SAS adds predictive modelling capabilities to leading human capital management solution

Organisations are now able to accurately predict which employees are most likely to resign voluntarily, allowing them to introduce intervention strategies key staff, as well as address the cost and competitive issues associated with employee turnover.

New predictive modelling functionality enables businesses to address challenges such as voluntary employee turnover of key personnel and the associated effect on diversity in the organisation. Since staff turnover has a very large direct and indirect impact on costs, for instance recruitment and training costs as well as potential loss of crucial knowledge and skills, it is important that companies understand why turnover is happening and how and where it's directly impacting the organisation.

SAS, the leader in business intelligence, has announced the addition of advanced predictive modelling functionality to SAS Human Capital Management. One of the most significant new capabilities is that of determining which employees are most likely to resign voluntarily.

"With this unique insight, available only from SAS, organisations can proactively implement targeted retention and succession planning strategies," says Annemarie Cronje, solution architect, SAS Institute SA. "As a result, they can retain the specific employees or groups of employees whose skills and knowledge are essential to the business's success."

Because every organisation has unique factors that contribute to staff turnover, this newly enhanced human capital management solution uses SAS's industry-leading data mining techniques to calculate groups of employees most likely to leave a specific company. It determines which organisational and common employee characteristics, such as salary, level of education and training or length of service, contribute to turnover. Additionally, employees are ranked and assigned individual probabilities for voluntarily leaving within a specific time frame.

If the firm's ability to compete in the market in the future relies on specific skills sets, it helps to know when the human capital possessing those skills is likely to leave. Knowing the mix of age, length of employment, where employees stand in pay scale range (the span between starting salary and upper end of salary range) helps predict when companies are likely to lose key employees. Armed with this insight, organisations can proactively align their workforces in support of corporate business objectives. This is increasingly important given the possibility of a looming economic rebound and a gold-rush for skilled staff in particular areas.

The Herman Group, which focuses on workforce development, identifies an interesting trend - one worth watching, if you can manage to see it. The consultancy reports that companies with leading human resources practices have already begun to add to the "bench strength" despite the ongoing uncertainty of the US and global economies. Those companies use "ghost-hiring" to add the types of employees they will soon need (when the economic slump reverses) based on "calculated strategic staffing, congruent with the corporate plan".

The Herman Group reports that some companies with hiring freezes even reach agreements with top prospects. Once those prospects have successfully run through the traditional hiring gauntlet - to essentially remain in the on-deck circle until the company is ready to lift its hiring freeze.

An overriding concern for HR managers is that, as the global economy continues improving and competitors begin hiring, it is very possible that those people most critical to their organisation's success may begin leaving.

"HR has faced challenges before, but perhaps none as significant as what could become the most severe shortage of skilled labour in history," says Betty Silver, SAS worldwide human capital management strategist. "Organisations can align their workforces, but only if they understand where their vulnerabilities lie. This is precisely the insight that only SAS Human Capital Management delivers using SAS's industry-leading predictive modelling capabilities."