People Metrics are a crucial way of analyzing the successes and failures of your department’s outreach, influence, programs and processes.
The data hidden within is an important catalyst for the development and change of both your strategies and those of the business. Allow your metric data to guide you financially and highlight your best talent, serving as proof of your impact and a record of progress.
There are different types of analysis we can use when attempting to connect our human resource goals to our organizational strategy.
HR People & Strategy, the executive network of the SHRM published the whitepaper “Maximizing the Impact and Effectiveness of HR Analytics to Drive Business Outcomes,” and recommends the use of cause-effect analysis and regression analysis to “conduct effective HR analytics to conclusively show your business impact within the organization.”
Cause-effect analysis
This practice focuses on Structural Equations Modeling (SEM), to “consider multiple independent & dependent measures concurrently, imply cause-effect relationships and correct for measurement errors.” Cause-effect is helpful when dealing with a volume of different scenarios, and allows HR to clearly see the effect of any improvements, implementations or developments within their company.
Regression Analysis
The regression technique provides the ability to search through various areas of data at the same time, to “help prioritize the impact of people data on business outcomes. Regression is used to show the connection from attitudes to attitudes on an employee opinion survey.” In contrast to cause-effect analysis, regression will not outline the correlation between impact and implementation.
Upon deciding which technique will most benefit your specific need, the next step is to conduct your analysis and consider which areas your department must focus on in the upcoming year.
Most of us will be concentrating on financial data first and foremost, as this branches out into every other aspect of human resource work. Your metrics will show you whether the outcomes of employee training, engagement exercise and any other talent-related communication was monetarily worthwhile. Similarly, you can assess whether any new technical equipment has been beneficial in your time and money management.
Another important aspect not to overlook is any employee survey responses that have been conducted. Cross-reference these with your data and see if you are neglecting any areas of employee wellbeing.
- Did employees request more training in some areas?
- Does your data show that you provided that training, and if so was it successful?
It may be hard to remain people-centered when staring at a screen full of reports, but using this data to your advantage can further the success of your department.
After defining your areas of improvement, you must then implement them into your organizational strategy – failing to do this will simply mean you are cheating yourself of improving on mistakes you found in your metrics data.
You may come across issues that you were previously unaware of, and acting upon this is crucial when aligning your upcoming goals.
When planning your strategy, your data can be sampled as references when presenting new policies or programs to your company’s executives. Use them as examples to prove your credibility, and stand behind your facts.
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View Comments (3)
Great post! You've shared a lot of info here that I wasn't really familiar with before. Metrics data is definitely important for so many reasons! I agree that doing some cross-referencing will really help you improve in areas that may be neglected currently.
Yes, Human Resource Metrics are a crucial tool for any HR department. What is most important though, is how the data is then analyzed and implemented. The proper implementation of data will help you stay on track and achieve your goals.
Agree heavily with your last point, it's not enough to gather data, you also need to be able to read that data and effectively implement it. Sometimes that means someone taking a stand and being a leader.