Harnessing Big Data to Solve Talent Crunch

Puducheri noted that human resources professionals need to help business leaders understand the implications of analytics to make the right people decisions. Using analytics in its competency program allows Halliburton to identify issues with profitability, safety and efficiency in individual business units and to design specific interventions for these units in order to attract and retain workers.

A company’s business strategy needs to be tied into its human capital planning. By doing so, companies can determine if they are hiring for the right skills and discipline and if they are designing retention programs that have an implication on how long new college graduates stay with a company.

Predictive modelling is about having a disciplined process to drive decision-making, such as determining the likelihood of a worker leaving in X number of years. Using analytics means that companies not only can have a seat at the table, but will be able to set the table, Puducheri noted.

“At the end of the day, analytics is about managing the health of a culture,” said Michael B. Howe, vice president of human resources at drilling contractor Ensco, during a panel discussion at the conference. “All of us are in the same war for talent, competing with each other to some degree, and to retain workers, we need to create a culture where people will want to stay, even when the inevitable cooling off of our industry takes place.”

Howe said that drilling companies are behind peers and major oil and gas companies in terms of human resources initiatives, but Ensco is starting to employ analytics in its HR planning. As part of its strategy to retain talent, Ensco introduced a strategy of getting its human resources professionals in front of customers, visiting rigs, to gather data and “to put the human back in human resources,” Howe noted.  

Ensco’s early rudimentary steps in introducing analytics into its business operations involved looking at the correlation of attrition statistics relative to downtime and safety. By being able to slice and dice data, Ensco has been able to determine that rigs with a higher voluntary attrition rate of workers was more likely to experience a safety incident, and to identify which rigs might need more investment of training or other efforts to reduce attrition.

Ensco used analytics to determine whether compensation levels need to be increased among workers. In one case, Ensco found that two positions in its onshore operations – which had lower pay rates and where experienced and new workers were receiving the same level of pay – was dragging down the overall score of pay in its first worker feedback survey conducted in 2012.