HR transformations have abounded in the last decade as HR organisations continue to attempt a grab for “the seat at the table.” Largely HR has been unsuccessful.
In a world run by numbers, balance sheets, and productivity, HR’s attempt at transforming things like “talent management” and creating efficiencies through “self service” and “HR outsourcing” have not resonated with management from the business or other corporate functions. HR constantly screams the mantras, “People are our most important asset” and “Human capital is our most expensive asset.”
The irony is lost only to HR that nobody can actually analyse how much incremental productivity is gained per dollar of human capital versus other assets, or that HR can’t even quantify with any degree of precision how much an employee costs when everything is factored in. Given that HR is trying to get that “seat at the table” with managers and executives who have gotten used to highly precise, quantitative information from Finance, success lies in providing the same.
The reason HR can’t provide analytical insight is that the focus is all wrong. HR is mired in the production of traditionally accepted measurements because at some point in time these reports were leading edge and provided something managers didn’t have before. This does not mean that that value hasn’t been diluted in this age of mass data. Indeed, traditional HR metrics have not progressed beyond being simply interesting data points to creating actionable insights that the business can use.
Here are just a few sample comparisons between current and future state HR analytics:
| Current HR Reporting | Future HR Reporting |
| Headcount does not matter | Capabilities matter |
| Turnover does not matter | Productivity matters |
| Absence reporting does not matter | Employee engagement matters |
| Time to hire does not matter | Recruiting source analysis matters |
Instead of thinking about transactional measurements, HR needs to get back to basics before getting advanced. It’s about the basics of HR reporting, it’s about the actual human resources. In order to get to end state analytical goals, HR first needs to understand the employee population. By dissecting population profiles, managers and HR both will begin to understand how the employee profiles begin to impact the ability to produce work. Here are a few more examples of how this works:
- Everyone knows that there are great managers and terrible ones, with the majority being in between. But knowing who the great ones are allows HR to transform programs and processes to maximise the probability of having great managers. If HR identifies the top 20% of managers in the organisation, they can run profiles on the average time someone needs to be in management before success, if there is a minimum tenure in the organisation, or a set of specific competencies that can be measured.
- HR and managers like to think about compensation a lot and how it is tied to last year’s performance. But it’s less important to know about levels of compensation and more important to understand if compensation is really tied to rewards for your most productive, highest potential employees. Much of the time, both HR and managers fall into the trap of rewarding for the past and not looking into the future. While sometimes the past and the future outcomes are correlated, having a real picture of potential and rewarding to that is more important.
- Every company calculates absenteeism rates, but few companies calculate absenteeism on Mondays and Fridays (usually spikes there are considered to be fake illnesses). And almost no companies look at which specific populations or employee attributes are absent on Mondays and Fridays, and possible correlated thresholds that impact absence (if employee engagement level dips below a certain score, Friday absences will spike.) Even fewer companies are taking a scientific and statistical approach to solving the question of decreasing undesired absence. Most companies take the anecdotal data they have and do nothing with it, or guess at solutions.
So the dissection of employee population profiles has nothing to do with the percentage of gender, race, or age mix in the organisation. In fact, demographics may have very little to do with the population profiles that matter. The attributes of high producers may turn out to be about the type of college they went to, or how much support staff they have. Managers who are net exporters of talent may have been recruited from certain industries or competitors. Engagement may have almost nothing to do with the manager relationship, and instead there is a major correlation to a Myers Briggs profile that your company culture happens to be a great fit for. These are all hypothetical examples, but the point being that nobody knows what drives important behaviors if all HR produces are turnover and headcount reports.
Perhaps counterintuitively, the path to great HR analytics has little to do with the creation of technological capabilities, and more to do with the deskilling or hiring of new people capabilities and creating processes to help people through the learning process. Indeed, no matter how much technology an organisation can bring to bear, without skilled people, advanced analytical insights will never be achieved, but a skilled group of the right analysts can produce actionable insightfulness with nothing more than a few spreadsheets.
Additionally, HR business partners have to understand how to translate data insights into business actions that managers and executives can understand and do something with. HR functional partners have to understand how data can positively influence the adoption, execution and overall quality of HR programs.
In the end, HR’s ability to gain acceptance in the business hinge on its ability to produce increasingly valuable insights over time that will help the organisation predict future success and actions to get there, rather than constantly looking backwards in time. To do this, HR has to transform the whole organisation and HR has not realised that the gap between what the organisation needs from analytics is a people rather than a technology gap. HR has focused for too long trying to transform the operational model and the technologies they have. It’s time to focus on building a different set of people skills.
By Wes Wu, HR Strategy Consultant, Appirio