The really advanced People Analytics teams that I speak to are using mixed method research, just as (highlighted in the first article) some of the most advanced customer analytics organizations are rapidly building mixed method approaches into their analyses.
I’ve long felt that if you start with a business question, and then ask yourself what information you need to answer that question you’ll find much of it will be qualitative. In fact you’ll probably realise that your approach must be mixed-methods. I’ve yet to see a problem which couldn’t be better solved combining qual and quant approaches.
One of the observations that moved OrganizationView towards understanding text based feedback was that executives were more likely to act based on qualitative data. We wanted to use machine learning to scale and reduce bias in their decisions.
Most of our work combines quant and qual data. In fact, as I mention below, most of our most successful projects over the last 12 months have been of the ‘Exploratory Research’ approach where we use existing text to fast-track understanding of where to look or what to collect with quantitive research.
The great thing for the mass of HR is that frequently our information demands require a large amount of qualitative work & that I’d suggest the techniques used are easier to learn. They still do require learning and understanding from a technical perspective to do well though.