The Growing Importance of HR Analytics
According to a Best Practice Institute (BPI) survey of over 50 organizations, HR professionals view almost every aspect of workforce management as highly important for analytics. This indicates that analytics can impact talent management at every level. However, it also suggests that analytics might be seen as a general solution without a clear focus. To be effective, a specific analytics plan is necessary, especially for "Productivity" and "Leadership," which were rated as the most important areas.
Interestingly, the data suggests that tangible outcomes like increased productivity and retention are valued more than a measurable ROI. For instance, the top productivity metric is the ability to place employees in roles that maximize their performance. While this can lead to significant gains, the complexity of attributing success makes it challenging.
Using Analytics to Determine Who to Keep and Promote
Survey respondents consistently use analytics to address challenges in identifying and predicting which employees will become future leaders.
Key findings from the survey include:
- 82% of respondents want analytics to help determine the best training and development for their top talent.
- 80% use analytics to identify the characteristics that predict team leader effectiveness.
- 73% state their top retention goal is using analytics to determine which employees to keep based on projected future contributions.
The primary strength of an HR team is understanding the intersection of employee strengths and company resources. The ultimate objective is to use analytics to identify effective training methods and apply them to employees with the highest potential.
Key Attributes of High-Potential Leaders
Past BPI research has identified several key attributes common among executives at globally influential brands. Tracking these characteristics can generate significant returns.
- The ability and desire to acquire new skills quickly.
- The capacity to bring together people from disparate backgrounds.
- A talent for maintaining operational efficiency in unfamiliar environments.
- The vision to build organizational support with creative solutions and clear action steps.
- The mental fortitude to understand new people, cultures, and situations.
By identifying these attributes, organizations can build metrics to track them. Creating an algorithm to predict an individual's improvement after training, for example, becomes easier when using current effective leaders as a baseline. When these algorithms are validated by future growth, it becomes easier to gain leadership buy-in and funding.
How to Get Started with Talent Analytics
While new software can be tempting, it isn't the necessary first step. Many professionals can make significant improvements by starting with what they already have.
Review Existing Systems and Processes
The first step is to review the systems and processes currently in place. This includes not only your analytics models but also the review processes that generate the data. Shockingly, more than half of survey respondents revisit their analytics capabilities only once a year or less.
These infrequent reviews make it harder to achieve strategic goals. We recommend reviewing analytics processes quarterly or whenever the company and its workforce undergo significant change. More frequent reviews of employee progress have been shown to improve talent retention and address inefficiencies. This data is the ideal guide for refining your analytics by comparing predictions with actual results. Waiting until this data is "cold" can lead to significant missed opportunities.
While it can require a significant investment, companies like Microsoft have demonstrated that competency modeling with regular revisits can yield substantial gains and increase baseline efficiency within a few years.
HR professionals have high hopes for analytics, but implementation can be challenging. The field of talent management analytics is now mature enough to have established best practices. HR leaders can benefit from seeking out training, research, and events that offer real-world examples of analytics in action.