Analytics
People
Implementation of HR analytics across all areas and automation of data collection and reporting.
Long story short
Task: to implement a data-driven approach to working with business processes (goal setting, development, performance assessment)
Decision-making regarding HR projects, job openings, and performance evaluation was based on intuition.
Lack of data-driven practices: identifying issues and areas of growth through data interpretation.
Qualitative data differed from quantitative data (exit interview results and surveys yielded different outcomes).
Manual tracking of HR metrics.
Lack of data-driven practices: identifying issues and areas of growth through data interpretation.
Qualitative data differed from quantitative data (exit interview results and surveys yielded different outcomes).
Manual tracking of HR metrics.
Before
After
Data-driven decision-making and the ability to capture non-obvious dependencies between two or more variables / events.
What is the project's uniqueness?
We focused on specific business challenges where HR analytics can be beneficial, instead of solely looking at metrics across different HR areas and documenting their dynamics within teams and time periods.
More about the process
1
Defining metrics
We identified metrics for each HR area: recruitment, onboarding, internal communications, promotions, turnover, terminations, and business metrics (profit per employee, personnel costs, investments in employees, etc.).
2
Choosing a data monitoring platform
We selected Jira as the platform for data collection and reporting automation, integrating it with other systems. As a result, we generate real-time updated reports and charts, allowing for data comparison with previous months and quarters, as well as across teams and departments. Access rights were configured for C-level executives, managers, leaders, and HR.
3
Automation of mailing reports
We automated report distribution to relevant stakeholders via email. Different levels of detail are provided in the reports based on the employee's level: C-level executives, leaders, managers, and HR.
4
Building the data workflow process
Determining the frequency of data collection, methods, the process of working with the obtained results, and the monitoring format.
Dependencies
What was not obvious and what we wanted to see in numbers
- The result of an employee's probation period depended on the managerial skills of their supervisor01
A transparent system of communication and goal-setting directly influenced team performance and engagement02
Setting KPIs solely focused on outcomes did not improve business metrics as it had a negative impact on the process03
Hiring a person and strengthening their team did not address the underlying challenges of a specific business area due to improper allocation of responsibilities04- An improperly structured organizational hierarchy and low managerial skills among leaders led to the CEO getting involved in operational activities.05
Results. What became possible:
Addressing business challenges using HR analytics tools
Utilizing data in goal-setting processes, risk assessment, and performance evaluation, as well as cost analysis
Utilizing data in goal-setting processes, risk assessment, and performance evaluation, as well as cost analysis
- Hypothesis testingEvaluating the effectiveness of HR project hypotheses, comparing them, and selecting the best ones
- Budget managementForecasting investments in personnel and their return on investment
- Team
controlForecasting the performance of the development team from its formation to the product's release at the MVP stage - Selecting
the bestHiring the best candidates in the market without overpaying, leveraging knowledge about market capacity in different regions and behavioral patterns
Having a similar issue?
Contact us, and we will answer any questions, consider all your ideas, and determine how we can be helpful
We want to work together.
It's fun and effective!
It's fun and effective!
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