Descriptive, predictive, prescriptive or cognitive analytics? Stop this nonsense!
Whenever you attend a people analytics conference, or simply open your LinkedIn feed, you'll quickly be amazed by what professionals promise on people analytics. The more complex techniques, the better. But they fail to provide a handle on the technique and access to its benefits.
These claims are dangerous as they impose unrealistic expectations of what people analytics can do. In over ten years of pioneering in people analytics, I’ve learned that over-promise and under-delivery does not help to develop this field. We need to get back to helping business partners to implement the analytics tools available and discover the benefits, before they get lost in disillusion.
Increasing speed of adoption
What is people analytics about? In my definition: “The use of digital methods to develop a deep understanding between people, organization and business performance, to make better and more reliable decisions”. These digital methods, ranging from models, statistics, artificial intelligence and visualizations to animations, are never a goal in themselves, but merely an instrument to support the bigger objective of making better and more reliable decisions related to workforce.
Companies start to embrace this concept, but in building capabilities they get bogged down easily in techniques and tools. The company-wide adoption stalls if business partners aren’t comfortable with people analytics. The bottleneck for the speed and successful people analytics programs are in user adoption, as depicted in the figure. In other words: make business partners comfortable with intuitive tooling. We’d like to use the play-learn-build methodology.
Making technology accessible
With this methodology in mind we have updated Crunchr. We have improved the overall look & feel, working with our user interface and experience design experts and with customers to iterate the design. We have simplified the navigation and redesigned our menu, helping users to find their way intuitively with room to spare to introduce all the research currently in the pipeline.
The dashboard invites HR professionals to (re)discover the key characteristics of the workforce in all its aspects and segments. Slicing and dicing the organization at a mouse click questions arise about productivity available, potential to be developed and gaps to be filled. Questions that people analytics can give meaningful answers to.
It’s all about making technology accessible. I believe that to really drive people analytics, companies should focus on the business partnering skills first and making technology accessible for the entire HR organization. We have learned to do this in four steps:
Apply business partnering skills to ask the right questions and make the correct interpretations;
Then apply analytical skills to build a model or workout the hypothesis;
Next import the data, facts, figures and visualizations to support your storytelling;
Finally apply technology to make people analytics scalable to the entire organization.