Every day we are producing mass amount of information. According to the estimation of Zettaset*, we create 2.5 quintillion* bytes of data every day and 90% of the data in the world today has been created in the last two years alone. This massive volume of information and the technology required to store it is called with the term Big Data. Even though big data is not such a new phenomenon, the concept of Big Data is one of the new hypes of the recent years. Indeed the real new thing is the analyses of the big data and the meaningful results as a result of the analyses.

One of the main classifications of big data is structured data versus unstructured data. Structured data refers to information which is classified with a high degree of organization and is readily searchable by simple search operations. An excel sheet which shows the applicants of a job post is an example of structured data. Unstructured data is essentially the opposite of structured data. It refers to information which is not organized in a pre-defined manner. Unstructured information is typically text-heavy, but may contain data such as dates, numbers, and facts as well. The content of job post applicants’ CVs and accompanying cover letters are examples of this kind of data. Analyzing structured data is easy whereas analyzing unstructured data is complicated. New technologies are evolving to help the analysis of unstructured data.

Analyzing big data has already become a basis of competition in various fields. There are many examples of critical insights and successes being realized in business, politics, and government. In addition to these fields, Human Resources (HR) also has the opportunity to use Big Data in the company’s people strategies. By using analytics tools and techniques; organizations can develop a “people model” for their teams, and understand precisely how these people-related factors directly relate to business results. They can use this data to assess leadership pipeline, engagement factors, and potential workforce gaps in the future.

Today there are growing numbers of success stories emerging in the HR field. I would like to share some of these examples to give insight into the subject.

Big Data is used by some companies to analyze the profile of high performers in the company. In an example cited by Bersin and Associates*, one of their clients that operated in the finance sector, operated under a belief system that employees with good grades who came from highly ranked colleges would make good performers. So the company’s recruitment and promotion process was based on these academic drivers.

Several years ago one of their analysts performed a statistical analysis of sales productivity and turnover. The analyst and the company looked at sales performance over the first two years of a new employee and correlated total performance and retention rates against a variety of demographic factors. What they found was really surprising.

According to the results of the analysis 6 things were highly correlated with success of the sales employees. Best sales professionals in this company;

1. Had no typing errors or grammatical mistakes on their resumes
2. Did not quit school before obtaining some degree
3. Had previous experience of selling real-estate or autos
4. Demonstrated success in their prior jobs
5. Had the ability to succeed under uncertain conditions
6. Managed time effectively and ran multiple tasks at the same time

According to the results of this study what did not have an impact on the performance of the sales employees was;

• Where they went to school
• What grades they had
• *The quality of their references

Data analysis showed a different fact than the belief system of the company. The results were taken into consideration and the recruitment process was modified accordingly. In the fiscal period following the new recruitment process, the company had more than $4,000,000 improvement in revenues.

In another example cited by eQuest*, they provided consultancy service to a financial institution with the aim to increase recruitment process performance. The firm made an analysis of the existing process and realized that the company was utilizing 48 different job boards and spending almost $175,000 per year for those. The consultants aimed to utilize the job posting service and after big data analysis they found that 45 of these sites showed no response within a reasonable time frame. Only 3 of the current boards were producing reasonable candidate response rates. In addition to this, they also found the words and phrases candidates were searching and the company improved their job posting titles and descriptions. In the end the candidate traffic soared by 175% and annual spending for recruitment advertisement decreased by 50%.

In addition to the utilization areas in the above examples, big data analysis can also be used to measure effectiveness of training programs and to identify training needs for future programs. Today training effectiveness is generally measured according to KirkPatrick’s and Jack Phillips’s evaluation models and the biggest emphasize is on the training program’s impact on job performance. In addition to the mentioned evaluation methods, big data analysis is also a promising way to see the correlation between job performance and a training program. We can use the information of training participation and post exam results following a training program to investigate the correlation between the program and job performance of the participants, hence we can evaluate the effectiveness of the program. Additionally big data analysis can be used to determine training needs. Data regarding application logs, reversal transaction logs and customer complaints can be analyzed to determine training needs.

Big data analysis has a remarkable potential in the field of human resources and such analysis can be used to improve business results, performance of recruitment processes and the effectiveness of training programs. HR should seize this valuable opportunity to reinforce its position as a strategic partner of the company.
*Special thanks to my workfellow Mehmet Hamdi Özçelik for his contributions

Additional Information
Zettaset*: Software development company based in the USA
Quintillion*: A thousand raised to the power of six (1018)
Bersin and Associates*: Consultancy company providing services in corporate HR
eQuest*: Job posting delivery company based in the USA

Resources:
2012: The First Big Data Election. Retrieved 09 02, 2013, from Harvard Business Review Blog: http://blogs.hbr.org/hbr/hbreditors/2012/11/2012_the_first_big_data_electi.html
Bernstein, D. eQuest. Retrieved 08 30, 2013, from You Can Do Big Data, Today!: http://www.equest.com/floating-point/you-can-do-big-data-today/
Bersin, J. Forbes. Retrieved 09 01, 2013, from Big Data in Human Resources: http://www.forbes.com/sites/joshbersin/2013/02/17/bigdata-in-human-resources
Chand, S. venturebeat.com. Retrieved 08 31, 2013, from How big data will impact employment and human resources: http://venturebeat.com/2013/08/06/how-big-data-will-impact-employment-and-human-resources/
Giuffrida, M. (2013, 06 28). http://talentmgt.com/. Retrieved from HR Can’t Ignore Big Data: http://talentmgt.com/articles/view/hr-can-t-ignore-big-data