实例探究 > Global HR Analytics improves Talent Retention Rates

Global HR Analytics improves Talent Retention Rates

公司规模

Large Corporate

产品

Synthetic Data Repositories

技术栈

Synthetic Data Generation
Data Anonymization

实施规模

Enterprise-wide Deployment

影响指标

Cost Savings
Employee Satisfaction
Productivity Improvements

技术

分析与建模 - 预测分析
分析与建模 - 数据挖掘
应用基础设施与中间件 - 数据交换与集成

适用行业

电信

适用功能

人力资源

服务

数据科学服务
系统集成

关于客户

The customer is a large telecommunications company with over 90,000 employees. The company operates on a global scale and faces significant challenges in managing its workforce. Employee turnover is a critical issue, and the company is keen on finding innovative solutions to improve talent retention. The company deals with a vast amount of sensitive employee data, which is subject to stringent legal regulations. This makes it difficult to analyze the data effectively and derive actionable insights. The company is looking for ways to streamline its HR processes and leverage data analytics to enhance employee satisfaction and reduce turnover rates.

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挑战

A large telecommunications company wanted to find new ways to reduce employee turnover and improve talent retention. Over 90,000 people’s sensitive data needed to be collected and analyzed to identify patterns in employee churn. However, legal regulations locked up the data, and manual anonymization of datasets for each analytics project took 6 weeks on average.

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解决方案

The HR Analytics project took off when readily shareable synthetic copies of siloed HR data assets were created and distributed. The resulting synthetic data was no longer classified as personal data and so it was exempt from legal regulations. The synthetic copies were statistically highly representative of the original data, enabling the analytics team to find the same insights they would have found in the original. This approach allowed the company to bypass the lengthy manual anonymization process, significantly speeding up the analytics projects. The synthetic data enabled the team to detect patterns leading to employee churn, identify employees most at risk, and develop targeted interventions to retain talent.

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运营影响

Using synthetic repositories, the analytics team detected patterns leading to employee churn.
The team identified employees most at risk of leaving the company.
Developed targeted interventions to retain high-risk employees.
Enabled the company to take proactive steps to improve employee retention.
Increased team productivity by streamlining the data analysis process.

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数量效益