Your firm is awash in workforce data and your team of data scientists have been charged with making sense of it and extracting meaningful insights the business can use. How do you do this? There are many different approaches to analyzing workforce data to choose from but the amount of relevant insight yielded really depends on the goals of the analysis.

If the goal is to take more of a traditional approach to workforce analytics, where the same datasets are massaged to try to squeeze ever more meaning from them then there’s no need to change the business as usual approach.

However, if the goal is to introduce a new dataset that more directly measures a huge factor affecting business performance (people themselves), in a way that these traits be combined with all other business data for correlations and new insights, then it’s worth considering adding Talent Analytics’ dataset about the people themselves. Talent Analytics’ dataset isn’t a replacement for what workforce analytics currently measures, but an enhancement.

How Does Talent Analytics’ Dataset Enhance Workforce Analytics Projects?
Current “workforce analytics” measures things like – Attrition went down by 15% last year. Traditional workforce analytics can answer “why” to some degree, but could use a lot of help in this area. If you add our talent analytics to this mix, you could find out if there are any patterns about the people themselves, the people who are leaving.

• Are those resigning the competitive, results oriented people that might be taken aback by the company’s new policy on additional benefits which end up costing everyone in the firm to pay a bit?
• Are those leaving the more Altruistic ones, who might be taken aback by the new policy that reduces holiday time and vacation by 40%?
• Are the people leaving ones who had their titles downgraded by a recent merger?  For many this change in title is not as important, for many it is more precious than gold.
• Are those leaving ones who were counting on reimbursement for college and advanced training – again, this for some this is more precious than gold.

What is interesting is that with the examples above, in addition to reporting on why history happened, the addition of our dataset moves the discussion towardspredicting and preventing instead of only reporting on what has happened.

Meaning, having talent analytics would allow leaders to predict the employee impact on performance before rolling out a new program. Having talent analytics available for inclusion in predictive models allows businesses to look for and often find a direct link between performance and employee traits.

For your next workforce analytics project, do you want to deliver more than business as usual workforce insights?

This blog was written by Greta Roberts, CEO, Talent Analytics, Corp. Follow her on twitter @gretaroberts.

Note: originally posted at TalentAnalytics.com.