Traditional performance analysis in most companies consists of retrospective analysis that provides a backward-looking view, reporting what happened in the past…
iNostix has developed powerful analytical algorithms that can 1) predict the employee characteristics that are associated with good/bad performance and 2) analyse how groups or clusters of high/low performance employees differ depending on those characteristics. Using advanced algorithms iNostix is able to predict the relationships between aspects such as employee characteristics, organisation context, training investments, management quality, employee engagement and employee performance.
Unlike traditional fuzzy measures of hiring, onboarding and learning, iNostix predictions can lead to faster time-to-contribution, lower cost-per-hire and ultimately, increased quality of hires.
Predict organisational effectiveness
Together with Prof. Dr. Baesens of the University of Leuven (B) and iNostix’s academic advisor, iNostix has developed a powerful process mining algorithm providing clients with a unique organisational x-ray.
Employee engagement analytics
iNostix’s world-class employee survey expertise, in combination with our superior data analytics methodologies and a large engagement database, can give our clients a unique competitive advantage.
Predicting absenteeism or work accident risks
By mining past patterns of absenteeism and by including demographic variables and work context into the analytical model, iNostix can predict future absenteeism and work accident risks in a so-called Risk Heat Map.