Automating recruitment performance reports using natural language, to improve the productivity of the HR team.
CLIENT: A PRIVATE SECTOR BANK
INDUSTRY: BANKING AND FINANCE
FUNCTION: HUMAN RESOURCE
USE CASE: RECRUITMENT PERFORMANCE REPORT
Being a robust player in the banking industry, India’s largest private sector bank keeps catalyzing automation and technology within the organization. Having an employee strength of 100,000 employees across regions, their human resources team was facing difficulties in managing recruitment timelines and reporting processes efficiently.
On a day-to-day basis, the leading bank has nearly 8000 – 11000 vacant positions with only 3 – 5% closures. Recruitment being a continual activity, the bank required an efficient reporting solution to fast-track their hiring process at an optimal cost.
Recruitment Constraints identified due to Manual Reporting
Onboarding talented resources in the expected timeframe was a major challenge for the talent acquisition team. Additionally, monitoring & optimizing the important KPIs like cost-per-hire, attrition and retention rates was a tedious task.
The cost of recruitment was on the rise but the ideal medium for sourcing talents was unknown. Meanwhile, though data was available in abundance, manually exporting it from the SAP system, analyzing and creating personalized reports for each level was extremely time-consuming
As a result, critical hiring decisions were either delayed, dismissed or made on gut instinct.
Key problems identified:
- Unavailability of personalized reports for top management and other levels.
- Talent acquisition teams are unable to analyze and interpret the data at hand.
- Data extraction from SAP system.
- Manually cleaning and structuring the extracted data.
Removing the Bottleneck
The decision-makers at the bank realized they needed a solution that would help them break-through these challenges and give the staffing team the ability to efficiently meet their recruitment timelines, at low costs. This was possible if the entire human resource division had access to timely, accurate and understandable insights in the form of recruitment performance reports to take data-driven actionable measures.
- Phrazor, a natural language generation & reporting automation platform helped the bank, simplify the recruitment reporting process by fetching complex datasets from their SAP system and converting them into easy-to-understand, narrative-based reports.
- In partnership with vPhrase, the bank’s analytics team could identify and establish key performance indicators (KPIs) to measure the recruitment team’s efforts against the quality of hires. The reports now consisted of useful performance metrics like the no. of offers, resignations and hires, visible right at the top for them to take quick actions.
- Utilizing Phrazor, the private sector bank was able to create personalized reports for each representative of the human resource team, from the service delivery head, regional heads and all the talent acquisition partners. The top management could now easily spot the departments & branches that needed attention in hiring
- The team could also recognize effective channels of recruitment marketing against the cost, quality, and consistency of the resources. Thus, they could promote their brand and company culture on the most successful job boards and web platforms to optimize their recruitment marketing strategies.
How India’s largest private-sector bank leveraged natural language generation platform, Phrazor?
Using natural language generation and intelligent reporting automation, the recruitment team could:
- Auto-create thousands of personalized recruitment reports at the speed of thought
- Understand complex hiring metrics with easily readable, human-like language.
- Fast-track the recruitment process by getting access to meaningful and right-at-the-top insights.
- Parallelly compare time-to-hire & time-to-fill of different teams and branches to identify the hiring feasibility and talent shortcomings.
Manual effort saved in report generation
Sent weekly to all the stakeholders with
Saved every week in SAP data extraction
and manual data cleaning.