The Clean Data Imperative
“Get the fundamentals down and the level of everything you do will rise“, former NBA star Michael Jordan famously said. This approach fits like a glove when it comes to companies’ attitudes towards capturing their workforce’s skills.
In this week’s article recommendation, the director of HR Insights at Spotify stresses the importance of gathering clean skill data about Spotify’s workforce. After all, clean data serves as a stepping stone for further analysis and should not cause any trouble when putting it into use.
We at People-Analytix have recognized clean data as a necessity. In order to upgrade your skill data to clean skill data, we use AI-enhanced technology. To ensure high quality, we provide to you a proper skill network (= ontology), which works as follows:
- Two or more skills meaning the same will be stored under one name (these remaining core-skills are called unique skills). Thus, skills, which are synonymous of each other, are recognized as interchangeable by our algorithms. Therefore, clutter caused by several skill synonyms in your database is no longer an issue.
- Our ontology automatically reduces more than 100’000 extended skills (= synonyms of unique skills) to 18’000 unique skills.
- In addition, our AI allows recognition of the proximity of skills to each other.
- Skills captured in one language are easily interlinked with their translations in different languages.
- You want to know more about how the People-Analytix solution enables strategic workforce management? Click here.
- Interested in reading the whole Spotify HR article? Click here.