Data Analytics macht nur Sinn, wenn auch genug Daten zur Analyse bereit liegen. Andererseits ist es im HR-Bereich noch wichtiger, den Mitarbeitern klar zu kommunizieren, warum welche Daten erhoben werden und was mit diesen Daten geschieht. Dabei gilt es, einige Fallstricke zu beachten.
Lesen Sie hierzu einen Erfahrungsbericht von Bob Bennett, ehemaliger chief learning officer bei FedEx. Laden Sie hier den englischsprachigen Artikel herunter:
http://bit.ly/TADA_bennett
2. HR Data Analytics
It’s not magic; throughout history, those with the greatest resources won the battles through better
planning and execution. It’s the same today with Big Data. In this ever-changing world, those with
data are better equipped for success.
There is no division with a more compelling reason to lead these efforts than Human Resources, with
its critical role in the development of strategy, strategic workforce planning, and just as importantly,
in the shaping of the culture. While the well-equipped win the battles, often times it is the entity with
the most loyal followers that wins the war! In leading this effort, one should remember: The term
Big Data can be intimidating and to some often implies ‘big brother is watching.’ Avoid it whenever
possible. Focus on ‘meaningful data’ that allows you to plan and manage your future. The perceptual
difference can make a world of difference.
In reviewing our Succession Planning status for officer positions at FedEx a few years ago, our data
indicated we had a significant number of positions at risk of being vacated and approximately the
same number without a replacement identified. This created an initial sense of urgency to develop
additional employees quickly, which would have led us down an unnecessary and most likely self-
destructing path. The reality was that there was a very small number of positions that were at risk
of becoming vacant and that did not have a replacement named. The problem to be addressed
was not how we develop others quickly, but rather how do we retain the current high potentials with
limited career opportunities.
So how do we use data? If all companies had access to the same data, some would fail while others
would thrive. Why is that? How an organization manages each of the four key factors associated
with data makes the critical difference:
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