Lyzr’s FPLS turns agent impact into a clear cause→effect chain: make work Faster (F), which raises Productivity (P), enabling Labor reduction/avoidance/redeployment (L), and producing measurable Savings (S). For CFO-grade rigor, we also track Revenue uplift and Risk avoidance, then risk-adjust benefits and net out TCO.
The FPLS formula
Defaults: 10 analysts, 160 hrs/person/month, $120/hr fully loaded.
1. Basic research (company/sector scans, site+LinkedIn scraping, synthesis)
2. Evaluation & scoring (15–100 weighted criteria, roll-ups)
3. Brainstorming & scenarios (comparisons, what-ifs, decision narrows)
4. Ad hoc (NDA execution workflow, investment-memo drafting)
Totals (labor value only): 893 hours/month saved ≈ 5.6 FTE-months, worth $107,200/month (≈ $1.29M/year).
• Add modest risk avoidance: $60k/year (fewer mistakes/chargebacks/compliance slips).
• No revenue uplift or non-labor OPEX savings credited yet (kept conservative).
• Apply 75% pilot confidence and 10% flexibility option value; net $300k/year TCO; $150k one-time setup.
Risk-adjusted ROI ≈ 5.6× Payback ≈ 1.6 months Risk-adjusted benefit ≈ $95k/month
How to adapt this in your calculations
1. Swap assumptions: hours/person, loaded rate, team size, and any external OPEX.
2. Replace tasks: keep the six columns (F, P, L, S, Revenue, Risk); use “—” where N/A.
3. Monetize L: \text{Hours saved} \times \text{loaded rate}. Split into reduction, avoidance, redeployment if you track them.
4. Add S / R_rev / R_risk: quantify OPEX cuts, pipeline/conversion lifts, and avoided losses.
5. Risk-adjust & report: set p, include Flexibility, subtract TCO, then show ROI, payback, time-to-value.
*Pair this with a 2–4 week pilot (control vs. treatment) so your F and P deltas are measurement-grade, not assumptions.