Benefits ROI Calculator for New York Cleaning Services Companies

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📊 Powered by Industry Data

{[ {icon:'💰', name:'KFF 2024', detail:'Employer Health Benefits Survey', desc:'The gold standard for U.S. employer health costs. Covers premiums, contributions, deductibles, and plan design across 2,000+ firms — the basis for our medical, dental, and vision cost estimates.'}, {icon:'👥', name:'SHRM & BLS', detail:'Workforce & Industry Benchmarks', desc:'SHRM\'s Human Capital Benchmarking and BLS JOLTS data provide turnover rates, hiring costs, and benefits adoption rates across 16 industries used in our ROI projections.'}, {icon:'⚖️', name:'EEOC & DOL', detail:'Compliance & Regulatory Data', desc:'Equal Employment Opportunity Commission and Department of Labor data on workplace claims, compliance costs, and employer liability — used to estimate risk-reduction value of PEO partnerships.'}, {icon:'📈', name:'MetLife & WTW', detail:'Employee Satisfaction Research', desc:'MetLife\'s Annual Benefits Trends Study and Willis Towers Watson\'s Global Benefits Attitudes Survey quantify how specific benefits drive employee satisfaction, engagement, and retention.'}, {icon:'🏢', name:'Work Institute', detail:'Retention & Turnover Research', desc:'Their annual Retention Report analyzes 250,000+ exit interviews to identify why employees leave and quantify the cost — our replacement cost and turnover reduction estimates are anchored here.'}, {icon:'🔒', name:'Hiscox', detail:'Employment Practices Liability', desc:'Hiscox\'s annual EPL study tracks the frequency and cost of employee lawsuits. Used to model liability-reduction savings when employers adopt compliant benefits through a PEO.'} ].map((s,i)=>(

{s.icon}

{s.name}

{s.detail}

{s.desc}

))}

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How It Works— Every number has a source. Hover any icon to see the calculation, data source, and assumptions behind each figure.

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{/* S1: Company Profile */}

uCp('name',v)} placeholder="Acme Corp"/>

Industry

Other Services / Cleaning Services

State

New York

uCp('range',v)} options={empRanges.map(r=>({v:r,l:r+' employees'}))}/> uCp('exact',v)} placeholder="e.g. 47" optional type="number"/>

{s1Ok&&

Complete — continue below

} {/* S2: Benefits Selection */}

Satisfaction Benchmarks: Health Only: 40-55% | +Dental+Vision: 50-65% | +Core 7: 60-75% | 30+ Benefits: 75-90%

2a. Select Your Current Benefits

{Object.entries(benefitsCatalog).map(([k,cat])=>{ const c=catClr[cat.color]; return

{cat.title}

{cat.items.map(b=>toggleCurrent(b.id)}/>)}

; })} {currentBenIds.length > 0 && <>

Current Employee Benefit Satisfaction Score

{currentSat}%

2b. Select Benefits to Add for Your Ideal Package

Check a benefit to add it. For some benefits, you can customize how it's funded or how much to invest.

{Object.entries(benefitsCatalog).map(([k,cat])=>{ const c=catClr[cat.color]; const available = cat.items.filter(b=>!currentBens[b.id]); if (available.length === 0) return null; return

{cat.title}

{available.map(b=>{ const cust = customizableBenefits[b.id]; const chk = idealBens[b.id]; const cfg = benConfig[b.id] || {}; const badgeText = chk && cust ? (cust.fundingModes ? (cust.labels[cfg.mode||cust.defaultMode]||'') : cust.amountInput ? fmt(parseFloat(cfg.amount)||cust.defaultAmount)+'/emp' : null) : null; return

toggleIdeal(b.id)} highlight={b.peo} value={badgeText}/> {chk && cust && cust.fundingModes &&

How will you offer {b.n}?

{Object.entries(cust.labels).map(([mode,lbl])=>{ const active = (cfg.mode||cust.defaultMode)===mode; const clr = mode==='voluntary'?'border-green-400 bg-green-50 text-green-700':mode==='split'?'border-amber-400 bg-amber-50 text-amber-700':'border-red-400 bg-red-50 text-red-700'; return ; })}

{(()=>{const m=cfg.mode||cust.defaultMode;const cs=cust.costs[m];return cs?(cs.mid>0?

90% confidence: ${cs.low}–${cs.high}/emp/yr (mid: ${cs.mid})

$0 employer cost — employee-paid via payroll deduction

):null;})()}

} {chk && cust && cust.amountInput &&

{cust.label}

$ {e.stopPropagation();uBen(b.id,'amount',e.target.value);}} className="flex-1 h-2 bg-gray-200 rounded-lg appearance-none cursor-pointer accent-bih-green"/> {e.stopPropagation();uBen(b.id,'amount',e.target.value);}} onClick={e=>e.stopPropagation()} onWheel={e=>e.target.blur()} className="w-24 px-2 py-1 border border-gray-300 rounded text-sm text-right"/> /yr

{cust.hint}

Total: {fmt((parseFloat(cfg.amount)||cust.defaultAmount)*empN)}/yr for {empN} employees

}

; })}

Ideal Package Employee Benefit Satisfaction

{idealSat}%

{idealBenIds.length} benefits total ({newBenIds.length} new)

{newBenIds.length > 0 && (

{/* Contribution Type Legend */}

Understanding Employer Cost Types:

Noncontributory — Employer pays 100%. All eligible employees enrolled automatically.

Contributory — Employer & employee share cost. Carriers often require 50%+ ER share, 75% participation.

Voluntary — Employee-paid. $0 employer cost possible. Employer provides access via payroll deduction.

Employer-Funded / Admin — Employer pays platform or program fee, or admin costs only.

{/* Important Notes */}

⚠️ Important Considerations:

Minimum participation: Most group benefit carriers require 75% employee participation for contributory plans (medical, dental). Voluntary lines typically need 10-25%.
Small group rules: Under 50 employees, ACA small group rules apply — community-rated premiums, essential health benefits required. Over 50, large group underwriting applies.
Employer contribution minimums: Most carriers require the employer to contribute at least 50% of employee-only premiums for group health. Some states require higher (e.g., Hawaii mandates 50%, some carriers require 75%).
Enrollment windows: Adding new benefits typically requires a qualifying event or annual open enrollment period.
Voluntary benefits at $0: Benefits marked "Voluntary" can genuinely cost the employer $0 — the employer simply provides access and payroll deduction. These still boost satisfaction and recruitment.

{idealBenefitsCostData.erPaidBenefits.length > 0 && (<>

Estimated Annual Employer Cost for New Benefits:

90% Confidence Interval (Employer Cost Only)

{fmt(idealBenefitsCostData.totalLow)} — {fmt(idealBenefitsCostData.totalMid)} — {fmt(idealBenefitsCostData.totalHigh)}

)} {/* All new benefits — ER-paid and voluntary together */} {idealBenefitsCostData.breakdown.length > 0 && (

{idealBenefitsCostData.breakdown.map(b => { const isVol = !b.hasERCost; const typeColor = isVol ? 'bg-green-100 text-green-700' : b.type === 'noncontributory' ? 'bg-red-100 text-red-700' : b.type === 'contributory' ? 'bg-amber-100 text-amber-700' : 'bg-blue-100 text-blue-700'; const typeLabel = isVol ? 'Employee-Paid' : b.type === 'noncontributory' ? 'ER-Paid' : b.type === 'contributory' ? 'Contributory' : b.type === 'admin-only' ? 'Admin Fee' : 'ER-Funded'; const textColor = isVol ? 'text-green-600' : 'text-blue-600'; return (

{typeLabel} {b.name} ${b.name}

Type: ${isVol ? 'Voluntary (employee-paid)' : b.type}
Employer cost: ${isVol ? '$0 — employee pays via payroll deduction' : '$'+b.costLow+'-$'+b.costHigh+'/emp/yr'}
Employer share: ${b.erShareRange}
Min participation: ${b.minParticipation}

Source: ${b.source}`}/> {isVol ? '$0/emp' : '$'+b.costLow+'-$'+b.costHigh+'/emp'}

); })}

)} {idealBenefitsCostData.voluntaryBenefits.length > 0 && (

{idealBenefitsCostData.voluntaryBenefits.length} benefit(s) marked Employee-Paid add value to your package at no direct employer cost — employees get group pricing via payroll deduction.

)}

2c. PEO Benefits Available

{allBens.filter(b=>b.peo).map(b=>

{b.n}

)}

Full PEO Employee Benefits Satisfaction

{peoSat}%

} {/* S3: Turnover & Value Drivers */}

Industry ({cp.industry || 'default'}): {ind.turnover}% avg turnover, {fmt(ind.avgSalary)} avg salary

uTd('salTyp',v)} prefix="$" placeholder={String(ind.avgSalary)} optional type="number"/> uTd('replCostTyp',v)} suffix="%" placeholder={String(ind.replacement)} optional type="number" tip={replacementTip}/>

Total Employee Turnover

uTd('totalLeaveCurrent',v)} suffix="emp" placeholder={String(defTotalLeave)} optional type="number" tip={`Industry average: ${ind.turnover}% = ${defTotalLeave} employees/year`}/> uTd('totalLeaveIdeal',v)} suffix="emp" placeholder={String(Math.round(defTotalLeave * 0.85))} optional type="number" tip={turnoverPredTip('ideal')}/> uTd('totalLeavePeo',v)} suffix="emp" placeholder={String(Math.round(defTotalLeave * 0.75))} optional type="number" tip={turnoverPredTip('peo')}/>

High-Value Employee Analysis

uTd('hvSalary',v)} prefix="$" placeholder={String(Math.round(avgSal * 1.7))} optional type="number"/> uTd('replCostHV',v)} suffix="%" placeholder={String(ind.replacement * 2)} optional type="number" tip={replacementTip}/>

uTd('hvExtraRevenue',v)} prefix="$" suffix="/year extra" placeholder={String(Math.round(avgSal * 0.5))} optional type="number" tip={hvRevenueTip}/>

uTd('hvLeaveCurrent',v)} suffix="emp" placeholder={String(defHVLeave)} optional type="number"/> uTd('hvLeaveIdeal',v)} suffix="emp" placeholder={String(Math.round(defHVLeave * 0.7))} optional type="number"/> uTd('hvLeavePeo',v)} suffix="emp" placeholder={String(Math.round(defHVLeave * 0.6))} optional type="number"/>

uTd('hvPct',v)} suffix="%" placeholder="15" optional type="number"/> uTd('hvPctIdeal',v)} suffix="%" placeholder="20" optional type="number"/> uTd('hvPctPeo',v)} suffix="%" placeholder="25" optional type="number"/>

uTd('growthHires',v)} suffix="new positions" placeholder={String(Math.round(empN * 0.1))} optional type="number" tip="Net new positions (excluding turnover). Total hires = growth + turnover replacements."/>

Time-to-Hire

uTd('tthCurrent',v)} suffix="days" placeholder={String(defTTH)} optional type="number"/> uTd('tthIdeal',v)} suffix="days" placeholder={String(Math.round(defTTH * 0.85))} optional type="number"/> uTd('tthPeo',v)} suffix="days" placeholder={String(Math.round(defTTH * 0.75))} optional type="number"/>

Productivity & Engagement

Top productivity boosters: Financial Planning, Mental Health, Wellness, Caregiving, On-Demand Pay

uTd('prodCurrent',v)} min={0} max={100} showValue/> uTd('prodIdeal',v)} min={0} max={100} showValue color="accent-blue-500"/> uTd('prodPeo',v)} min={0} max={100} showValue/>

{/* Turnover Preview */}

Turnover Savings Preview

Your Ideal Benefits

{fmt(turnoverIdeal.total)}

{turnoverIdeal.fewerTotal} fewer employees leaving

Full PEO Benefits

{fmt(turnoverPeo.total)}

{turnoverPeo.fewerTotal} fewer employees leaving

{/* S4: PEO Value Analysis */}

Do you currently have a PEO?

{['yes','no'].map(v=>)}

{pe.hasPeo==='yes'&&(

uPe('peoName',v)} placeholder="e.g. ADP TotalSource" optional/> uPe('peoCost',v)} prefix="$" placeholder="5000" optional type="number"/>

)} {pe.hasPeo==='no'&&(

Current Payroll & HR Tool Costs

A PEO replaces these tools entirely. Enter your current costs so we can calculate your true net investment. Values are pre-filled with industry benchmarks for {empN} employees.

uPe('payrollCost',v)} prefix="$" placeholder={String(hrToolBenchmarks.payroll.cost(empN) * empN)} tip="Total monthly bill from your payroll provider (ADP, Paychex, Gusto, etc.). Not employee wages — just the service fee." optional type="number"/> {!pe.payrollCost &&

Industry avg for {empN} employees: ~{fmt(hrToolBenchmarks.payroll.cost(empN) * empN)}/mo (${hrToolBenchmarks.payroll.cost(empN)}/emp/mo)

}

HR Tools & Services (check all that apply):

{Object.entries(hrToolBenchmarks).filter(([id])=>id!=='payroll').map(([id,tool])=>{ const on = pe.hrTools[id]; const benchMo = tool.cost(empN); const ovr = pe.hrToolOverrides[id]; const effMo = ovr !== undefined && ovr !== '' ? parseFloat(ovr) : benchMo; const annTotal = effMo * empN * 12; return

toggleTool(id)} className="flex items-center gap-2 cursor-pointer flex-1">

{on&&}

{tool.label} {tool.hint}

{on && {fmt(annTotal)}/yr}

{on &&

$/emp/mo: {e.stopPropagation();uToolOvr(id,e.target.value);}} onClick={e=>e.stopPropagation()} onWheel={e=>e.target.blur()} className="w-20 px-2 py-1 border border-gray-300 rounded text-xs text-right" min="0" step="1"/> {ovr !== undefined && ovr !== '' && parseFloat(ovr) !== benchMo && } = {fmt(effMo * empN)}/mo for {empN} emp

}

; })}

{replacedToolsCost > 0 &&

Total Current Tools Cost:{fmt(replacedToolsCost)}/year

This amount is replaced by your PEO and counted as savings in the analysis below.

}

)}

uPe('ft',v)} placeholder={String(empN)} optional type="number"/> uPe('pt',v)} placeholder="0" optional type="number"/>

Estimated PEO Cost:${tier.pepm.toFixed(2)}/emp/mo

Annual:{fmt(peoAnnual)}

{pe.hasPeo==='yes' && currentPeoCost > 0 &&

vs Current: peoAnnual ? 'text-bih-green' : 'text-red-600'}`}>{currentPeoCost > peoAnnual ? `Save ${fmt(currentPeoCost - peoAnnual)}/yr` : `${fmt(peoAnnual - currentPeoCost)}/yr more`}

} {pe.hasPeo==='no' && replacedToolsCost > 0 && <>

Current tools replaced:{fmt(replacedToolsCost)}/yr

Net new PEO cost:{peoAnnual - replacedToolsCost <= 0 ? `Save ${fmt(Math.abs(peoAnnual - replacedToolsCost))}/yr` : `${fmt(peoAnnual - replacedToolsCost)}/yr`}

}

HR Time Savings

With guaranteed compliance, expert access, and unified integrations:

uPe('hrHoursSaved',v)} suffix="hrs" placeholder={String(benchmarkHours)} optional type="number"/> uPe('hrHourlyRate',v)} prefix="$" placeholder={String(ind.hrHourlyRate)} optional type="number"/> uPe('hrOpportunityCost',v)} suffix="%" placeholder="40" optional type="number"/>

Total HR Time Value: {fmt(hrTimeSavings)}/year

HR Challenges

Suggested values are based on your industry and headcount. You can adjust any value after selecting it.

{hrChallenges.map(c=>{ const sug=getHRVal(c.id); const on=pe.hrCh.includes(c.id); const ov=pe.hrChOvr[c.id]; const eff=ov!==undefined&&ov!==''?parseFloat(ov):sug; return

toggleArr('hrCh',c.id)} value={fmt(eff)} tip={getHRTip(c.id)}/> {on &&

Annual value: $ uHrOvr(c.id,e.target.value)} onWheel={e=>e.target.blur()} className="w-28 px-2 py-1 border border-gray-300 rounded text-xs text-right" min="0" step="500"/> {ov!==undefined&&ov!==''&&parseFloat(ov)!==sug && }

}

; })}

{hrChValue > 0 &&

Total: {fmt(hrChValue)}/year

}

Compliance Concerns

Values are expected annual risk cost (probability × typical claim cost). Adjust as needed.

{complianceItems.map(c=>{ const sug=getCompVal(c.id); const on=pe.comp.includes(c.id); const ov=pe.compOvr[c.id]; const eff=ov!==undefined&&ov!==''?parseFloat(ov):sug; return

toggleArr('comp',c.id)} value={eff>0?fmt(eff):'N/A'} tip={getCompTip(c.id)}/> {on && sug>0 &&

Annual risk value: $ uCompOvr(c.id,e.target.value)} onWheel={e=>e.target.blur()} className="w-28 px-2 py-1 border border-gray-300 rounded text-xs text-right" min="0" step="500"/> {ov!==undefined&&ov!==''&&parseFloat(ov)!==sug && }

}

; })}

{compValue > 0 &&

Total: {fmt(compValue)}/year

}

Workers' Compensation

PEO savings: {isBlue ? '20-60%' : '0-30%'} ({isBlue ? 'blue' : 'white'}-collar)

uPe('wcPremium',v)} prefix="$" placeholder="25000" optional type="number"/> uPe('wcSavingsEst',v)} suffix="%" placeholder={String(Math.round(wcSavPct))} optional type="number"/>

{wcSavings > 0 &&

{fmt(wcSavings)} savings

}

{/* S5: Value Breakdown */} {/* Scenario Tabs */}

Projection Scenario

{[{k:'conservative',l:'Conservative',sub:'70%'},{k:'base',l:'Base Case',sub:'100%'},{k:'optimistic',l:'Optimistic',sub:'130%'}].map(s=>( ))}

{op.scenario === 'conservative' ? 'Showing 70% of projected improvements — your floor estimate' : op.scenario === 'optimistic' ? 'Showing 130% of projected improvements — with strong execution' : 'Showing base case — projected improvements from industry research'}

{/* Industry Benchmark */} {(() => { const ct = ind.compThreshold; // Map satisfaction to industry-relative percentile: compThreshold = 50th percentile const toPos = (sat) => { if (sat <= 35) return 5; if (sat < ct) return 5 + (sat - 35) / (ct - 35) * 45; // 35→5%, ct→50% return 50 + (sat - ct) / (95 - ct) * 45; // ct→50%, 95→95% }; const curPos = Math.min(95, Math.max(5, toPos(currentSat))); const idealPos = Math.min(95, Math.max(5, toPos(idealSat))); const peoPos = Math.min(95, Math.max(5, toPos(peoSat))); const curLabel = curPos < 25 ? 'Below Average' : curPos < 50 ? 'Approaching Average' : curPos < 75 ? 'Competitive' : 'Top Tier'; return (

📊 Benefits Competitiveness: {cp.industry || 'Your Industry'} INDUSTRY-SPECIFIC COMPETITIVENESS

This bar reflects what it takes to be competitive in ${cp.industry || 'your industry'} specifically — not a one-size-fits-all score.

How it works:
Different industries have different benefits expectations. In ${cp.industry || 'your industry'}, a satisfaction score of ~${ct}% represents the competitive midpoint where most employers sit.

${cp.industry || 'Your industry'} insight:
${ind.compNote}

What the positions mean:
• Left (red): Well below ${cp.industry || 'industry'} norms — high turnover risk
• Center line: Average for ${cp.industry || 'your industry'} (~${ct}% satisfaction)
• Right (green): Above ${cp.industry || 'industry'} peers — strong recruitment advantage

Your scores:
• Current: ${currentSat}% — ${curLabel}
• Ideal: ${idealSat}%
• PEO: ${peoSat}%

Sources: MetLife, SHRM, Willis Towers Watson industry benchmarks`}/>

{/* Industry average marker */}

{/* Current marker */}

{/* Ideal marker */}

{/* PEO marker */}

Below AverageIndustry Avg ({ct}%)Top Tier

Current: {currentSat}% — {curLabel} Ideal: {idealSat}% PEO: {peoSat}%

{ind.compNote}

); })()} {(() => { const sMult = op.scenario === 'conservative' ? 0.7 : op.scenario === 'optimistic' ? 1.3 : 1.0; const sLabel = op.scenario === 'conservative' ? 'Conservative' : op.scenario === 'optimistic' ? 'Optimistic' : 'Base Case'; // Scenario-adjusted values const sTurnoverIdeal = Math.round(turnoverIdeal.total * sMult); const sTurnoverPeo = Math.round(turnoverPeo.total * sMult); const sAttractionIdeal = Math.round(attractionIdeal.value * sMult); const sAttractionPeo = Math.round(attractionPeo.value * sMult); const sTthIdeal = Math.round(tthCalcIdeal.total * sMult); const sTthPeo = Math.round(tthCalcPeo.total * sMult); const sProdIdeal = Math.round(prodValueIdeal * sMult); const sProdPeo = Math.round(prodValuePeo * sMult); const sHrTime = Math.round(hrTimeSavings * sMult); const sHrCh = Math.round(hrChValue * sMult); const sComp = Math.round(compValue * sMult); const sWc = Math.round(wcSavings * sMult); const sIdealGross = sTurnoverIdeal + sAttractionIdeal + sTthIdeal + sProdIdeal; const sIdealNet = sIdealGross - idealBenefitsCostData.totalMid; const sReplacedTools = replacedToolsCost; // not scenario-adjusted — real spend const sPeoGross = sTurnoverPeo + sAttractionPeo + sTthPeo + sProdPeo + sHrTime + sHrCh + sComp + sWc + sReplacedTools; const sPeoNet = sPeoGross - peoAnnual; const sPeoChangeAmount = currentPeoCost > 0 ? peoAnnual - currentPeoCost : peoAnnual; const sPeoNetAdjusted = currentPeoCost > 0 ? sPeoGross - sPeoChangeAmount : sPeoNet; const sPeoROI = peoAnnual > 0 ? Math.round((sPeoGross / peoAnnual) * 100) : 0; const sIdealROI = idealBenefitsCostData.totalMid > 0 ? Math.round((sIdealGross / idealBenefitsCostData.totalMid) * 100) : 0; return (<>

{/* Ideal Benefits Column */}

Your Ideal Benefits

{sTurnoverIdeal > 0 && {turnoverIdeal.fewerTotal} fewer leaving} tip={turnoverPreviewTip(true)}/>} {sAttractionIdeal > 0 && {attractionIdeal.extraHV} extra high-value hires} tip={attractionTip(true)}/>} {sTthIdeal > 0 && {tthCalcIdeal.daysSaved} days saved × {totalHires} hires} tip={tthTip(true)}/>} {sProdIdeal > 0 && {prodC}% → {prodIdeal}%} tip={prodTip(true)}/>}

Gross Value ({sLabel}):{fmt(sIdealGross)}

{idealBenefitsCostData.totalMid > 0 && (

Benefits Investment90% CONFIDENCE INTERVAL

Low: ${fmt(idealBenefitsCostData.totalLow)}/yr
Mid: ${fmt(idealBenefitsCostData.totalMid)}/yr
High: ${fmt(idealBenefitsCostData.totalHigh)}/yr`}/> ({fmt(idealBenefitsCostData.totalLow)} - {fmt(idealBenefitsCostData.totalHigh)})

)}

Net Value {fmt(sIdealNet)}/yr

{idealBenefitsCostData.totalMid > 0 &&

ROI: {sIdealROI}%

}

{/* PEO Column */}

Full PEO Benefits

{sTurnoverPeo > 0 && {turnoverPeo.fewerTotal} fewer leaving} tip={turnoverPreviewTip(false)}/>} {sAttractionPeo > 0 && {attractionPeo.extraHV} extra high-value hires} tip={attractionTip(false)}/>} {sTthPeo > 0 && {tthCalcPeo.daysSaved} days saved × {totalHires} hires} tip={tthTip(false)}/>} {sProdPeo > 0 && {prodC}% → {prodPeo}%} tip={prodTip(false)}/>} {sHrTime > 0 && {hoursSaved} hrs/week freed} tip={hrTimeSavingsTip}/>} {sHrCh > 0 && {pe.hrCh.length} challenges addressed}/>} {sComp > 0 && {pe.comp.length} risks mitigated}/>} {sWc > 0 && {wcSavPct}% savings}/>} {replacedToolsCost > 0 && Payroll + {Object.keys(pe.hrTools).filter(k=>pe.hrTools[k]).length} HR tools replaced} tip={`TOOLS REPLACED BY PEO

A PEO bundles payroll, HRIS, benefits admin, compliance, and more into one platform.

Your current costs being replaced:
${payrollAnnual > 0 ? '\u2022 Payroll: ' + fmt(payrollAnnual) + '/yr
' : ''}${Object.keys(pe.hrTools).filter(k=>pe.hrTools[k]).map(id => {const b=hrToolBenchmarks[id];const ovr=pe.hrToolOverrides[id];const mo=ovr!==undefined&&ovr!==''?parseFloat(ovr):b.cost(empN);return '\u2022 '+b.label+': '+fmt(mo*empN*12)+'/yr';}).join('
')}

Total replaced: ${fmt(replacedToolsCost)}/yr

This is real budget you're already spending that the PEO absorbs.`}/>}

Gross Value ({sLabel}):{fmt(sPeoGross)}

{currentPeoCost > 0 && (

PEO Change: {sPeoChangeAmount < 0 ? `+${fmt(Math.abs(sPeoChangeAmount))} savings` : `(${fmt(sPeoChangeAmount)})`}

)} {!(currentPeoCost > 0) && (

PEO Investment:({fmt(peoAnnual)})

)} {!(currentPeoCost > 0) && sReplacedTools > 0 && (

Tools Replaced:+{fmt(sReplacedTools)}

)}

Net Value {fmt(sPeoNetAdjusted)}/yr

ROI: {sPeoROI}%

{pe.hasPeo === 'yes' && currentPeoCost > 0 && (

Switching Analysis

Your current PEO cost:{fmt(currentPeoCost)}/yr

Recommended PEO cost:{fmt(peoAnnual)}/yr

PEO cost difference:{sPeoChangeAmount < 0 ? `Save ${fmt(Math.abs(sPeoChangeAmount))}` : fmt(sPeoChangeAmount)}/yr

{sWc > 0 &&

Workers' comp savings:+{fmt(sWc)}/yr

}

0 ? 'text-bih-green' : 'text-amber-300'}`}> Total switching {switchingSavings > 0 ? 'saves' : 'costs'}: {fmt(Math.abs(switchingSavings))}/yr

)}

{/* Multi-Year Projection Inputs */}

Multi-Year Projection Settings

uTd('illustrateYears',v)} options={[{v:'1',l:'1 Year'},{v:'2',l:'2 Years'},{v:'3',l:'3 Years'},{v:'4',l:'4 Years'},{v:'5',l:'5 Years'},{v:'6',l:'6 Years'}]} tip="Select the number of years for your value projection (max 6 years)."/>

Expected New Employees Per Year

{Array.from({length: parseInt(td.illustrateYears||'3')}, (_,i)=> { const yr = i+1; const gby = td.growthByYear || {}; return

Year {yr}

{const v=e.target.value;setTd(p=>({...p,growthByYear:{...p.growthByYear,[yr]:v}}));}} onWheel={e=>e.target.blur()} placeholder={String(growthHires)} className="w-full px-3 py-2 border border-gray-300 rounded-bih focus:ring-2 focus:ring-bih-green font-body text-bih-charcoal text-sm pr-10"/> emp

; })}

{/* Side by Side Time Values */} {(() => { const illustrateYears = parseInt(td.illustrateYears) || 3; const gby = td.growthByYear || {}; const getYearGrowth = (yr) => { const v = gby[yr]; return (v !== '' && v !== undefined && v !== null && !isNaN(parseFloat(v))) ? parseFloat(v) : growthHires; }; // Base annual values WITHOUT HV attraction (attraction will be recalculated per year) const baseIdealNetNoAttraction = sIdealNet - sAttractionIdeal; const basePeoNetNoAttraction = sPeoNetAdjusted - sAttractionPeo; // Build year-by-year projection const yearRows = []; let cumulativeIdeal = 0; let cumulativePeo = 0; let cumulativeHVIdeal = 0; let cumulativeHVPeo = 0; let cumulativeNewEmps = 0; for (let y = 1; y <= illustrateYears; y++) { const growthThisYear = getYearGrowth(y); cumulativeNewEmps += (y > 1 ? getYearGrowth(y - 1) : 0); const empY = empN + cumulativeNewEmps; const empRatio = empN > 0 ? empY / empN : 1; // Recalculate hires for this year's employee count const turnoverHiresY = Math.round(empY * ind.turnover / 100); const growthHiresY = growthThisYear; const totalHiresY = turnoverHiresY + growthHiresY; // Calculate new extra HV employees attracted this year const currentHVY = Math.round(totalHiresY * hvPctC / 100); const targetHVIdealY = Math.round(totalHiresY * hvPctIdeal / 100); const targetHVPeoY = Math.round(totalHiresY * hvPctPeo / 100); const extraHVIdealY = targetHVIdealY - currentHVY; const extraHVPeoY = targetHVPeoY - currentHVY; // Accumulate HV employees (they persist and generate value each year) cumulativeHVIdeal += Math.max(0, extraHVIdealY); cumulativeHVPeo += Math.max(0, extraHVPeoY); // This year's value: scaled base + cumulative HV attraction value const yearIdealValue = baseIdealNetNoAttraction * empRatio + cumulativeHVIdeal * hvExtraRevenue * sMult; const yearPeoValue = basePeoNetNoAttraction * empRatio + cumulativeHVPeo * hvExtraRevenue * sMult; cumulativeIdeal += yearIdealValue; cumulativePeo += yearPeoValue; yearRows.push({ year: y, empCount: Math.round(empY), newHVIdeal: Math.max(0, extraHVIdealY), newHVPeo: Math.max(0, extraHVPeoY), cumHVIdeal: cumulativeHVIdeal, cumHVPeo: cumulativeHVPeo, annualIdeal: Math.round(yearIdealValue), annualPeo: Math.round(yearPeoValue), cumulativeIdeal: Math.round(cumulativeIdeal), cumulativePeo: Math.round(cumulativePeo) }); } return (

Value Comparison Over Time

{sLabel} scenario ({sMult === 1 ? '100%' : sMult === 0.7 ? '70%' : '130%'} of projected improvements) • {Array.from({length:illustrateYears},(_,i)=>getYearGrowth(i+1)).join('/')} employees added (by year)

{yearRows.map((r, i) => ( ))}

Period	Your Ideal Benefits	Full PEO Benefits
Monthly	{fmt(Math.round(sIdealNet / 12))}	{fmt(Math.round(sPeoNetAdjusted / 12))}
{r.year}-Year Total {r.empCount} employees • {r.cumHVIdeal > 0 \|\| r.cumHVPeo > 0 ? `+${r.cumHVIdeal}/${r.cumHVPeo} HV` : ''}	{fmt(r.cumulativeIdeal)}	{fmt(r.cumulativePeo)}

{cumulativeHVIdeal > 0 || cumulativeHVPeo > 0 ? (

High-Value Employee Compounding Effect

Over {illustrateYears} year{illustrateYears > 1 ? 's' : ''}, your improved benefits attract {yearRows[yearRows.length-1].cumHVIdeal} additional high-value employees (Ideal) / {yearRows[yearRows.length-1].cumHVPeo} (PEO) who each generate {fmt(hvExtraRevenue)}/yr in extra revenue. Earlier hires compound value across all subsequent years.

) : null}

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🗺️ Cleaning Services Benefits ROI by State

See how cleaning services benefits ROI compares in other states:

MA Massachusetts Cleaning Services TX Texas Cleaning Services CA California Cleaning Services FL Florida Cleaning Services IL Illinois Cleaning Services PA Pennsylvania Cleaning Services NJ New Jersey Cleaning Services GA Georgia Cleaning Services OH Ohio Cleaning Services

← Back to National Cleaning Services Benefits ROI Calculator

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Use our other free tools to refine your analysis and find additional savings:

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❓

Frequently Asked Questions: New York Cleaning Services Benefits

What is the average wage for cleaning service workers in New York?

According to BLS data, the average annual wage for janitors and cleaners in New York is approximately $37,850 ($18.20/hour). In NYC, commercial cleaning wages reach $40,000-$48,000 for experienced workers, especially in union-represented buildings. Upstate wages average $32,000-$35,000, closer to the national median.

What are the workers' compensation rates for cleaning companies in New York?

New York cleaning service workers' comp rates range from $4.00 to $9.50 per $100 of payroll, with a typical rate of approximately $6.20 per $100. New York's WC system is among the most expensive in the nation, and cleaning companies must also carry Disability Benefits Law (DBL) coverage as a separate mandatory policy.

How does SEIU 32BJ affect non-union cleaning companies in New York?

SEIU 32BJ represents tens of thousands of building service workers in NYC and sets de facto wage and benefit standards. Union commercial cleaners earn $20-$25/hour with full health benefits. Even non-union cleaning companies must approach these levels to attract and retain workers in the NYC metro area, making competitive benefits packages a business necessity rather than an optional perk.

What is the turnover rate for cleaning companies in New York?

National cleaning industry turnover runs approximately 28.7% (BLS JOLTS 2024 for Other Services). In New York, high cost of living and abundant alternative employment options push effective turnover to an estimated 34% for non-union cleaning companies. Union shops with 32BJ contracts see significantly lower turnover due to comprehensive benefits, reinforcing the value of benefits investment.

How much do New York cleaning companies spend on health insurance?

The average employer share of single-coverage health insurance in New York is $9,245 per year (KFF 2024), among the highest in the nation. New York's community rating laws prevent carriers from varying premiums by health status, which benefits cleaning workforces with diverse health profiles. The NY State of Health marketplace offers small group options for employers with 1-100 employees.

What New York-specific benefits rules affect cleaning service employers?

Key NY rules include: (1) Mandatory Disability Benefits Law coverage for all employees, (2) Paid Family Leave at 67% of average weekly wage for up to 12 weeks, (3) NYC paid safe and sick leave of 40-56 hours depending on employer size, (4) Written wage notice requirements in employee's primary language, and (5) Active worker misclassification enforcement targeting cleaning contractors. NYC cleaning companies face the most layered compliance requirements in the country.

)} {/* Methodology & Sources (collapsible) */} {s2Ok && (

{op.methodology && (

Data Sources

Benefits Costs: KFF Employer Health Benefits Survey 2024, NADP Dental Benefits Report, VSP/EyeMed Vision Benchmarks. Turnover & Retention: SHRM Human Capital Benchmarking Report, Work Institute Retention Report, BLS Job Openings and Labor Turnover Survey (JOLTS). Compliance & Risk: Hiscox EPL Study, EEOC Charge Statistics, DOL Wage & Hour Division enforcement data, ICE Worksite Enforcement, OSHA penalty adjustments. Satisfaction & Engagement: MetLife Annual Employee Benefits Study, Willis Towers Watson Benefits Research, Gallup Employee Engagement Survey. PEO Data: NAPEO Industry Statistics, Pepperdine Private Capital Markets Project.

Key Assumptions

Turnover reduction from improved benefits: 10-25% (ideal), 20-30% (PEO), based on SHRM and Work Institute research. Satisfaction scoring follows MetLife/Willis Towers Watson tiered benchmarks (health only → core 7 → comprehensive). Replacement cost percentages sourced from SHRM, Center for American Progress, and Work Institute by role level. Benefit cost ranges represent 90% confidence intervals from cited industry surveys and do not reflect specific carrier quotes. All values are annualized estimates.

Important Limitations

This tool provides estimates based on industry benchmarks and published research. Actual costs and savings depend on plan design, carrier selection, geographic factors, workforce demographics, contribution strategy, participation rates, and regulatory requirements. Benefits cost ranges assume typical employer contribution levels; actual quotes will vary based on group size, claims history, and underwriting. Voluntary benefits show $0 employer cost but may have implicit costs (admin time, enrollment support). Small groups (under 50) are subject to ACA small group market rules; large groups (50+) have different underwriting and compliance obligations. This calculator is educational — consult with a licensed benefits advisor for plan-specific projections and carrier quotes.

Participation & Contribution Rules

Group health coverage: Most carriers require 75% eligible employee participation and 50%+ employer contribution for employee-only coverage. Some states have higher minimums (e.g., Hawaii 50% mandate, some carriers require 75% contribution). Voluntary lines: Typically 10-25% participation minimums, no employer contribution required. Under 2 enrolled: Many carriers will not issue group coverage with fewer than 2 enrolled employees. Section 125 / Cafeteria Plan: Pre-tax employee contributions require a Section 125 plan document — PEOs typically include this.

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BENEFITRA

Estimates based on industry data from KFF, SHRM, BLS, MetLife, Willis Towers Watson, Work Institute, and EEOC.

Consult with a licensed benefits advisor for plan-specific projections.

Benefits ROI Calculator for New York Cleaning Services Companies

New York Cleaning Services Industry at a Glance

What Makes New York Cleaning Services Different

New York-Specific Rules for Cleaning Services Employers

📊 Powered by Industry Data

2a. Select Your Current Benefits

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2b. Select Benefits to Add for Your Ideal Package

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2c. PEO Benefits Available

Total Employee Turnover

High-Value Employee Analysis

Time-to-Hire

Productivity & Engagement

Turnover Savings Preview

Do you currently have a PEO?

Current Payroll & HR Tool Costs

HR Time Savings

HR Challenges

Compliance Concerns

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Your Ideal Benefits

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Multi-Year Projection Settings

Value Comparison Over Time

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🗺️ Cleaning Services Benefits ROI by State

💡 Go Deeper With Your Numbers

Business Valuation Projection

Premium Renewal Stress Test

Health Funding Cost Projector

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Frequently Asked Questions: New York Cleaning Services Benefits

What is the average wage for cleaning service workers in New York?

What are the workers' compensation rates for cleaning companies in New York?

How does SEIU 32BJ affect non-union cleaning companies in New York?

What is the turnover rate for cleaning companies in New York?

How much do New York cleaning companies spend on health insurance?

What New York-specific benefits rules affect cleaning service employers?

Data Sources

Key Assumptions

Important Limitations

Participation & Contribution Rules