Watercooler
// about them .
Partner Overview
Behavioral People Analytics for early detection of talent risk
What if talent risk could be predicted? With AI analytics it can.
Losing key talent impacts engagement, accelerates attrition, and harms employer reputation. And we rarely see it coming. Yet, despite expectations for real-time analytics and agility, HR still relies on periodic surveys, gut intuition, and time-consuming manual spreadsheets,
Watercooler lets you see what’s really happening in your organization. Every function of an organization is becoming more data-driven and so is HR.
Now you can look at a team’s digital footprint and get a real-time view. This gives an HR manager early detection of talent risk and insights for customized intervention.
The result:
- lower costs by reducing key talent loss
- improve employee engagement
- take better care of your people
Name:
Watercooler
Country:
Israel
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// Burnout prevention
Detect people risks early
Find organizational blindspots. Before it’s too late.
// Workload
Act when people are working excessive hours
Interventions, based on what’s really happening within an organization.
// Collaboration
Help managers build healthy teams
AI-tailored training for personal and leadership development.
// Business goals
Align talent with business goals
Close the loop between analytics and impact.
// Support DEI
Foster a culture of diversity and inclusion
AI-tailored training for personal and leadership development.
// what they offer .
Experience Behavioral People Analytics
- Talent Retention
- Overworked Teams
- Management Diversity
Which Teams are at risk of losing key talent?
A focus on retaining key talent in a period preceded by uncertainty and layoffs.
Analysis
Identification of teams most at risk of losing key employees. Further analysis of risk factors including isolation and burnout also provided.
Findings
Two development teams were flagged as having an extremely high likelihood of employee departures in the next 3 to 6 months.
Action
HR used this data to engage with specific Team leaders and identify concrete actions to alleviate underlying factors leading to resignation.
Are Teams working extreme hours?
A concern was raised that in a post-lay-off period, employees have assumed additional responsibilities which could lead to burnout.
Analysis
Mapped the activities of all teams to identify those teams with excessive or extremely low workloads. Additional comparisons were made on focus time and time spent in meetings.
Findings
Across the organization, almost 8% of employees belong to teams identified as having high burnout risk based on overworking.
Action
Because there was no option of hiring additional resources, HR used this data to engage with specific Team leaders and develop concrete plans to redistribute workloads and implement flexible working hours.
How diverse is management?
Senior management recognized that there is an underrepresentation of specific population groups in management positions. HR was tasked with providing a report on how widespread the phenomena is but lacked data.
Analysis
A comprehensive analysis of team leads, line managers and senior managers across the entire organization at a team, group and division level. Additional analytics into resignation and burnout risks were performed.
Findings
Rankings of representation levels across all teams, highlighted areas of significant underrepresentation. The rate of potential burnout from individuals from underrepresented groups was over 57% the rate for all managers.
Action
The information on diversity has provided HR with a new tool to address DEI at an individual level. The immediate action has been to include this information in promotion evaluation meetings. In specific cases where the patterns of underrepresentation were most severe, it has required escalations. Specific instances of burnout and resignation factors were communicated to division management for potential interventions.