What are the features of an HR analytics solution?

The key features of an HR analytics solution

1. They answer the business questions the C-suite asks. This may require that you invest in a solution to address each question, leading to investments in multiple analytics solutions for granular data on each question. Alternatively, you may choose a unified solution that can assess multiple metrics to answer each business question.

2. They are easy to use by individuals who are not data scientists. An accessible solution created for laypersons is ideal when they want to assess any one or more metrics without interrupting the workflow of the data scientist.

3. They are cloud-based rather than on-premise. A cloud-based solution also aids accessibility without heavy IT integration. This grants HR the autonomy to use the solution as and when needed.

4. They are powered with statistical analysis and machine learning technology. Big data platforms require advanced data management systems powered by machine learning and natural language processing. This allows the technology to learn and reason autonomously, revealing insights that data scientists can then analyze.

5. They are based on predictive analytics. “[Predictive analytics is] the practice of extracting information from existing data sets to determine patterns and forecast future outcomes. Analysts use statistical methods to forecast future alternatives – will the current termination rate continue at the same pace or might we expect a surge of exits as the job market strengthens?” explains Collins.

6. They are powered with visualization technology. A visual representation of vast amounts of data can allow for better understanding of trends and events. The complex data processed through an analytics engine requires advanced visualization software, as it cannot be presented in simple charts and presentations.

7. They are available through a subscription model. Subscription models of software as a service (SaaS) platforms are useful because they easily allow you to access the latest upgrades in technology. They also eliminate the significant upfront expense of purchasing an analytics solution and may be a more cost-efficient way of investing in analytics.