Adoption of advanced workforce analytics amongst South African HR practitoners
| dc.contributor.author | Malebatja, Ntswaki | |
| dc.date.accessioned | 2019-02-14T11:23:12Z | |
| dc.date.available | 2019-02-14T11:23:12Z | |
| dc.date.issued | 2018 | |
| dc.description | MBA Thesis | en_ZA |
| dc.description.abstract | ABSTRACT The 21st century is characterised by a volatile, complex and ambiguous business environment which is primarily data driven. Those who are able to derive insight from data obtain a competitive advantage. This can be seen in the medical, engineering and even marketing industries. Due to these successes, the field of management is being challenged to move from “gut-feel” into becoming more evidence-based. It is this transition, into evidence-based management, that affords HR the opportunity to become a strategic partner in business, thus building a strong case for workforce analytics. Workforce analytics is said to offer visibility of trends, the impact of training on business outcomes and improve the quality of hire. Workforce analytics has three levels, namely descriptive, predictive and prescriptive. It is the latter two levels which provide additional value to the business, especially surrounding effective strategy formulation and decision-making. Academic research conducted to date suggests that the adoption rate of the latter levels is slow and HR excellence is an exception in South Africa. Thus, prompting the need for this study. Information gleaned from the literature review revealed that the field of advanced analytics is still in its infancy. It appears that the slow progress is due to lack of widely accepted management principles in the field. Other challenges include HR practitioners’ lack of analytical skills, business acumen, leadership support and organisational cultures that are not supportive of evidence-based management. While there is a strong call for evidence-based management, a critique which is often levelled against it is that human behaviour is unpredictable and therefore cannot be measured accurately. Several frameworks such as the balanced scorecard, human capital model and value-linkage model have been developed to provide instruments of calculating advanced analytics. However, none of these frameworks offer a model for prescriptive analytics. The commonality in the frameworks is that successful implementation requires that the HR practitioner should have in-depth knowledge of the business and advanced statistical competencies – skills which most HR practitioners seem to lack. As such, advanced workforce analytics has become a multi-disciplinary process. To gain an understanding into the South African landscape, the research used a quantitative approach. A questionnaire was distributed to 5,800 HR practitioners across the country. The research found that only 11.8% of respondents reported their analytics as advanced. The implication is that 89% are indeed relying entirely on gut-feel because they are either unequipped or ill-equipped to manipulate data to derive insight. As such practitioners are unable to provide HR intelligence. ii The low rate of adoption of advanced analytics should be of major concern to practitioners and business alike. Evidence-based management, achieved through analytics, provides decision-makers with timeous business information and insight required to make sound business decisions enabling businesses to gain competitive advantages. HR intelligence lies primarily in HR addressing business needs. Analytics, and thus evidence-based management, is but an enabler. Therefore, without a thorough understanding of the business needs, analytics, advanced or otherwise, will be another façade and HR practitioners risk being replaced by dashboards. | en_ZA |
| dc.description.librarian | NM | en_ZA |
| dc.identifier.uri | https://hdl.handle.net/10539/26404 | |
| dc.language.iso | en | en_ZA |
| dc.subject | Personnel management -- South Africa. | en_ZA |
| dc.title | Adoption of advanced workforce analytics amongst South African HR practitoners | en_ZA |
| dc.type | Thesis | en_ZA |