This shows that analytics has the potential to impact talent management at every level but may also signify that analytics is viewed as a catch-all.
It takes a specific analytics plan and strategy to turn predictive modeling into a useful tool, especially for “Productivity” and “Leadership,” which had the largest score in the “very high” designation.
Question: To what extent are the following analytics important to your organization?
An interesting interpretation of this data suggests that actual outcomes, such as increases in productivity and retention, are more important than a measurable ROI.
This is further borne out by the most important metric in the realm of productivity being the ability to place employees to maximize performance, which could lead to significant gains but the volume of changes may make attribution of success very difficult.
HR professionals recognize that leadership talent must be nurtured by placing it in the right position that match their functional expertise and leadership strengths.
Determining Who to Keep and Promote
Survey respondents overwhelmingly sought out analytics to help them solve concerns identifying and predicting who should be retained because they’ll become a star leader.
5 Keys to Buildiing a Leadership Team – by Louis Carter
Some important responses to consider:
• 82% want analytics to help them determine the best training and development approaches for their top talent.
• 80% turn to analytics to determine what characteristics demonstrate or predict team leader effectiveness.
• 73% say the top retention analytic goal is determining who HR professionals should strive to keep based on projected future contribution.
An HR team’s strength is in its ability to understand the intersection of employee strengths and firm resources. The ultimate goal is to use analytics to determine the most effective training methods and applying them to the employees with the highest probability of being future standout employees.
Past research from the Best Practice Institute has identified a few key attributes that top executives share, especially when looking at globally influential brands.
These characteristics can generate significant returns when tracked and include:
1. The ability and desire to acquire new skills quickly.
2. The ability to bring together people of disparate backgrounds.
3. A knack for maintaining operational efficiency in unfamiliar environments.
4. Vision to build organizational support that incorporates both creative solutions and specific action steps.
5. The mental fortitude and willingness to understand new people, cultures, and situations.
Identifying these elements and building metrics that track them as a whole or in part — such as crafting an algorithm that predicts whether an individual will improve after training — becomes easier when using currently effective management as a baseline.
When algorithms and metrics are validated by future growth, increased buy-in and funding can be easier to achieve if leadership sees itself as a model for success.
Where Should You Start?
Software is often the most compelling eye candy when HR practitioners find a little room in the budget for analytics improvements. We often tend to think we need to find that money before anything can be done, but that’s not the case for many professionals.
The first place to start is reviewing the systems and processes already in place. This includes both your analytics paradigms as well as your review process that generates the data used in your analytics. Reviews happen much less often than you’d think.
More than half of respondents check revisit their analytics capabilities once a year or less.
If you’re not reviewing your analytics processes often enough – we suggest quarterly or when your company and its workforce undergo any significant change — you’re making it more difficult to achieve your goals.
Reviewing employee progress more often has proven to yield better results for retaining top talent and addressing employee inefficiencies. This information is the perfect guide to improving your analytics by marrying predictions with results. However, waiting to revise an analytics strategy until this data is “cold” can mean significant missed opportunities in the interim.
It may take a significant investment, but brands like Microsoft have proven that competency modeling with repeat revisits can yield significant gains and raise baseline efficiency in just a few years.
HR professionals told us that they have many high hopes for analytics programs, but putting a paradigm into practice can be difficult. Talent management analytics is mature enough to have established best practices. So, HR leaders can benefit from seeking out training, research, and events that provide real-world examples of analytics in play.