Struggling with finding IT staff members who were able to communicate with end users about business and programmers about technical requirements, a major aerospace company went out on a limb and decided to hire persons with liberal arts and music backgrounds. Prior to deciding to do this, the company commissioned an HR consulting firm to perform research on the qualities and attributes of exceptional systems analysts. The study came back showing high correlations between musical aptitude and computer programming. In earnest, the company began hiring “non-technical” graduate students with strong learning abilities from local universities — and at last found a way to end its IT-end user business communications breakdowns.

Unable to teach the operationally-oriented tellers in its branches to hawk its products and services to customers who were there to do their banking, a major financial institution decided to tread new ground by breaking with the tradition of hiring “strictly banking types.” Instead, it opted to hire people into its branches who had prior retail experience. The new hires came with the ability to interact with customers and learn what customers really needed and how the bank could help. These new employees also helped the bank’s bottom line with increased sales.

Neither of these real-world hiring examples constitutes the model of the textbook hiring that companies and their CXOs by custom adhere to. Instead, both examples represent bold departures from the rank and file hiring practices that dominate companies, and that are more set on playing it safe with new hires by only looking for specific training and experience that exactly maps into the responsibilities of jobs that organizations are trying to fill.

But great hiring doesn’t always work that way. Sometimes a high tech company will hire the head of a cookie and cracker conglomerate as its CEO , or a rap star will become a multi-million dollar sports agent.

This is why today’s availability of big data can get at the bottom of characteristics and qualities of individuals and their abilities — and not just what they present on a resume — can greatly assist CXOs in making key hires and at better understanding the skillsets and qualities of employees already on the job and how their roles can be expanded.

It was only two years ago that research into 31 corporate case studies revealed that it was costing companies an average of 20% of each employee’s salary to replace employees in jobs earning less than $50,000 per year. As salaries increased, so did employee replacement costs. Consequently, the same study revealed that it could cost a company as much as 213% of an executive’s salary to replace that executive.

High turnover also causes companies to lose productivity, to lose knowledge, and to redouble efforts in renewed training and interviewing costs for replacements — not to mention the potential loss of goodwill from remaining staff, which must now work harder to make up for someone who has left.

By using big data as an “insight generator” into the best qualities and attributes of people who do a certain job well, companies can reduce turnover and enhance overall staff morale. CXOs and especially HR executives who use these more data-driven systems also increase their odds of hiring great people into the positions they are best suited for the first time around. This is why capitalizing on big data opportunities in HR that can lead to productive (and lasting!) hires should be on every CXO’s short list — because the age-old adage still holds true: “People are a company’s most important asset.”