Data-driven human resource (HR) management systems are arming managers with facts to improve employee management and are also helping the company to attract and retain staff more effectively, says JSE-listed information technology multinational Dimension Data Middle East and Africa HR executive Michaela Voller.
Voller reviewed the company’s applicant interview and employee induction processes and found them to be subjective and with design flaws that did not effectively meet the aim of attracting talented individuals and smoothing the entry of new employees into the company’s operational environments.
The company decided to digitise the induction process, which led to the development of a mobile application (app) that new employees used to view induction and safety videos, as well as access orientation information and co-worker profiles.
“The interview and induction processes relied too much on ungoverned business practices and were subject to human error. They had become uncoordinated,” she explains.
The app also has various completion targets and rewards, also provides initial work objectives to employees, as well as helping to manage their workflow, and provides employee benefit information, such as tax incentives for school fees and food that the employees can access.
Digitalisation of its induction processes presented a quick and easy solution for Dimension Data as part of its broader digitalisation journey, and helped it to explore various use cases and applications, as well as establish best practices without disrupting services to clients.
“We took a design-thinking approach and rolled out the new system over eight weeks. We used an off-the-shelf app (South African-developed Hello Crowd) rather than building an in-house app to accelerate implementation. We also have two-weekly reviews – armed with data and facts provided by the feedback from the app – that we use to review the entire process and each individual element,” Voller says.
Dimension Data is also in the process of digitising its interview processes to improve its engagement with potential employees and base its assessments on data instead of the perceptions of managers.
“We applied facial recognition, artificial intelligence, as well as personality and psychometric systems to our candidate interview processes. “This provided us with a wealth of new data and parameters with which to assess candidates and revealed flaws in our processes.
The company also provided a way for candidates to rate the interview and the person who interviewed them, and express their views of the interview conducted because we found some evidence of subjectivity on the part of our interviewing managers.
Specifically, the new data helps the company to empirically improve its processes, better assess where candidates can fit into its operations and reduce the human bias in these processes.
“These new systems also enabled us to give choice and agency to the individuals we were engaging with, check managers’ decisions against the data and reduce the impact of own biases on hiring and career management processes.
“We found that we tended to hire memorable people. While this is understandable, we should be hiring the best candidates for the company,” Voller explains.
The data derived from the app and high-technology interview systems also allows Dimension Data to more effectively engage with the talent pool in the industry and, owing to the transparency of the engagement with candidates and more individualistic engagement, improve its ability to approach candidates at a later stage.
“The new data-driven approach provides a human touch to this business function, especially the engagement with and management of our most important resources: our people. I believe that HR management can provide greater value at greater speed to support business objectives by taking a fact-based approach.
All the new systems meet Dimension Data’s business requirements and regulatory obligations, including personal information regulations that ensure that candidates’ information is deleted after a set time and [requests] for their data to be deleted,” Voller concludes.