Founded in 1994, this company has for over 20 years remained at the forefront of key concepts and functions to design, engineer, validate and manufacture. Their primary focus hovers around drivelines, metal forming, powertrains and casting technologies for automotive, commercial and industrial markets.
Continued efforts have since helped become a tier-1 automotive supplier with capabilities across multiple product lines to deliver powerful, innovative and efficient solutions. As of FY2016, they has posted a revenue of $3.95 billion.
As a tier-1 player in the automotive supplier industry, they possessed an army of skilled engineers scattered across different functions within the organization. However, time revealed a couple of cracks in their workforce structure.
What were their concerns?
1. UNIDENTIFIABLE EMPLOYEE BUCKETS
With a multitude of engineers, they sought efficiency by bucketing their employees into component, systems & application engineers.
2. BEHAVIOURAL + TECHNICAL COMPETENCY ANALYSIS
While they understood the varying competencies required both technically and behaviourally to bucket their engineers, the execution of the same proved puzzling.
This company partnered with Mettl and its team of experts, a company that had since its inception remained at the forefront of assessment technology. Consistent interaction with relevant stakeholders further set the cogs in motion. The exercise netted two moments of note:
INTEGRATED ASSESSMENTS (PSYCHOGRAPHIC + COGNITIVE)
Psychographic profiling unveiled innate behavioural competencies; the cognitive segment of assessments worked to reveal an employee’s adeptness to one of the three buckets: systems, application and component.
Post-Assessment diagnostic reports were delivered to both managers and engineers. While the employee report provided detailed insights based on what was revealed, including strengths and areas of development, the manager reports possessed added recommendation on how best to use the data presented.
The project included 450 employees. Assessments – both psychometric and cognitive in nature – provided managers with employee inclination towards a particular bucket.
In conclusion, they could map their workforce more efficiently behind proof of hard, data-driven analytics and numbers.