How do you present confidence levels to clients? I've got a Duke Energy audit with $32K in savings but some are slam-dunks (tariff error) and others are estimates based on load profiling. Do you assign percentages or just use qualitative terms like 'high confidence' vs 'estimated'?
Quantifying Confidence Levels in Savings Estimates
Todd, I use a three-tier system: Guaranteed (billing errors, tariff changes), High Confidence (>90%, based on solid data), and Estimated (70-90%, requires assumptions). Clients appreciate the honesty and it protects you if some estimates don't pan out exactly.
I like Randy's range approach. For load profile estimates, I show them the underlying assumptions - 'based on 12 months of demand data, assuming similar patterns continue.' Makes the uncertainty transparent rather than hidden. Better to underpromise and overdeliver.
Ruben's sensitivity analysis idea is excellent for larger savings estimates. One thing I've learned is to separate implementation-dependent savings from automatic ones. A tariff change happens regardless, but demand reduction requires behavior change. Different confidence levels for different types of recommendations.
Rosa, showing assumptions is key. I've started including sensitivity analysis for major estimates - 'if usage increases 10%, savings drop to $X; if it decreases 10%, savings rise to $Y.' Helps clients understand what could affect the outcomes.
Ed's approach is solid. I also include range estimates for the uncertain items - 'operational changes could save $8-12K annually based on similar facilities.' Gives them realistic expectations rather than false precision. Conservative estimates that you can exceed are better than optimistic ones you miss.