Prescriptive analytics on employee’s past education, work profile and experiences can help the employer to carefully craft engagement plans
HR function deals with high quantum of data throughout the employee lifecycle. Data, however in itself, has limited value. Mercer runs extensive analysis on the workforce data that it sources from its clients to draw meaningful conclusions.
One of the researches conducted by Mercer on headcount ratios and span for two different sets of organizations in the BPO Industry aimed at analyzing the headcount allocation at different career streams viz. executives, management, professionals and agents in two different groups. According to the analysis, while third party BPO providers and shared services/captives revealed that the primary driver of the case for outsourcing is cost arbitrage, the focus of the third party providers has typically been on improving margins through deskilling, with ‘need basis’ domain focused roles. The captives engaged high-end skill sets available at economical costs as compared to the parent country. A deeper understanding of the business profile reveals that captives augment the mid-management level for internal stakeholder management, escalation management and for technical expertise. This is more pertinent for some profiles like financial modelling, treasury management, fund management as they are critical to the parent company. This analysis and its application helps an organization to check if they are optimally staffed across levels, if this resulted in improved productivity ~ calculated as Revenue per Full Time Equivalent, and if wider spans resulting in some of the people issues like attrition and lack of knowledge/capability building impacts business continuity management. So broadly, the application of workforce metrics can be across multiple inter-related disciplines, each yielding a different insight into organization structure, focus areas and the impact it has on all quadrants of the scorecard like financials, clients, processes and people.
A more interesting advent of the analytics is predictive analytics. Once sufficient analytics is conducted on attrites over a period of time and recurring factors are identified, which can help in establishing a predictive index. Coefficient correlation analysis applied on the factors can help arrive at the predictive index, which when applied to a newer set of employees can help predict the attrition possibility. Some of these could be tenure with the organization, kind of process/project, tenure in the process/project, manager tenure in the role, specific qualification, performance ratings, last promotion time frame and similar parameters, which impact the state of engagement of an employee with the organization thereby impacting attrition. This analysis when used well can help identify employees in high attrition probability and preventive measures can be taken accordingly.
Take a step forward and we can experience prescriptive analysis. Prescriptive analytics on employees past education, work profile, experiences can help the employer to carefully craft engagement plans. It is an extension to attrition prediction but a more proactive approach to use it for deepening the employee connect with the current organization. Once the attrition prediction model helps in identifying the employees in red zone, the prescriptive analytics could help understand what’s in the employee mind, what employees at different tenure levels and/or different work groups value, what do they aspire for and then intelligently piecing it all together to arrive at action agenda to improve engagement. Clearly, the application of predictive analysis is not just limited to improved retention but also in creating a more engaged workforce and (if we were to extend the concept of vacancy cost) huge financial savings as well. It is safe to conclude that analytics in HR results in a balanced approach to review data and information available, draw meaningful insights and use it to take proactive actions towards creation of a robust organization.