Proper data collection and analysis play a crucial role in today’s organizations, guiding decision makers through difficult decisions and directing overall corporate strategy. Considering human capital typically accounts for anywhere between 50-80% of variable costs within companies, HR departments often face intense pressure to optimize their talent strategies and prove that their efforts improve the bottom line. In order for HR teams to become truly strategic partners, they must learn to directly link their own metrics with key business outcomes.
Fortunately, it’s become commonly accepted that employee engagement and performance have a significant impact on corporate health and success. Organizations with highly engaged employees consistently out-perform the market, and understanding how to optimize and reward productive, satisfied employees leads to a tremendous competitive advantage in today’s highly competitive labor market.
And after nearly 20 years of studying employee engagement, the results are unambiguous: it’s clear that the best way to measure how employees feel about their work is simply to ask them, in their own words. This seemingly simple solution, however, is anything but—unstructured data adds another layer of complications. The process of normalizing and analyzing massive amounts of free-text data typically either demands exhaustive internal resources or expensive external consultants. Either way, by the time the results are available, they’re often no longer relevant, much less tied to immediate business outcomes.
Fortunately, artificial intelligence (AI) has proven to be the key to making unstructured data both understandable and useful, which is especially pertinent considering it represents an estimated 80% of all organizational data. And this has certainly proven true in the employee survey space, where advanced sentiment analysis tools like Perception by Ultimate Softwareleverage natural language processing (NLP) to decipher free-text responses with better-than-human accuracy. The most incredible aspect of this technology is that it’s capable of not only understanding what employees are saying, but also how they actually feel, discerning between more than 100 different emotions.
In real time.
Feedback can be filtered and analyzed to determine engagement and satisfaction levels throughout various teams, departments, or even geographic locations. It’s easy to drill down if you see any red flags or, alternatively, to reward leaders whose teams are particularly satisfied and engaged.
But when it comes to overall business strategy, the real power of these insights comes not from isolated metrics but from linking engagement metrics with other critical indicators and analyzing the underlying connection. By coupling Perception with a unified human capital solution like UltiPro®, you can combine engagement results with relevant people data such as performance, retention, and compensation. In this way, the connection between employee engagement and the key business metrics your C-suite cares about, such as performance or revenue per employee, is no longer theoretical. It’s factual.
By creating a powerful and compelling story around your engagement data, you can demonstrate the real business value behind your proposed changes. Ultimately, HR leaders who can logically and concisely demonstrate the connection between talent and business metrics are better positioned to gain buy-in from key decision makers and drive meaningful changes in their organizations.
When positioned appropriately, the data will speak for itself.