The latest Data Mining techniques help Managers coach Sales and Service Representatives to greater productivity while retaining them longer.
How it Works
Posts about the science behind assessments
The goal is to predict which internal or external candidate for the next open sales position is most likely to sell at the highest tier.
This demonstration of an interactive spreadsheet combines data-mining techniques (ensemble method, boosting and regression trees).
In this brief video, Chris at Kunze Analytics explains that it's more realistic and powerful to accept uncertainty when simulating and estimating outcome results in the Assessment industry.
Chris demonstrates how AI optimization and simulation software forecast value as a distribution of possible outcomes.
Few people like writing checks to the IRS. Similarly, no one wants to waste money on a hiring or employee development solution that has not been validated by relevant criteria.
Overall Job Match and Job Fit scores become more predictive of performance. That brings great value turning HR into a profit center.
In this video, Chris at Kunze Analytics references thirty (30) years of research to understand the difference between status quo Assessment usefulness (validity) and Machine Learning usefulness. Next, Chris demonstrates how Machine Learning also reduces the risk of using Assessments in error.
Today, Chris at Kunze Analytics simply asks some questions every company should know.
Chris at Kunze Analytics demonstrates how AI and Machine Learning are allowing custom performance modeling work with Selection Assessments to be done at smaller and smaller companies.