35% improvement in forecasting accuracy
PREDICTABLE O&M SPENDING • TIMELY COMPLETION OF COMPLIANCE WORK • OPTIMIZED O&M/CAPITAL ALLOCATION
The first step to adopting AI and machine learning for forecasting is to understand the appropriate methods and analytical considerations. Without this groundwork, there is a risk of teaching incorrect logic to the AI models, potentially leading to significant correction costs.
Our approach
1 Conducted end-to-end process evaluation and analysis
2 Integrated best practices tailored to the client’s capabilities and objectives
3 Implemented improved practices ahead of AI/ML for testing and immediate cash flow
4 AI/ML training completed using established, reliable methods to prevent costly errors and rework
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End-to-end process evaluation and analysis
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Integrated best practices
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Early adoption for immediate cash flow
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AI/ML training with reliable methods
Our results
Timeliness
forecasts completed two months earlier than historical timelines
Work and financial forecasts were completed two months ahead of historical timelines, allowing more time for financial planning and adjustments, enhancing strategic decision-making capabilities.
Accuracy
improvements in job duration and cost estimates
Enhanced precision in financial forecasting, resulting in better management of O&M and capital budgets, and more accurate Net Operating Earnings projections.
Efficiency
leading to higher productivity and lowered O&M costs
Improved job duration accuracy and schedule optimization, leading to reduced overtime and efficient resource utilization, and freed resources to apply to capital work.
E. C., Director, Work Planning and Forecasting
“Tremendous appreciation for you scripting this out for me. Really appreciate your expertise as always to lean in and support as needed.”
