HR Data Integration
HR data integration is the process of ingesting, aggregating, normalizing and categorizing data from multiple sources such as Human Resources Information System (HRIS), Applicant Tracking System (ATS), Enterprise Resource Planning (ERP), Learning and Management System (LMS), and 3rd party providers (e.g. engagement surveys).
The data integration process allows HR to compare and contrast metrics from multiple sources that are not available with just one data source. For example, integrating Recruiting with Performance data allows HR to identify the best recruiting source(s) that yield the highest percentage of high performers.
Why HR Data Integration
Using just one source of HR data such as core HRIS allows users to analyze a limited set of an organization’s performance trends. Users might also be able to make simple forecasts based on previous change rate or seasonality. However, they are missing an opportunity to combine data types for deeper insights into optimizing workforce cost, productivity and performance.
Additional benefits of integrating multiple sources of data include:
Conduct forward-looking analysis and planning
Find potential drivers or causes of a workforce trend/phenomenal
Identify how to best intervene to optimize cost and performance
See the impact of workforce interventions on business performance
Video: The Power of Combining Data Sources
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SOLVE™️ Automates HR Data Integration Process
SOLVE™️ Workforce Intelligence Software helps HR automate the data aggregation, categorization and integration from various systems and reduce the time spent each month on reports and ad hoc analyses by 95%.
SOLVE™️’s data integration framework has received rave reviews from organizations such as General Mills, Southern California Edison, Abbott Laboratories and the Aerospace Corporation for its ability to measure the financial impact of all talent management areas. This past year, we helped organizations from various sizes, industries and analytics maturity levels save millions in the process.
Example 1: Combine Turnover with Recruiting data to assess potential drivers of turnover
Example 2: Combine Turnover and Management data to assess and track managers' performance
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