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Harver employs data to transform the modern hiring experience
技术
- 分析与建模 - 实时分析
- 分析与建模 - 大数据分析
适用功能
- 人力资源
用例
- 实时定位系统 (RTLS)
- 计算机视觉
服务
- 数据科学服务
- 系统集成
挑战
Harver, a pre-employment assessment software company, was facing the challenge of scaling to meet the demands of its growing enterprise customers. Initially, the company relied on labor-intensive statistical analysis in R or Excel to surface hiring metrics to their customers. However, as Harver continued to grow and add more enterprise customers, it had to automate and scale processes in order to provide their growing customer base the insights and customization they expected. The company needed an analytics solution that could also support its multi-tiered product offering, integrate with other tools such as Zendesk, and support multi-tenancy. In addition to the technical functionality, it was also critical that an embedded solution could appear seamless and natural within the impeccably designed Harver platform.
关于客户
Harver is a leading pre-employment assessment software company that enables its customers to transform their hiring process into a digital and fair experience. Founded in 2014, the company has offices in New York, Amsterdam, and London. Harver uses data and machine learning to automate parts of the application, interview, and hiring process for some of the world’s largest global brands, including Sitel, McDonald’s, Heineken, and KPMG. The company's platform is designed to provide real-time, actionable insights to improve the quality and efficiency of their hiring processes. Harver's customer base includes a wide range of global enterprises, and the company is committed to providing these customers with the insights and customization they need to optimize their hiring processes.
解决方案
Harver chose Looker’s embedded analytics offering, Powered by Looker for its ability to replicate and customize customer-facing reports at scale. Looker’s full API coverage allows Harver and their customers to continue to leverage the latest and greatest capabilities and insights. With Looker, the Harver team focuses on their customers and product, rather than needing to spend time and resources focused on building and maintaining thousands of custom dashboards. After defining metrics once via Looker’s git-versioned modeling layer, LookML, Harver can trust that their customers are all looking at accurate metrics, while maintaining the flexibility to efficiently update or customize metric definitions as their customers’ needs change. These updates can be deployed instantly across all customers, saving the Harver team valuable time and ensuring customers insights are fresh and accurate.
运营影响
数量效益
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