Part 2: Employee Recruitment and Retention
In this two part series, I am exploring how Human Resource departments can utilize data to improve the efficiency and effectiveness of organizational operations and employees’ work.
In the first part of this series, I examined how HR can leverage a broad range of data sets to better evaluate the impact of professional development programs and effectively nurture the learning and development needs of employees. In this second part, I will focus on how data can support the improvement of recruitment practices and retention policies and programs to drive higher levels of operational efficiency, thereby impacting overall productivity and performance.
The Challenges of Effective Hiring and Retention
Despite the growth of emerging recruitment solutions such as LinkedIn, companies continue to experience high levels of inefficiency in identifying, interviewing, and eventually hiring top talent into their respective organizations. Some argue that the process is more art than science, though after careful examination of large recruitment data sets, one may think otherwise. Additionally, recruitment costs continue to rise as more companies aggressively compete for smaller pools of highly specialized talent, particularly in the technology sector.
Aside from the challenges of getting people into your company, it is also becoming more difficult to keep them there and happy. As the competition for talent heats up, more companies are strengthening their benefits packages and implementing innovative strategies for increasing employee satisfaction and retention levels. The costs of these interventions can quickly add up and the return on investments may take longer to realize, or, in some cases, be difficult to measure or even justify.
How Big Data Can Play a Role
If companies make investments to improve their data systems, particularly in capturing larger quantities of highly refined data across the full recruitment cycle and in relation to employee retention policies and programs, then there will be more opportunities to identify key patterns, trends, and anomalies, which can be leveraged or corrected to improve efficiency and performance.
By doing so, companies can begin to address some difficult questions that are often experienced but go unexplained. For example, these could include:
- why a proportion of candidates who are identified as potentials by recruiters are not brought in for interviews by a hiring manager
- why a high percentage of offer letters are declined by candidates from a particular department
- why a costly retention program is being underutilized by employees
This data can be derived from interview notes, recruitment management systems, employee satisfaction/feedback surveys, exit interviews, etc.
The following are two examples of how data collection and analysis has supported the identification of key factors that contribute to recruitment efficiency and effective retention programs.
Examples of How HR Can Use Big Data to Improve Recruitment and Retention
What’s in a Name? More than You Might Think
A company that was collecting highly detailed recruitment data began to notice a pattern emerging amongst candidates below the age of the 28. A high percentage of candidates from this segment were declining job offers than any other segment by age or other attribute.
As the company explored this issue further, it realized that candidates within this segment were acutely sensitive to job titles and were more willing to accept offers if the title conveyed a higher sense of responsibility or authority in the respective area of work.
The company took this finding into account with future candidates in this segment and communicated its flexibility on the naming of titles for the respective roles. Without fail, the numbers began to turn, and more candidates from this segment began accepting job offers — and of course, took on new titles!
More Time with a Newborn May Lead to More Time with the Company
Another company that had implemented a sophisticated HR data management solution began to notice that an increasing proportion of female employees were switching companies just before starting a family. This became known through comments shared by employees during their exit interviews.
The company soon realized that its maternity leave benefits policy was not up to par with industry leaders, and that more could have been done to ensure that new parents were able to adequately balance their personal and work responsibilities upon starting a family. As such, the company modified its maternity leave policy to be consistent with industry leaders and also introduced some innovative family friendly programs — both factors played a key role in reducing the attrition rate within the segment.
Investment in Data Can Go a Long Way
The examples outlined above illustrate the immense value that can be gained for companies and employees when a larger volume of data is captured on recruitment processes and retention policies and programs. Though it may seem to be a high investment in terms of time and costs, comprehensive data management systems hold significant long-term benefits, which undoubtedly outweigh the short-term costs.
As technology becomes more prevalent throughout business operations, it will become much easier to capture the relevant data needed to make more informed decisions about HR policies and practices — leading to overall improved performance and productivity for companies.
What are some ways in which your HR department is utilizing larger data sets to improve employee recruitment practices and retention policies and programs?