1. HR machine learning and predictive analytics is over-hyped.
There has been quite a bit written about, and many HR technology vendors are touting the virtues of machine learning and predictive analytics. Be careful. Buyer beware. It feels like they have become the flavor of the month.
Machine learning and predictive analytics, although very developed in other disciplines, is in very early stages in HR. Many market solutions have not been thoroughly vetted and have inherent flaws that may influence people’s careers. For example, some of the early predictions of “flight risk” have proven to be wrong. There also are ethical and privacy issues around these techniques. If you want to dig into these issues deeper, John Sumser at HR Examiner does extensive writing on these topics.
Don’t misunderstand me, there is some really good work going on in our industry in both areas. However, these techniques are deployed generally at large companies who can afford data analysts, statisticians, and other specialists. David Green at IBM writes extensively about advances in people analytics and highlights compelling case studies.
However, deploying these advanced techniques are complicated and many are not perfected. Be careful in your adoption.
2. Your data will never be perfect, work with it so it can improve over time.
Unfortunately, organizations have historically invested in HR technology last, or in some cases, not at all. There still is quite a bit of work being done ad-hoc on paper and excel worksheets. Typically, there are disparate systems that have been cobbled together, making data extraction and organization difficult. To make matters worse, generally, there are no standards between the systems.
People data and metrics are messy and sometimes there are elements like employee engagement that are hard to quantify. We have got to work with what we have to start, make the best of what we have, and make it better. Your data will never be perfect but when you work with it, you can improve it over time.
3. Get started now with people analytics or your organization won’t be competitive.
Most likely some other function in your organization (marketing, operations, finance, others) leverage their data and advances in analytics to make more intelligent, strategic decisions. For example, marketers analyze patterns in the immense amount of data they collect to figure out how to get you to spend a little more on your next trip. This is analytics.
By applying analytics to investments in people development, HR leaders know that they are deploying programs that work. They can fine-tune investments to their population’s needs. Employees appreciate programs that give them what they need and want on the job.
There is ample proof that organizations applying fact-based decision-making significantly outperform their competitors. If you can run payroll, you’ve got enough data to start. Moving from reporting to descriptive analytics is the first step. Finding relationships between different data sets offers insights into the workforce that reports don’t show. Once descriptive is mastered, you can begin to move into predictive analytics. But get started now.
To enable you to start this work is exactly why I developed my course.