Yet is a data analytics company. We love data. We care about all kinds of crazy structures and the future implied by AIs fueled by granular and ubiquitous and live streaming data. But the thing we love most is helping businesses solve problems with data.
We've recently added a few new graphs to the interactive analytics in our Learning Record Store. A particularly powerful new addition is the outlier graphs.
Outliers have a lot of weight in a human capital context; they provide the answers to the questions:
- "Who are my top and bottom performers?"
- "Who are my most and least engaged team members?"
- "Who are my influencers? Which team members are isolated?"
Knowing the answers to these questions can help you understand and improve performance, collaboration, engagement and retention. Understanding and identifying outliers can help you improve your human capital and your business.
Outliers have always been visible to some degree in Yet's visual analytics, especially in the network graphs:
Knowing that yellow are people, and blue are the things they do, it's pretty clear here which of these team members have been the busiest.
Yet's new outlier visualizations quantify outliers and give a sense of proportion relative to the norm, and provide insight into outliers beyond simple volume of activity.
Here we can see all our outliers in engagement, positioned relative to +/- 1 and 2 standard deviations. In a compact view, we get a visual of the statistical distribution pattern and specific placement of our outliers relative to that pattern.
Performance outlier data provides insights across all quantitatively assessed activity – training, performance reviews, peer feedback, job execution, etc.
These identified performance outliers are great candidates for further review – and pattern mapping. Ultimately the data that describes outlier performers can be used to build and identify high success paths, and likewise low performers can be easily identified by the data for early intervention.
Network connectivity here is a representation of shared activities and connections to other employees. This is a great way to identify influencers – who have unusually high overlapping connections – and lone agents – who may not be connecting and collaborating well within their teams.
Find the Patterns Behind Your Outliers
Knowing which employees are your best and your worst is critical for human capital management. But beyond that, outliers point the way to identifying high success and failure patterns in your human capital management. Gathering the data and finding the place to start – your outliers – has to be your first step.
Interested in finding the patterns of performance in your human capital data?