Managing your workforce has become ever more challenging. A rise in skill requirements faces a global labour market that does not offer talent at the same rate. A global war for talent is underway. Knowing where to find skilled labour, how to retain and motivate high potentials and how to prepare them for tomorrow’s challenges through proper training has become a key risk for companies, especially when they operate globally.
Understanding and managing that risk requires granular analysis. Looking at broad trends and aggregate information is no longer sufficient. Rather, your investment and hiring takes place at a local level, under a regulatory framework often set at the regional or national level, and with market conditions determined internationally. This interaction of different layers of risk forces you to dive deep into a range of multi-dimensional data sets, using information from various sources, variable quality and different scope.
In today’s digital era, such information is often available at the point of the fingertip. Large swath of data can be accessed with a couple of clicks using internet search engines or pre-assembled databases, most of them free of charge. Still, accessing some of the databases can be a challenge, as interfaces differ and access routes require different levels of authorization. However, the key problem is not so much to get the information but rather that the amount of data easily exceeds the capacity of even the most capable and trained analyst. In this environment, your challenge is to make sense of the amount of data, extracting only those trends and patterns that are relevant for your business and HR strategy.
Techniques vary. Sometimes, it suffices to present the data in a nice chart. The map above, for instance, gives a quick overview of the worldwide skills gap expected over the next five years. Often, however, more sophisticated approaches are necessary. Broadly speaking, these so-called data reduction techniques involve summarizing large amount of data into one or two indicators that reflect the underlying trends. In many cases, the analyst can use standard statistical techniques. Increasingly, however, the dynamic nature of the global economy and the constantly shifting patterns make it necessary to use the full power of today’s computers, letting the computer detecting underlying and possible shifting patterns: machine learning.
To introduce this topic and provide an overview of the key tools that you might need to consider in your quest for HR analytics excellence, I have posted a short webinar on BrightTalk. This webinar is meant to introduce to state-of-the-art tools for predictive HR analysis. HR experts will learn how to make use of a large and diverse source of publicly available data sources to better prepare their company for the challenges ahead. I introduce different sources and discuss their relative merits. The webinar also offers a short introduction in how to make best use of these tools, for instance through the presentation of dashboards or leading indicators.
I start off the webinar with a short overview of the current state of global labour markets, showing the diverging trends in talent supply and demand for high potentials. I will introduce a range of different indicators drawing on social media or other publicly available data and discuss how these can be made useful for HR predictions. Finally, I will give an overview over different tools to illustrate these predictions both for internal and external purposes.
The webinar is available here:
https://www.brighttalk.com/webcast/9059/180529