Problem statement
A leading innovator in electrification software struggled with inefficient resource planning caused by poor data quality, fragmented systems, and manual processes. Inconsistent and inaccurate information across multiple projects and workforce platforms led to misaligned staffing decisions and the lack of a reliable, real-time single source of truth. Their monthly planning cycle was manual, unstructured, and prone to delays, while limited visibility into future staffing needs resulted in overallocation, underutilization, and rising costs.
These challenges resulted in:
- Delays in Workforce Allocation: Misaligned projections hindered timely staffing.
- Reduced Operational Efficiency: Manual processes and data reconciliation slowed decision-making.
- Limited Scalability: Inefficient resource strategies restricted growth.
Impact
- Achieved a ~12% reduction in workforce spend within three months in a pilot region.
- Reallocated contractual budgets to support in-house labor, resulting in a ~5% increase in in-house hires.
- Enabled 12 critical decisions across staffing, hiring, and project pipeline adjustments through near real-time insights and automated reporting.
- Identified and addressed over 60,000 under-utilized man-hours and 5,000 over-utilized hours, enabling proactive workforce planning and allocation.
- Established a continuous feedback loop to detect and resolve data discrepancies, ensuring a single source of truth across systems and consistent, reliable planning inputs.
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