hours, how many people they communicate with, how often they meet with managers or teammates, how much time they spend on the road and a host of other measures and correlate them with activities such as fraud, workplace accidents and even the level of employee happiness that they expressed on surveys.
So, the good news is we can now chart out all sorts of patterns. But the holy grail is prediction and that’s where talent management software and AI really come in.
A New World
Using AI, HR analytics software can keep more diverse data inputs, but more importantly can also make predictions based on literally dozens of disparate data points. They can spot correlations which otherwise would have been too time-intensive for HR to find any other way.
That being said, as we know, we have lots and lots of data. The key is how can we find all the relevant data and more importantly, do something about it. In Google Analytics for example, instead of scrolling through literally thousands of measures, AI is used to present key trends or “Events” that allow analysts to look at major events during a given period and suggests a few ways of addressing those.
AI in HR Analytics has basically the same purpose. Not only can we predict factors that might lead to underperformance, turnover or even more dangerous events like workplace accidents, but AI allows the system to present solutions to us on how to prevent these predictions from happening. Add to this the fact that we can use dashboards to focus on the most relevant information and you can imagine the potential through which HR analytics can help us to improve compensation standards (either in terms of making salaries more competitive or even avoiding giving raises when doing so likely will not impact performance), manager quality, organizational expectations and a host of other factors that directly impact not only the performance of the team, but to a large extent can have a major impact on overall organizational performance.
All told, the AI component added to the acceptance of HR analytics as a tool that is relevant in both non-HR functions and at the executive level presents some exciting opportunities for the future for any organization, especially as the tools become more cost-accessible even for smaller teams. The good news is that while performance management tools are enabling us to use more data science, AI means that thankfully we won’t all need to be data scientists to benefit from their insights.