Decoding Talent by Eric Sydell
Author:Eric Sydell
Language: eng
Format: epub
ISBN: 9781639080106
Publisher: Fast Company Press
Published: 2022-10-15T00:00:00+00:00
Figure 6.2. Predictor of data quality
Completing these four audit steps will put you in a strong position to connect and analyze different data sets. Performing such an inspection will help you determine how well your hiring process works, identify which parts are redundant or ineffective, and ultimately understand how to hire high-quality candidates at a previously inconceivable speed.
Step 2: CaptureâBuild Data Capture Capabilities
Once you have completed a thorough audit of your available data, begin collecting information you are not currently capturing. Collecting good-quality metric data is often time consuming but imperative to revamping your hiring process. Itâs the target we aim to hit with predictive pre-hire data, like that captured with assessments and interviews. Without it you are shooting blindly.
When evaluating data quality, pay attention to the four Vâs: volume, variety, velocity, and veracity. Hereâs why they matter:
1.Volume. This one is simple: the more data, the better.
2.Variety. Analyzing unstructured and messy data sets used to be more challenging, but advancements in AI mean we can now learn more from expanding the types of data we collect, integrate, and analyze.
3.Velocity. The rate at which data becomes available grows faster and faster all the time. Even so, you must decide how to collect it, summarize it, and analyze it. (Again, the more, the merrier.)
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