{"items":[{"name":"Win Rate","type":"Lagging","group":"function","category":"Sales KPIs","definition":"The share of qualified opportunities that close as won over a period.","formula":"(Deals won ÷ total qualified opportunities) × 100.","example":"45 won ÷ 180 qualified = 25%.","benchmark":"B2B win rates commonly run 15–30% of qualified opportunities; clearing ~30% consistently is strong","weakStrong":"\"We close a decent amount of our deals\" → \"Lift mid-market win rate from 25% to 32% by Q4, owned by the VP of Sales.\""},{"name":"Sales Cycle Length","type":"Lagging","group":"function","category":"Sales KPIs","definition":"The average elapsed time from opportunity creation to closed-won.","formula":"Total days to close across won deals ÷ number of won deals.","example":"5,400 days ÷ 90 deals = 60 days.","benchmark":"","weakStrong":""},{"name":"Quota Attainment","type":"Lagging","group":"function","category":"Sales KPIs","definition":"How much of an assigned sales target a rep or team has achieved.","formula":"(Actual bookings ÷ quota) × 100.","example":"$480,000 ÷ $600,000 = 80%.","benchmark":"","weakStrong":""},{"name":"Pipeline Coverage Ratio","type":"Leading","group":"function","category":"Sales KPIs","definition":"The amount of open pipeline relative to the revenue target for a period, signaling whether enough opportunities exist to hit goal.","formula":"Open pipeline value ÷ revenue target.","example":"$3,000,000 ÷ $1,000,000 = 3.0×.","benchmark":"","weakStrong":""},{"name":"Average Deal Size","type":"Lagging","group":"function","category":"Sales KPIs","definition":"The mean revenue value of a closed-won deal in a period.","formula":"Total closed-won revenue ÷ number of won deals.","example":"$900,000 ÷ 90 = $10,000.","benchmark":"","weakStrong":""},{"name":"Lead-to-Opportunity Conversion Rate","type":"Leading","group":"function","category":"Sales KPIs","definition":"The share of qualified leads that advance into sales opportunities.","formula":"(Opportunities created ÷ qualified leads) × 100.","example":"300 opportunities ÷ 1,200 leads = 25%.","benchmark":"","weakStrong":""},{"name":"Sales Velocity","type":"Leading","group":"function","category":"Sales KPIs","definition":"The rate at which revenue moves through the pipeline, combining opportunity volume, deal size, win rate, and cycle length.","formula":"(Number of opportunities × average deal size × win rate) ÷ sales cycle length in days.","example":"(200 × $10,000 × 0.25) ÷ 50 = $10,000/day.","benchmark":"","weakStrong":""},{"name":"Monthly Recurring Revenue (MRR)","type":"Lagging","group":"function","category":"Sales KPIs","definition":"The predictable subscription revenue normalized to a single month.","formula":"Sum of all active monthly subscription fees.","example":"500 customers × $200/month = $100,000 MRR.","benchmark":"","weakStrong":""},{"name":"Annual Recurring Revenue (ARR)","type":"Lagging","group":"function","category":"Sales KPIs","definition":"The predictable subscription revenue normalized to a full year.","formula":"MRR × 12.","example":"$100,000 MRR × 12 = $1,200,000 ARR.","benchmark":"","weakStrong":""},{"name":"Customer Acquisition Cost (CAC)","type":"Lagging","group":"function","category":"Sales KPIs","definition":"The fully loaded sales and marketing cost to acquire one new customer.","formula":"Total sales and marketing spend ÷ new customers acquired.","example":"$300,000 ÷ 100 = $3,000.","benchmark":"","weakStrong":""},{"name":"Customer Lifetime Value (LTV)","type":"Lagging","group":"function","category":"Sales KPIs","definition":"The total gross profit expected from a customer over the entire relationship.","formula":"Average revenue per account × gross margin × average customer lifespan.","example":"$6,000/year × 0.75 × 4 years = $18,000.","benchmark":"","weakStrong":""},{"name":"LTV:CAC Ratio","type":"Lagging","group":"function","category":"Sales KPIs","definition":"The ratio of customer lifetime value to the cost of acquiring that customer, measuring acquisition efficiency.","formula":"Customer lifetime value ÷ customer acquisition cost.","example":"$18,000 ÷ $3,000 = 6.0:1.","benchmark":"3:1 is the widely cited healthy target — below 1:1 you lose money on every customer, while above ~5:1 can mean you're under-investing in growth","weakStrong":"\"Our customers are worth more than they cost to win\" → \"Hold blended LTV:CAC at or above 3:1 while scaling spend 20%, reviewed monthly by RevOps.\""},{"name":"Net Revenue Retention (NRR)","type":"Lagging","group":"function","category":"Sales KPIs","definition":"The percentage of recurring revenue retained from existing customers including expansion, net of churn and contraction.","formula":"((Starting recurring revenue + expansion − contraction − churn) ÷ starting recurring revenue) × 100.","example":"(($1,000,000 + $150,000 − $50,000 − $100,000) ÷ $1,000,000) × 100 = 110%.","benchmark":"","weakStrong":""},{"name":"Upsell/Cross-sell Rate","type":"Lagging","group":"function","category":"Sales KPIs","definition":"The share of existing customers who purchase an upgrade or an additional product in a period.","formula":"(Customers with an upsell or cross-sell ÷ total existing customers) × 100.","example":"120 ÷ 1,000 = 12%.","benchmark":"","weakStrong":""},{"name":"New Logos Acquired","type":"Lagging","group":"function","category":"Sales KPIs","definition":"The count of brand-new customer accounts won in a period, excluding expansion of existing accounts.","formula":"Sum of net-new customer accounts closed in the period.","example":"28 net-new accounts in the quarter = 28 new logos.","benchmark":"","weakStrong":""},{"name":"Marketing Qualified Leads (MQLs)","type":"Leading","group":"function","category":"Marketing KPIs","definition":"The count of leads that meet the agreed marketing-qualification threshold and are passed toward sales.","formula":"Sum of leads reaching the defined MQL score or criteria in a period.","example":"600 leads crossed the MQL threshold last month = 600 MQLs.","benchmark":"","weakStrong":""},{"name":"Sales Qualified Leads (SQLs)","type":"Leading","group":"function","category":"Marketing KPIs","definition":"The count of MQLs that sales accepts as genuine opportunities worth active pursuit.","formula":"Sum of leads accepted by sales as qualified in a period.","example":"180 of the month's MQLs were accepted = 180 SQLs.","benchmark":"","weakStrong":""},{"name":"Cost Per Lead (CPL)","type":"Lagging","group":"function","category":"Marketing KPIs","definition":"The average marketing cost to generate a single lead.","formula":"Total campaign spend ÷ number of leads generated.","example":"$60,000 ÷ 1,200 = $50.","benchmark":"","weakStrong":""},{"name":"Lead Conversion Rate","type":"Lagging","group":"function","category":"Marketing KPIs","definition":"The share of leads that complete the desired next step, such as becoming an opportunity or a customer.","formula":"(Conversions ÷ total leads) × 100.","example":"120 conversions ÷ 1,200 leads = 10%.","benchmark":"this varies enormously by source — low single digits for cold traffic, double digits for high-intent demo requests — so judge it against your own baseline, not a universal number","weakStrong":"\"Our leads convert reasonably well\" → \"Raise demo-request lead conversion from 10% to 14% by improving form UX, owned by the demand-gen lead this quarter.\""},{"name":"Return on Marketing Investment (ROMI)","type":"Lagging","group":"function","category":"Marketing KPIs","definition":"The profit generated for every dollar invested in marketing, net of the marketing cost itself.","formula":"((Revenue attributed to marketing − marketing cost) ÷ marketing cost) × 100.","example":"(($500,000 − $100,000) ÷ $100,000) × 100 = 400%.","benchmark":"a 5:1 revenue-to-cost ratio (~400% ROMI) is a common 'good' bar; roughly 2:1 is break-even once gross margin is counted","weakStrong":"\"Marketing drives a lot of revenue\" → \"Deliver a 4:1 ROMI on the paid-search program in H2, reported monthly against attributed pipeline by the marketing ops manager.\""},{"name":"Return on Ad Spend (ROAS)","type":"Lagging","group":"function","category":"Marketing KPIs","definition":"The revenue generated for every dollar spent on advertising.","formula":"Revenue from ads ÷ ad spend.","example":"$250,000 ÷ $50,000 = 5.0× (or 500%).","benchmark":"","weakStrong":""},{"name":"Organic Traffic","type":"Leading","group":"function","category":"Marketing KPIs","definition":"The number of website visits arriving from unpaid search and other non-paid channels.","formula":"Sum of non-paid sessions to the site in a period.","example":"80,000 unpaid sessions last month = 80,000 organic visits.","benchmark":"","weakStrong":""},{"name":"Click-Through Rate (CTR)","type":"Leading","group":"function","category":"Marketing KPIs","definition":"The share of people who click an ad, link, or result after seeing it.","formula":"(Clicks ÷ impressions) × 100.","example":"2,000 clicks ÷ 100,000 impressions = 2%.","benchmark":"","weakStrong":""},{"name":"Email Open Rate","type":"Leading","group":"function","category":"Marketing KPIs","definition":"The share of delivered emails that recipients open.","formula":"(Emails opened ÷ emails delivered) × 100.","example":"4,000 opens ÷ 20,000 delivered = 20%.","benchmark":"","weakStrong":""},{"name":"Email Click Rate","type":"Leading","group":"function","category":"Marketing KPIs","definition":"The share of delivered emails in which a recipient clicks at least one link.","formula":"(Emails with a click ÷ emails delivered) × 100.","example":"600 clicks ÷ 20,000 delivered = 3%.","benchmark":"","weakStrong":""},{"name":"Website Bounce Rate","type":"Lagging","group":"function","category":"Marketing KPIs","definition":"The share of sessions in which a visitor leaves after viewing only one page without further interaction.","formula":"(Single-page sessions ÷ total sessions) × 100.","example":"4,500 single-page sessions ÷ 10,000 sessions = 45%.","benchmark":"","weakStrong":""},{"name":"Marketing-Sourced Pipeline","type":"Lagging","group":"function","category":"Marketing KPIs","definition":"The total value of sales pipeline originated by marketing-generated leads.","formula":"Sum of opportunity value where marketing created the originating lead.","example":"50 opportunities × $20,000 average value = $1,000,000.","benchmark":"","weakStrong":""},{"name":"Brand Search Volume","type":"Leading","group":"function","category":"Marketing KPIs","definition":"The number of searches that include the company or product name, indicating brand demand.","formula":"Sum of monthly search queries containing the brand term.","example":"12,000 branded queries last month = 12,000 searches.","benchmark":"","weakStrong":""},{"name":"Cost Per Acquisition (CPA)","type":"Lagging","group":"function","category":"Marketing KPIs","definition":"The average marketing cost to acquire one customer or completed conversion.","formula":"Total campaign spend ÷ number of acquisitions.","example":"$100,000 ÷ 250 = $400.","benchmark":"","weakStrong":""},{"name":"Marketing Qualified Lead-to-SQL Rate","type":"Lagging","group":"function","category":"Marketing KPIs","definition":"The share of MQLs that sales accepts and qualifies as SQLs, measuring lead quality and handoff alignment.","formula":"(SQLs ÷ MQLs) × 100.","example":"180 SQLs ÷ 600 MQLs = 30%.","benchmark":"","weakStrong":""},{"name":"Gross Profit Margin","type":"Lagging","group":"function","category":"Financial KPIs","definition":"The share of revenue left after the direct cost of goods sold.","formula":"((Revenue − cost of goods sold) ÷ revenue) × 100.","example":"(($1,000,000 − $400,000) ÷ $1,000,000) × 100 = 60%.","benchmark":"","weakStrong":""},{"name":"Net Profit Margin","type":"Lagging","group":"function","category":"Financial KPIs","definition":"The share of revenue remaining as profit after all expenses, interest, and taxes.","formula":"(Net income ÷ revenue) × 100.","example":"$120,000 ÷ $1,000,000 = 12%.","benchmark":"~10% net margin is broadly 'good' and 20%+ is excellent — but it is highly sector-dependent (software runs far higher than grocery)","weakStrong":"\"We're profitable overall\" → \"Expand net profit margin from 12% to 15% within the fiscal year by reducing overhead, owned by the CFO.\""},{"name":"Operating Margin","type":"Lagging","group":"function","category":"Financial KPIs","definition":"The share of revenue left as operating profit after operating expenses but before interest and taxes.","formula":"(Operating income ÷ revenue) × 100.","example":"$180,000 ÷ $1,000,000 = 18%.","benchmark":"","weakStrong":""},{"name":"EBITDA","type":"Lagging","group":"function","category":"Financial KPIs","definition":"Earnings before interest, taxes, depreciation, and amortization, used as a proxy for core operating cash generation.","formula":"Net income + interest + taxes + depreciation + amortization.","example":"$120,000 + $30,000 + $40,000 + $50,000 + $10,000 = $250,000.","benchmark":"","weakStrong":""},{"name":"Revenue Growth Rate","type":"Lagging","group":"function","category":"Financial KPIs","definition":"The percentage change in revenue from one period to the next.","formula":"((Current period revenue − prior period revenue) ÷ prior period revenue) × 100.","example":"(($1,200,000 − $1,000,000) ÷ $1,000,000) × 100 = 20%.","benchmark":"","weakStrong":""},{"name":"Current Ratio","type":"Lagging","group":"function","category":"Financial KPIs","definition":"A liquidity measure of whether current assets can cover current liabilities.","formula":"Current assets ÷ current liabilities.","example":"$600,000 ÷ $300,000 = 2.0.","benchmark":"","weakStrong":""},{"name":"Quick Ratio","type":"Lagging","group":"function","category":"Financial KPIs","definition":"A stricter liquidity measure that excludes inventory from current assets.","formula":"(Current assets − inventory) ÷ current liabilities.","example":"($600,000 − $150,000) ÷ $300,000 = 1.5.","benchmark":"","weakStrong":""},{"name":"Days Sales Outstanding (DSO)","type":"Lagging","group":"function","category":"Financial KPIs","definition":"The average number of days it takes to collect payment after a sale.","formula":"(Accounts receivable ÷ total credit sales) × number of days in the period.","example":"($300,000 ÷ $1,800,000) × 90 = 15 days.","benchmark":"","weakStrong":""},{"name":"Accounts Payable Turnover","type":"Lagging","group":"function","category":"Financial KPIs","definition":"How many times a company pays off its average accounts payable during a period.","formula":"Total supplier purchases ÷ average accounts payable.","example":"$1,200,000 ÷ $200,000 = 6.0×.","benchmark":"","weakStrong":""},{"name":"Cash Conversion Cycle","type":"Lagging","group":"function","category":"Financial KPIs","definition":"The number of days it takes to convert investments in inventory and receivables back into cash, net of payables.","formula":"Days inventory outstanding + days sales outstanding − days payable outstanding.","example":"40 + 15 − 25 = 30 days.","benchmark":"","weakStrong":""},{"name":"Burn Rate","type":"Leading","group":"function","category":"Financial KPIs","definition":"The rate at which a company spends its cash reserves each month, net of revenue.","formula":"(Starting cash − ending cash) ÷ number of months.","example":"($1,200,000 − $900,000) ÷ 3 = $100,000/month.","benchmark":"","weakStrong":""},{"name":"Cash Runway","type":"Leading","group":"function","category":"Financial KPIs","definition":"The number of months a company can operate before exhausting its cash at the current burn rate.","formula":"Current cash balance ÷ monthly net burn rate.","example":"$900,000 ÷ $100,000 = 9 months.","benchmark":"","weakStrong":""},{"name":"Working Capital","type":"Lagging","group":"function","category":"Financial KPIs","definition":"The short-term capital available to fund daily operations.","formula":"Current assets − current liabilities.","example":"$600,000 − $300,000 = $300,000.","benchmark":"","weakStrong":""},{"name":"Return on Equity (ROE)","type":"Lagging","group":"function","category":"Financial KPIs","definition":"The profit generated for every dollar of shareholders' equity.","formula":"(Net income ÷ shareholders' equity) × 100.","example":"$120,000 ÷ $800,000 = 15%.","benchmark":"","weakStrong":""},{"name":"Return on Assets (ROA)","type":"Lagging","group":"function","category":"Financial KPIs","definition":"The profit generated for every dollar of total assets, measuring how efficiently assets produce earnings.","formula":"(Net income ÷ total assets) × 100.","example":"$120,000 ÷ $1,500,000 = 8%.","benchmark":"","weakStrong":""},{"name":"Budget Variance","type":"Lagging","group":"function","category":"Financial KPIs","definition":"The difference between budgeted and actual figures, showing how closely spending or revenue tracked the plan.","formula":"((Actual − budgeted) ÷ budgeted) × 100.","example":"(($1,050,000 − $1,000,000) ÷ $1,000,000) × 100 = +5%.","benchmark":"mature finance teams hold variance within ±5% (often ±3% on operating budgets); the goal is small and explained, not zero","weakStrong":"\"We came in close to budget\" → \"Keep departmental budget variance within ±3% each quarter, with monthly reviews owned by the finance business partner.\""},{"name":"Employee Turnover Rate","type":"Lagging","group":"function","category":"HR & Human Capital KPIs","definition":"The rate at which employees leave the organization over a period.","formula":"(Separations ÷ average headcount) × 100.","example":"18 leavers ÷ 200 avg headcount = 9%.","benchmark":"~10% annual voluntary turnover is often considered healthy; sustained 20%+ usually signals a retention problem, though it varies sharply by sector","weakStrong":"\"Keep turnover low\" → \"Hold voluntary turnover below 10% annually, owned by the People team, reviewed each quarter\"."},{"name":"Employee Retention Rate","type":"Lagging","group":"function","category":"HR & Human Capital KPIs","definition":"The share of employees who stay with the organization over a period.","formula":"(Employees retained ÷ headcount at start) × 100.","example":"184 retained ÷ 200 at start = 92%.","benchmark":"","weakStrong":""},{"name":"Time to Fill","type":"Lagging","group":"function","category":"HR & Human Capital KPIs","definition":"The average number of days from opening a requisition to a candidate accepting the offer.","formula":"Total days to fill ÷ number of roles filled.","example":"1,200 days ÷ 30 hires = 40 days.","benchmark":"","weakStrong":""},{"name":"Cost Per Hire","type":"Lagging","group":"function","category":"HR & Human Capital KPIs","definition":"The average total recruiting cost to fill one open role.","formula":"(Internal + external recruiting costs) ÷ number of hires.","example":"$120,000 ÷ 30 hires = $4,000.","benchmark":"","weakStrong":""},{"name":"Employee Net Promoter Score (eNPS)","type":"Leading","group":"function","category":"HR & Human Capital KPIs","definition":"A measure of how likely employees are to recommend the organization as a place to work.","formula":"% Promoters − % Detractors.","example":"55% promoters − 15% detractors = +40.","benchmark":"","weakStrong":""},{"name":"Absenteeism Rate","type":"Lagging","group":"function","category":"HR & Human Capital KPIs","definition":"The proportion of scheduled workdays lost to unplanned absence.","formula":"(Absent days ÷ total scheduled workdays) × 100.","example":"400 absent days ÷ 50,000 scheduled = 0.8%.","benchmark":"","weakStrong":""},{"name":"Revenue Per Employee","type":"Lagging","group":"function","category":"HR & Human Capital KPIs","definition":"The average revenue generated per full-time employee, a proxy for workforce productivity.","formula":"Total revenue ÷ total headcount.","example":"$40,000,000 ÷ 200 employees = $200,000.","benchmark":"","weakStrong":""},{"name":"Training Hours Per Employee","type":"Leading","group":"function","category":"HR & Human Capital KPIs","definition":"The average hours of formal training delivered per employee over a period.","formula":"Total training hours ÷ total headcount.","example":"4,000 hours ÷ 200 employees = 20 hours.","benchmark":"","weakStrong":""},{"name":"Offer Acceptance Rate","type":"Leading","group":"function","category":"HR & Human Capital KPIs","definition":"The share of job offers extended that candidates accept.","formula":"(Offers accepted ÷ offers extended) × 100.","example":"27 accepted ÷ 30 extended = 90%.","benchmark":"","weakStrong":""},{"name":"Quality of Hire","type":"Lagging","group":"function","category":"HR & Human Capital KPIs","definition":"A composite score of how well new hires perform and stay after joining.","formula":"Average of new-hire performance, retention, and ramp scores (indexed to 100).","example":"(90 performance + 85 retention + 80 ramp) ÷ 3 = 85.","benchmark":"there is no universal number — define it as a composite of ramp time, performance, and one-year retention, then beat your own trailing baseline","weakStrong":"\"Hire good people\" → \"Reach a 90-day quality-of-hire index of 85+, owned by hiring managers, scored at each 90-day review\"."},{"name":"Time to Productivity","type":"Leading","group":"function","category":"HR & Human Capital KPIs","definition":"The average time for a new hire to reach full expected performance.","formula":"Total days to full productivity ÷ number of new hires.","example":"2,700 days ÷ 30 hires = 90 days.","benchmark":"","weakStrong":""},{"name":"Internal Mobility Rate","type":"Leading","group":"function","category":"HR & Human Capital KPIs","definition":"The share of roles filled by existing employees moving internally.","formula":"(Internal moves ÷ total roles filled) × 100.","example":"12 internal moves ÷ 40 roles = 30%.","benchmark":"","weakStrong":""},{"name":"Employee Engagement Score","type":"Leading","group":"function","category":"HR & Human Capital KPIs","definition":"The average level of employee commitment and motivation from survey responses.","formula":"(Favorable responses ÷ total responses) × 100.","example":"1,360 favorable ÷ 1,700 total = 80%.","benchmark":"","weakStrong":""},{"name":"Diversity Ratio","type":"Lagging","group":"function","category":"HR & Human Capital KPIs","definition":"The representation of a given group within the workforce.","formula":"(Employees in group ÷ total headcount) × 100.","example":"90 ÷ 200 employees = 45%.","benchmark":"","weakStrong":""},{"name":"Voluntary vs Involuntary Turnover","type":"Lagging","group":"function","category":"HR & Human Capital KPIs","definition":"The split of departures initiated by employees versus by the organization.","formula":"(Voluntary separations ÷ total separations) × 100.","example":"14 voluntary ÷ 18 total = 78% voluntary.","benchmark":"","weakStrong":""},{"name":"Overall Equipment Effectiveness (OEE)","type":"Lagging","group":"function","category":"Operations & Supply Chain KPIs","definition":"A composite measure of how productively equipment is used, combining availability, performance, and quality.","formula":"Availability × Performance × Quality.","example":"90% × 95% × 99% = ~85%.","benchmark":"85% OEE is the textbook gold-standard mark; ~60% is typical for discrete manufacturers, and under 40% signals major hidden losses","weakStrong":"\"Run machines efficiently\" → \"Hold line OEE at 85%+, owned by the plant manager, reviewed weekly per production line\"."},{"name":"Cycle Time","type":"Lagging","group":"function","category":"Operations & Supply Chain KPIs","definition":"The average time to complete one unit of work from start to finish.","formula":"Total production time ÷ units produced.","example":"600 minutes ÷ 300 units = 2 minutes/unit.","benchmark":"","weakStrong":""},{"name":"Throughput","type":"Lagging","group":"function","category":"Operations & Supply Chain KPIs","definition":"The number of units produced or processed per unit of time.","formula":"Units produced ÷ time period.","example":"4,800 units ÷ 8 hours = 600 units/hour.","benchmark":"","weakStrong":""},{"name":"On-Time Delivery Rate","type":"Lagging","group":"function","category":"Operations & Supply Chain KPIs","definition":"The share of orders delivered on or before the promised date.","formula":"(On-time deliveries ÷ total deliveries) × 100.","example":"950 on-time ÷ 1,000 = 95%.","benchmark":"leading supply chains target 95%+ on-time-in-full; slipping below ~90% starts to erode customer trust","weakStrong":"\"Ship orders on time\" → \"Hit 98% on-time delivery against promised dates, owned by the fulfillment lead, reviewed weekly\"."},{"name":"Order Accuracy Rate","type":"Lagging","group":"function","category":"Operations & Supply Chain KPIs","definition":"The share of orders shipped complete and error-free.","formula":"(Accurate orders ÷ total orders) × 100.","example":"990 accurate ÷ 1,000 = 99%.","benchmark":"","weakStrong":""},{"name":"Inventory Turnover","type":"Lagging","group":"function","category":"Operations & Supply Chain KPIs","definition":"How many times inventory is sold and replaced over a period.","formula":"Cost of goods sold ÷ average inventory.","example":"$6,000,000 ÷ $1,000,000 = 6 turns.","benchmark":"","weakStrong":""},{"name":"Capacity Utilization","type":"Leading","group":"function","category":"Operations & Supply Chain KPIs","definition":"The share of available production capacity actually used.","formula":"(Actual output ÷ maximum possible output) × 100.","example":"800 units ÷ 1,000 capacity = 80%.","benchmark":"","weakStrong":""},{"name":"Defect Rate","type":"Lagging","group":"function","category":"Operations & Supply Chain KPIs","definition":"The proportion of units produced that fail to meet quality standards.","formula":"(Defective units ÷ total units) × 100.","example":"15 defects ÷ 1,000 units = 1.5%.","benchmark":"","weakStrong":""},{"name":"First Pass Yield","type":"Lagging","group":"function","category":"Operations & Supply Chain KPIs","definition":"The share of units that pass through production correctly the first time without rework.","formula":"(Good units first pass ÷ total units started) × 100.","example":"940 ÷ 1,000 = 94%.","benchmark":"","weakStrong":""},{"name":"Lead Time","type":"Lagging","group":"function","category":"Operations & Supply Chain KPIs","definition":"The total elapsed time from order placement to delivery.","formula":"Delivery date − order date (averaged).","example":"140 total days ÷ 20 orders = 7 days.","benchmark":"","weakStrong":""},{"name":"Backorder Rate","type":"Lagging","group":"function","category":"Operations & Supply Chain KPIs","definition":"The share of orders that cannot be fulfilled from current stock.","formula":"(Backordered items ÷ total ordered items) × 100.","example":"30 backordered ÷ 1,000 = 3%.","benchmark":"","weakStrong":""},{"name":"Cost Per Unit","type":"Lagging","group":"function","category":"Operations & Supply Chain KPIs","definition":"The average total cost to produce one unit of output.","formula":"Total production cost ÷ units produced.","example":"$300,000 ÷ 60,000 units = $5/unit.","benchmark":"","weakStrong":""},{"name":"Unplanned Downtime","type":"Lagging","group":"function","category":"Operations & Supply Chain KPIs","definition":"The share of scheduled production time lost to unexpected stoppages.","formula":"(Unplanned downtime ÷ scheduled production time) × 100.","example":"12 hours ÷ 160 hours = 7.5%.","benchmark":"","weakStrong":""},{"name":"Customer Satisfaction (CSAT)","type":"Lagging","group":"function","category":"Customer Service & Success KPIs","definition":"The share of customers who report being satisfied after an interaction.","formula":"(Satisfied responses ÷ total responses) × 100.","example":"880 satisfied ÷ 1,000 = 88%.","benchmark":"75–85% satisfied is a common 'good' band, but the trend and the reasons behind your detractors matter more than the absolute score","weakStrong":"\"Keep customers happy\" → \"Maintain a 90%+ CSAT on post-resolution surveys, owned by the support manager, reviewed monthly\"."},{"name":"Net Promoter Score (NPS)","type":"Lagging","group":"function","category":"Customer Service & Success KPIs","definition":"A measure of customer loyalty based on likelihood to recommend.","formula":"% Promoters − % Detractors.","example":"60% promoters − 15% detractors = +45.","benchmark":"","weakStrong":""},{"name":"Customer Effort Score (CES)","type":"Leading","group":"function","category":"Customer Service & Success KPIs","definition":"How much effort customers feel they expended to get an issue resolved.","formula":"Sum of effort ratings ÷ number of responses (typically 1–7).","example":"1,500 ÷ 1,000 responses = 1.5.","benchmark":"","weakStrong":""},{"name":"First Response Time","type":"Leading","group":"function","category":"Customer Service & Success KPIs","definition":"The average time between a customer raising a ticket and the first reply.","formula":"Total first-response time ÷ number of tickets.","example":"2,000 minutes ÷ 1,000 tickets = 2 minutes.","benchmark":"","weakStrong":""},{"name":"Average Resolution Time","type":"Lagging","group":"function","category":"Customer Service & Success KPIs","definition":"The average time taken to fully resolve a customer issue.","formula":"Total resolution time ÷ number of resolved tickets.","example":"4,000 hours ÷ 1,000 tickets = 4 hours.","benchmark":"","weakStrong":""},{"name":"First Contact Resolution Rate","type":"Lagging","group":"function","category":"Customer Service & Success KPIs","definition":"The share of issues resolved in a single interaction without follow-up.","formula":"(Issues resolved on first contact ÷ total issues) × 100.","example":"750 ÷ 1,000 = 75%.","benchmark":"~70%+ FCR is widely considered strong; every point of FCR tends to cut repeat contacts and cost-to-serve","weakStrong":"\"Resolve issues fast\" → \"Resolve 80% of tickets on first contact, owned by the support team lead, reviewed weekly by channel\"."},{"name":"Ticket Volume","type":"Leading","group":"function","category":"Customer Service & Success KPIs","definition":"The total number of support tickets received over a period.","formula":"Count of tickets created in the period.","example":"5,000 tickets in a month = 5,000.","benchmark":"","weakStrong":""},{"name":"Ticket Backlog","type":"Lagging","group":"function","category":"Customer Service & Success KPIs","definition":"The number of unresolved tickets remaining open at a point in time.","formula":"Tickets opened − tickets closed (cumulative).","example":"1,000 opened − 900 closed = 100 open.","benchmark":"","weakStrong":""},{"name":"Customer Churn Rate","type":"Lagging","group":"function","category":"Customer Service & Success KPIs","definition":"The share of customers lost over a period.","formula":"(Customers lost ÷ customers at start) × 100.","example":"50 lost ÷ 1,000 = 5%.","benchmark":"","weakStrong":""},{"name":"Customer Retention Rate","type":"Lagging","group":"function","category":"Customer Service & Success KPIs","definition":"The share of customers kept over a period, excluding new acquisitions.","formula":"((Customers at end − new customers) ÷ customers at start) × 100.","example":"(1,050 − 100) ÷ 1,000 = 95%.","benchmark":"","weakStrong":""},{"name":"SLA Compliance Rate","type":"Lagging","group":"function","category":"Customer Service & Success KPIs","definition":"The share of tickets resolved within the agreed service-level target.","formula":"(Tickets meeting SLA ÷ total tickets) × 100.","example":"970 ÷ 1,000 = 97%.","benchmark":"","weakStrong":""},{"name":"Escalation Rate","type":"Lagging","group":"function","category":"Customer Service & Success KPIs","definition":"The share of tickets escalated beyond the first support tier.","formula":"(Escalated tickets ÷ total tickets) × 100.","example":"80 escalated ÷ 1,000 = 8%.","benchmark":"","weakStrong":""},{"name":"Customer Health Score","type":"Leading","group":"function","category":"Customer Service & Success KPIs","definition":"A composite index predicting how likely an account is to renew or churn.","formula":"Weighted average of usage, engagement, and support signals (indexed to 100).","example":"(80 usage + 70 engagement + 90 support) weighted = 80.","benchmark":"","weakStrong":""},{"name":"System Uptime / Availability","type":"Lagging","group":"function","category":"IT KPIs","definition":"The share of time a system is operational and available to users.","formula":"(Uptime ÷ total scheduled time) × 100.","example":"7,128 hours ÷ 7,200 = 99%.","benchmark":"99.9% ('three nines') still leaves ~8.8 hours of downtime a year; critical systems target 99.99%","weakStrong":"\"Keep systems up\" → \"Maintain 99.9% availability for tier-1 systems, owned by the infrastructure lead, reviewed monthly against SLA\"."},{"name":"Mean Time to Repair (MTTR)","type":"Lagging","group":"function","category":"IT KPIs","definition":"The average time to restore service after an incident occurs.","formula":"Total repair time ÷ number of incidents.","example":"500 minutes ÷ 10 incidents = 50 minutes.","benchmark":"there is no universal target — set it against your SLA and drive the trend down; elite teams restore tier-1 service in under an hour","weakStrong":"\"Fix outages quickly\" → \"Restore tier-1 service within 60 minutes (MTTR), owned by the on-call lead, reviewed per incident\"."},{"name":"Mean Time Between Failures (MTBF)","type":"Lagging","group":"function","category":"IT KPIs","definition":"The average operating time between system failures, a measure of reliability.","formula":"Total operating time ÷ number of failures.","example":"10,000 hours ÷ 10 failures = 1,000 hours.","benchmark":"","weakStrong":""},{"name":"Mean Time to Detect (MTTD)","type":"Lagging","group":"function","category":"IT KPIs","definition":"The average time between an issue arising and the team detecting it.","formula":"Total detection time ÷ number of incidents.","example":"150 minutes ÷ 10 incidents = 15 minutes.","benchmark":"","weakStrong":""},{"name":"Incident Volume","type":"Leading","group":"function","category":"IT KPIs","definition":"The total number of IT incidents logged over a period.","formula":"Count of incidents in the period.","example":"120 incidents in a month = 120.","benchmark":"","weakStrong":""},{"name":"Average System Response Time","type":"Leading","group":"function","category":"IT KPIs","definition":"The average time a system takes to respond to a request.","formula":"Total response time ÷ number of requests.","example":"2,000 ms ÷ 10,000 requests = 200 ms.","benchmark":"","weakStrong":""},{"name":"Ticket Resolution Time","type":"Lagging","group":"function","category":"IT KPIs","definition":"The average time to close an IT support ticket.","formula":"Total resolution time ÷ number of tickets.","example":"3,000 hours ÷ 1,000 tickets = 3 hours.","benchmark":"","weakStrong":""},{"name":"Cost Per Ticket","type":"Lagging","group":"function","category":"IT KPIs","definition":"The average cost to handle one IT support ticket.","formula":"Total support cost ÷ number of tickets.","example":"$25,000 ÷ 1,000 tickets = $25.","benchmark":"","weakStrong":""},{"name":"Security Incident Count","type":"Lagging","group":"function","category":"IT KPIs","definition":"The number of confirmed security incidents over a period.","formula":"Count of verified security incidents in the period.","example":"4 incidents in a quarter = 4.","benchmark":"","weakStrong":""},{"name":"Patch Compliance Rate","type":"Leading","group":"function","category":"IT KPIs","definition":"The share of systems patched to the required level within policy timelines.","formula":"(Compliant systems ÷ total systems) × 100.","example":"950 ÷ 1,000 = 95%.","benchmark":"","weakStrong":""},{"name":"Backup Success Rate","type":"Lagging","group":"function","category":"IT KPIs","definition":"The share of scheduled backups that complete successfully.","formula":"(Successful backups ÷ total scheduled backups) × 100.","example":"990 ÷ 1,000 = 99%.","benchmark":"","weakStrong":""},{"name":"Sprint Velocity","type":"Lagging","group":"function","category":"IT KPIs","definition":"The average amount of work a development team completes per sprint.","formula":"Total story points completed ÷ number of sprints.","example":"120 points ÷ 3 sprints = 40 points/sprint.","benchmark":"","weakStrong":""},{"name":"On-Time Completion Rate","type":"Lagging","group":"function","category":"Project Management KPIs","definition":"The share of projects or tasks completed by their planned due date.","formula":"(Completed on time ÷ total completed) × 100.","example":"45 on time ÷ 50 = 90%.","benchmark":"across 500+ organizations on the ClearPoint platform, only about 14% of initiatives are ever completed — and projects with a named owner finish roughly 2.5× as often, so 'has an owner' is the first target","weakStrong":"\"Deliver projects on time\" → \"Complete 90% of milestones by their baseline date, owned by the project manager, reviewed at each gate\"."},{"name":"On-Budget Completion Rate","type":"Lagging","group":"function","category":"Project Management KPIs","definition":"The share of projects completed at or under their approved budget.","formula":"(Projects on/under budget ÷ total projects) × 100.","example":"44 ÷ 50 = 88%.","benchmark":"","weakStrong":""},{"name":"Schedule Variance (SV)","type":"Lagging","group":"function","category":"Project Management KPIs","definition":"The difference between work scheduled and work performed, expressed in cost terms.","formula":"Earned Value − Planned Value.","example":"$90,000 EV − $100,000 PV = −$10,000.","benchmark":"","weakStrong":""},{"name":"Cost Variance (CV)","type":"Lagging","group":"function","category":"Project Management KPIs","definition":"The difference between budgeted and actual cost of work performed.","formula":"Earned Value − Actual Cost.","example":"$90,000 EV − $95,000 AC = −$5,000.","benchmark":"","weakStrong":""},{"name":"Cost Performance Index (CPI)","type":"Leading","group":"function","category":"Project Management KPIs","definition":"A measure of cost efficiency comparing earned value to actual cost.","formula":"Earned Value ÷ Actual Cost.","example":"$90,000 ÷ $95,000 = 0.95.","benchmark":"a CPI of 1.0 means you are exactly on budget; below 1.0 is over budget; sustained ≥1.0 across the portfolio is the goal","weakStrong":"\"Stay on budget\" → \"Hold CPI at or above 1.0 across active projects, owned by the PMO, reviewed monthly\"."},{"name":"Schedule Performance Index (SPI)","type":"Leading","group":"function","category":"Project Management KPIs","definition":"A measure of schedule efficiency comparing earned value to planned value.","formula":"Earned Value ÷ Planned Value.","example":"$90,000 ÷ $100,000 = 0.90.","benchmark":"","weakStrong":""},{"name":"Resource Utilization Rate","type":"Leading","group":"function","category":"Project Management KPIs","definition":"The share of available resource time spent on productive project work.","formula":"(Billable or project hours ÷ total available hours) × 100.","example":"1,500 ÷ 2,000 hours = 75%.","benchmark":"","weakStrong":""},{"name":"Scope Creep","type":"Lagging","group":"function","category":"Project Management KPIs","definition":"The degree to which project scope expands beyond the original baseline.","formula":"((Added scope items ÷ original scope items) × 100).","example":"8 added ÷ 40 original = 20%.","benchmark":"","weakStrong":""},{"name":"Milestone Hit Rate","type":"Lagging","group":"function","category":"Project Management KPIs","definition":"The share of project milestones met on or before their target date.","formula":"(Milestones hit on time ÷ total milestones) × 100.","example":"18 ÷ 20 = 90%.","benchmark":"","weakStrong":""},{"name":"Earned Value (EV)","type":"Lagging","group":"function","category":"Project Management KPIs","definition":"The budgeted value of work actually completed at a point in time.","formula":"% work complete × budget at completion.","example":"45% × $200,000 = $90,000.","benchmark":"","weakStrong":""},{"name":"Planned vs Actual Hours","type":"Lagging","group":"function","category":"Project Management KPIs","definition":"The comparison of hours estimated for work against hours actually spent.","formula":"(Actual hours ÷ planned hours) × 100.","example":"1,100 actual ÷ 1,000 planned = 110%.","benchmark":"","weakStrong":""},{"name":"Risk Count","type":"Leading","group":"function","category":"Project Management KPIs","definition":"The number of active, identified risks tracked on a project at a point in time.","formula":"Count of open risks in the risk register.","example":"12 open risks logged = 12.","benchmark":"","weakStrong":""},{"name":"Emergency Response Time","type":"Lagging","group":"industry","category":"Local Government KPIs","definition":"Average elapsed time from a 911 call being received to the first responder arriving on scene.","formula":"Sum of all response times ÷ number of incidents.","example":"5,400 minutes ÷ 720 incidents = 7.5 min average.","benchmark":"NFPA 1710 sets a 4-minute first-engine response standard for career fire departments and ~8 minutes for EMS; response time is one of the most-tracked KPIs across the governments on the ClearPoint platform","weakStrong":"\"We respond to emergencies quickly\" → \"Median fire/EMS response under 7 minutes for 90% of priority-1 calls, owned by the Fire Chief, reviewed monthly\"."},{"name":"311 Service Request Resolution Rate","type":"Lagging","group":"industry","category":"Local Government KPIs","definition":"Share of non-emergency 311 service requests closed within the published target window.","formula":"(Requests resolved on time ÷ total requests received) × 100.","example":"8,500 ÷ 10,000 = 85% resolution rate.","benchmark":"leading cities publish on-time closure rates by request type and target 90%+ within the posted service-level window","weakStrong":"\"We handle citizen requests\" → \"Close 90% of 311 requests within the service-level target by Q4, owned by the 311 Operations Manager\"."},{"name":"Permit Processing Time","type":"Lagging","group":"industry","category":"Local Government KPIs","definition":"Average number of business days from permit application submission to final approval or issuance.","formula":"Sum of processing days ÷ number of permits issued.","example":"4,200 days ÷ 600 permits = 7 days average.","benchmark":"","weakStrong":""},{"name":"Road/Pavement Condition Index","type":"Lagging","group":"industry","category":"Local Government KPIs","definition":"Composite score (typically 0–100) rating the surface condition of a road network from field inspections.","formula":"Weighted average of individual segment condition scores across the network.","example":"Network-wide weighted average = 72 PCI (good).","benchmark":"","weakStrong":""},{"name":"General Fund Balance","type":"Lagging","group":"industry","category":"Local Government KPIs","definition":"Unrestricted reserves held in the general fund, often expressed as months of operating expenditure.","formula":"Unassigned fund balance ÷ average monthly operating expenditure.","example":"$30M ÷ $5M per month = 6 months of reserves.","benchmark":"","weakStrong":""},{"name":"Budget Variance","type":"Leading","group":"industry","category":"Local Government KPIs","definition":"Difference between budgeted and actual spending, signaling fiscal discipline before year-end results land.","formula":"((Actual − budgeted) ÷ budgeted) × 100.","example":"(($52M − $50M) ÷ $50M) × 100 = +4% over budget.","benchmark":"","weakStrong":""},{"name":"Citizen Satisfaction Score","type":"Lagging","group":"industry","category":"Local Government KPIs","definition":"Resident-rated satisfaction with municipal services, captured through community surveys.","formula":"(Satisfied respondents ÷ total respondents) × 100.","example":"1,560 ÷ 2,000 = 78% satisfaction.","benchmark":"","weakStrong":""},{"name":"Crime Rate / Clearance Rate","type":"Lagging","group":"industry","category":"Local Government KPIs","definition":"Crime rate is reported offenses per 100,000 residents; clearance rate is the share of those crimes solved or closed.","formula":"Clearance rate = (cases cleared ÷ reported cases) × 100.","example":"1,800 cleared ÷ 6,000 reported = 30% clearance rate.","benchmark":"","weakStrong":""},{"name":"Infrastructure Projects On-Time","type":"Lagging","group":"industry","category":"Local Government KPIs","definition":"Share of capital infrastructure projects completed on or before their scheduled deadline.","formula":"(Projects delivered on time ÷ total projects completed) × 100.","example":"34 ÷ 40 = 85% on-time.","benchmark":"","weakStrong":""},{"name":"Water Quality Compliance Rate","type":"Lagging","group":"industry","category":"Local Government KPIs","definition":"Percentage of water quality tests that meet regulatory safety standards over a reporting period.","formula":"(Compliant samples ÷ total samples tested) × 100.","example":"1,990 ÷ 2,000 = 99.5% compliance.","benchmark":"","weakStrong":""},{"name":"Property Tax Collection Rate","type":"Lagging","group":"industry","category":"Local Government KPIs","definition":"Share of property taxes levied that are actually collected within the fiscal year.","formula":"(Taxes collected ÷ taxes levied) × 100.","example":"$96M ÷ $100M = 96% collection rate.","benchmark":"","weakStrong":""},{"name":"Average Time to Fill Potholes","type":"Lagging","group":"industry","category":"Local Government KPIs","definition":"Average elapsed time from a pothole being reported to it being repaired.","formula":"Sum of repair times ÷ number of potholes filled.","example":"4,800 hours ÷ 1,600 potholes = 3 hours average.","benchmark":"","weakStrong":""},{"name":"Public Transit On-Time Performance","type":"Lagging","group":"industry","category":"Local Government KPIs","definition":"Percentage of transit trips arriving within the agency's defined on-time window.","formula":"(On-time trips ÷ total scheduled trips) × 100.","example":"18,400 ÷ 20,000 = 92% on-time.","benchmark":"","weakStrong":""},{"name":"Hospital Readmission Rate","type":"Lagging","group":"industry","category":"Healthcare KPIs","definition":"Share of discharged patients readmitted to a hospital within a defined window, typically 30 days.","formula":"(Readmissions within 30 days ÷ total discharges) × 100.","example":"240 ÷ 3,000 = 8% readmission rate.","benchmark":"U.S. 30-day all-cause readmission runs ~14–15%, and CMS financially penalizes excess readmissions, so beating the national rate is the goal","weakStrong":"\"Reduce readmissions\" → \"Cut 30-day all-cause readmissions to under 10% for heart-failure patients by year-end, owned by the VP of Quality\"."},{"name":"Average Length of Stay (ALOS)","type":"Lagging","group":"industry","category":"Healthcare KPIs","definition":"Average number of days an admitted patient stays in the hospital per inpatient episode.","formula":"Total inpatient days ÷ number of discharges (or admissions).","example":"12,600 patient days ÷ 3,000 discharges = 4.2 days ALOS.","benchmark":"","weakStrong":""},{"name":"Bed Occupancy Rate","type":"Lagging","group":"industry","category":"Healthcare KPIs","definition":"Proportion of available inpatient beds occupied over a period, indicating capacity utilization.","formula":"(Occupied bed days ÷ available bed days) × 100.","example":"25,500 ÷ 30,000 = 85% occupancy.","benchmark":"","weakStrong":""},{"name":"Patient Satisfaction (HCAHPS)","type":"Lagging","group":"industry","category":"Healthcare KPIs","definition":"Standardized survey measuring patients' perspectives on their hospital care, often summarized as the share giving a top-box rating.","formula":"(Top-box \"9 or 10\" overall ratings ÷ total survey respondents) × 100.","example":"1,440 ÷ 1,800 = 80% top-box score.","benchmark":"track the top-box (9–10) share against the national CMS percentile; the target is steady movement up the percentile, not a single fixed number","weakStrong":"\"Improve patient experience\" → \"Raise HCAHPS overall top-box rating to 82% across med-surg units by Q3, owned by the Chief Nursing Officer\"."},{"name":"Hospital-Acquired Infection (HAI) Rate","type":"Lagging","group":"industry","category":"Healthcare KPIs","definition":"Rate of infections patients contract during their hospital stay, normalized to patient exposure.","formula":"(Number of HAIs ÷ patient days) × 1,000.","example":"(45 ÷ 30,000) × 1,000 = 1.5 infections per 1,000 patient days.","benchmark":"","weakStrong":""},{"name":"Emergency Department Wait Time","type":"Lagging","group":"industry","category":"Healthcare KPIs","definition":"Average time from a patient's ED arrival to being seen by a qualified clinical provider.","formula":"Sum of door-to-provider times ÷ number of ED patients.","example":"50,000 minutes ÷ 2,000 patients = 25 min average.","benchmark":"","weakStrong":""},{"name":"Mortality Rate","type":"Lagging","group":"industry","category":"Healthcare KPIs","definition":"Share of admitted patients who die during their hospital stay, often risk-adjusted for case mix.","formula":"(In-hospital deaths ÷ total discharges) × 100.","example":"60 ÷ 3,000 = 2% mortality rate.","benchmark":"","weakStrong":""},{"name":"Medication Error Rate","type":"Lagging","group":"industry","category":"Healthcare KPIs","definition":"Frequency of medication errors relative to the volume of doses administered.","formula":"(Medication errors ÷ total doses administered) × 100.","example":"150 ÷ 50,000 = 0.3% error rate.","benchmark":"","weakStrong":""},{"name":"Claim Denial Rate","type":"Lagging","group":"industry","category":"Healthcare KPIs","definition":"Percentage of submitted insurance claims denied by payers on first submission.","formula":"(Denied claims ÷ total claims submitted) × 100.","example":"700 ÷ 10,000 = 7% denial rate.","benchmark":"","weakStrong":""},{"name":"Days in Accounts Receivable","type":"Lagging","group":"industry","category":"Healthcare KPIs","definition":"Average number of days it takes to collect payment after a service is billed.","formula":"(Total accounts receivable ÷ average daily net patient revenue).","example":"$9M ÷ $200K per day = 45 days in A/R.","benchmark":"","weakStrong":""},{"name":"Patient No-Show Rate","type":"Lagging","group":"industry","category":"Healthcare KPIs","definition":"Share of scheduled appointments where the patient fails to attend without canceling.","formula":"(No-show appointments ÷ total scheduled appointments) × 100.","example":"800 ÷ 8,000 = 10% no-show rate.","benchmark":"","weakStrong":""},{"name":"Staff-to-Patient Ratio","type":"Leading","group":"industry","category":"Healthcare KPIs","definition":"Number of clinical staff (e.g., nurses) available per patient, a leading indicator of care capacity and safety.","formula":"Number of nurses on shift ÷ number of patients.","example":"25 nurses ÷ 100 patients = 1:4 ratio.","benchmark":"","weakStrong":""},{"name":"Operating Margin","type":"Lagging","group":"industry","category":"Healthcare KPIs","definition":"Profitability of core operations as a share of total operating revenue.","formula":"((Operating revenue − operating expenses) ÷ operating revenue) × 100.","example":"(($210M − $200M) ÷ $210M) × 100 = 4.8% margin.","benchmark":"","weakStrong":""},{"name":"Student Enrollment","type":"Lagging","group":"industry","category":"Higher Education KPIs","definition":"Total count of students registered at the institution for a given term, typically reported as headcount or full-time equivalent.","formula":"Sum of all registered students for the term.","example":"9,200 undergraduates + 2,800 graduates = 12,000 enrolled.","benchmark":"","weakStrong":""},{"name":"Student Retention Rate","type":"Leading","group":"industry","category":"Higher Education KPIs","definition":"Share of first-year students who return to the same institution for their second year, an early signal of eventual graduation.","formula":"(Students returning year two ÷ first-year cohort) × 100.","example":"2,550 ÷ 3,000 = 85% retention.","benchmark":"first-to-second-year retention averages ~75% at four-year institutions and swings widely by selectivity, so set the target against your peer group","weakStrong":"\"Keep more students\" → \"Lift first-to-second-year retention to 87% for the incoming cohort by next fall, owned by the VP of Student Success\"."},{"name":"Graduation Rate","type":"Lagging","group":"industry","category":"Higher Education KPIs","definition":"Share of an entering cohort that completes a degree within a defined period, commonly 150% of normal time (6 years for a 4-year degree).","formula":"(Graduates within the window ÷ entering cohort) × 100.","example":"1,950 ÷ 3,000 = 65% 6-year graduation rate.","benchmark":"the federal 6-year graduation rate averages ~60–64% at four-year schools; compare to peer institutions rather than a universal bar","weakStrong":"\"Graduate more students\" → \"Raise the 6-year graduation rate to 68% for the 2020 entering cohort, owned by the Provost\"."},{"name":"Student-to-Faculty Ratio","type":"Lagging","group":"industry","category":"Higher Education KPIs","definition":"Number of students per full-time-equivalent instructional faculty member, a proxy for class size and access.","formula":"FTE students ÷ FTE faculty.","example":"12,000 ÷ 800 = 15:1 ratio.","benchmark":"","weakStrong":""},{"name":"Cost Per Student","type":"Lagging","group":"industry","category":"Higher Education KPIs","definition":"Total educational expenditure divided by enrollment, measuring the cost of delivering instruction per student.","formula":"Total operating expenditure ÷ FTE students.","example":"$240M ÷ 12,000 = $20,000 per student.","benchmark":"","weakStrong":""},{"name":"Job Placement Rate","type":"Lagging","group":"industry","category":"Higher Education KPIs","definition":"Share of graduates employed or in further education within a set period after graduation, typically six months.","formula":"(Graduates placed ÷ graduates seeking placement) × 100.","example":"1,700 ÷ 2,000 = 85% placement.","benchmark":"","weakStrong":""},{"name":"Time-to-Degree","type":"Lagging","group":"industry","category":"Higher Education KPIs","definition":"Average elapsed time students take to complete their degree from initial enrollment.","formula":"Sum of years to completion ÷ number of graduates.","example":"8,400 years ÷ 2,000 graduates = 4.2 years average.","benchmark":"","weakStrong":""},{"name":"Course Completion Rate","type":"Leading","group":"industry","category":"Higher Education KPIs","definition":"Share of enrolled course seats that students complete with a passing grade, an early indicator of progression.","formula":"(Courses completed successfully ÷ courses enrolled) × 100.","example":"46,000 ÷ 50,000 = 92% completion.","benchmark":"","weakStrong":""},{"name":"Research Funding Secured","type":"Lagging","group":"industry","category":"Higher Education KPIs","definition":"Total value of external research grants and contracts awarded to the institution in a period.","formula":"Sum of all awarded grant and contract dollars.","example":"180 awards totaling $45M secured.","benchmark":"","weakStrong":""},{"name":"Alumni Giving Rate","type":"Lagging","group":"industry","category":"Higher Education KPIs","definition":"Share of solicitable alumni who make a financial gift to the institution in a given year.","formula":"(Alumni donors ÷ total solicitable alumni) × 100.","example":"12,000 ÷ 100,000 = 12% giving rate.","benchmark":"","weakStrong":""},{"name":"Application Yield Rate","type":"Leading","group":"industry","category":"Higher Education KPIs","definition":"Share of admitted students who choose to enroll, signaling enrollment strength ahead of the term.","formula":"(Students who enroll ÷ students admitted) × 100.","example":"3,000 ÷ 7,500 = 40% yield.","benchmark":"","weakStrong":""},{"name":"Endowment Growth","type":"Lagging","group":"industry","category":"Higher Education KPIs","definition":"Year-over-year percentage change in the market value of the institution's endowment.","formula":"((Ending value − beginning value) ÷ beginning value) × 100.","example":"(($840M − $800M) ÷ $800M) × 100 = 5% growth.","benchmark":"","weakStrong":""},{"name":"System Average Interruption Duration Index (SAIDI)","type":"Lagging","group":"industry","category":"Utilities & Energy KPIs","definition":"Average total duration of outages experienced by a customer over a period, measured in minutes per customer per year.","formula":"Sum of all customer interruption durations ÷ total number of customers served.","example":"9,000,000 customer-minutes ÷ 100,000 customers = 90 minutes per customer.","benchmark":"U.S. utilities average roughly 100–150 minutes of interruption per customer per year excluding major events (which are reported separately); lower is better","weakStrong":"\"Improve reliability\" → \"Cut SAIDI to under 90 minutes per customer this year (excluding major events), owned by the VP of Grid Operations\"."},{"name":"System Average Interruption Frequency Index (SAIFI)","type":"Lagging","group":"industry","category":"Utilities & Energy KPIs","definition":"Average number of sustained interruptions a customer experiences over a period.","formula":"Total number of customer interruptions ÷ total number of customers served.","example":"120,000 customer interruptions ÷ 100,000 customers = 1.2 interruptions per customer.","benchmark":"","weakStrong":""},{"name":"Customer Average Interruption Duration Index (CAIDI)","type":"Lagging","group":"industry","category":"Utilities & Energy KPIs","definition":"Average time to restore service per interruption, effectively SAIDI divided by SAIFI.","formula":"SAIDI ÷ SAIFI (sum of interruption durations ÷ total number of interruptions).","example":"90 minutes ÷ 1.2 interruptions = 75 minutes per interruption.","benchmark":"","weakStrong":""},{"name":"Percent Renewable Generation","type":"Lagging","group":"industry","category":"Utilities & Energy KPIs","definition":"Share of total energy generated or delivered that comes from renewable sources.","formula":"(Renewable generation ÷ total generation) × 100.","example":"1,200 GWh ÷ 4,000 GWh = 30% renewable.","benchmark":"","weakStrong":""},{"name":"Line Loss / Transmission Loss","type":"Lagging","group":"industry","category":"Utilities & Energy KPIs","definition":"Share of generated electricity lost during transmission and distribution before reaching customers.","formula":"((Energy generated − energy delivered) ÷ energy generated) × 100.","example":"((4,000 − 3,760) ÷ 4,000) × 100 = 6% line loss.","benchmark":"","weakStrong":""},{"name":"Customer Satisfaction","type":"Lagging","group":"industry","category":"Utilities & Energy KPIs","definition":"Customer-rated satisfaction with utility service, reliability, and support, captured via survey.","formula":"(Satisfied respondents ÷ total respondents) × 100.","example":"4,200 ÷ 5,000 = 84% satisfaction.","benchmark":"","weakStrong":""},{"name":"Safety Incident Rate (OSHA Recordables)","type":"Lagging","group":"industry","category":"Utilities & Energy KPIs","definition":"OSHA-recordable injuries and illnesses normalized to 100 full-time workers per year (the Total Recordable Incident Rate).","formula":"(Number of recordable incidents × 200,000) ÷ total hours worked.","example":"(12 × 200,000) ÷ 1,000,000 = 2.4 TRIR.","benchmark":"a Total Recordable Incident Rate under ~3.0 is broadly considered good; the safest operations push toward zero","weakStrong":"\"Work safely\" → \"Hold the Total Recordable Incident Rate below 2.0 across field crews this year, owned by the Director of Health & Safety\"."},{"name":"Capacity Factor","type":"Lagging","group":"industry","category":"Utilities & Energy KPIs","definition":"Ratio of actual energy output to the maximum possible output if a plant ran at full capacity the entire period.","formula":"(Actual energy output ÷ (rated capacity × hours in period)) × 100.","example":"(3,066 GWh ÷ 4,380 GWh) × 100 = 70% capacity factor.","benchmark":"","weakStrong":""},{"name":"Non-Revenue Water (Water Loss)","type":"Lagging","group":"industry","category":"Utilities & Energy KPIs","definition":"Share of water produced that is lost to leaks, theft, or metering errors before it is billed.","formula":"((Water supplied − water billed) ÷ water supplied) × 100.","example":"((10,000 − 8,500) ÷ 10,000) × 100 = 15% non-revenue water.","benchmark":"","weakStrong":""},{"name":"Regulatory Compliance Rate","type":"Lagging","group":"industry","category":"Utilities & Energy KPIs","definition":"Share of applicable regulatory requirements and reporting obligations met without violation in a period.","formula":"(Requirements met ÷ total applicable requirements) × 100.","example":"245 ÷ 250 = 98% compliance.","benchmark":"","weakStrong":""},{"name":"Average Restoration Time","type":"Lagging","group":"industry","category":"Utilities & Energy KPIs","definition":"Average time taken to restore service to customers after an outage begins.","formula":"Sum of restoration times ÷ number of outage events.","example":"4,500 minutes ÷ 60 outages = 75 min average.","benchmark":"","weakStrong":""},{"name":"Net Interest Margin (NIM)","type":"Lagging","group":"industry","category":"Banking & Financial Services KPIs","definition":"The spread a bank earns between interest generated on assets and interest paid on funding, relative to its earning assets.","formula":"(Interest income − interest expense) ÷ average earning assets.","example":"($120M − $45M) ÷ $2.5B = 3.0%.","benchmark":"U.S. bank net interest margins typically sit around ~3%; the right target depends on asset mix and the rate environment","weakStrong":"\"Improve our margins\" → \"Lift NIM from 3.0% to 3.3% by Q4, owned by the Treasury lead through repricing the loan book\"."},{"name":"Return on Assets (ROA)","type":"Lagging","group":"industry","category":"Banking & Financial Services KPIs","definition":"How efficiently a bank converts its total assets into net profit.","formula":"Net income ÷ average total assets.","example":"$90M ÷ $7.5B = 1.2%.","benchmark":"","weakStrong":""},{"name":"Return on Equity (ROE)","type":"Lagging","group":"industry","category":"Banking & Financial Services KPIs","definition":"The return generated on shareholders' invested capital.","formula":"Net income ÷ average shareholders' equity.","example":"$90M ÷ $750M = 12%.","benchmark":"","weakStrong":""},{"name":"Efficiency Ratio","type":"Lagging","group":"industry","category":"Banking & Financial Services KPIs","definition":"The share of revenue consumed by operating expenses, where lower is better.","formula":"Non-interest expense ÷ (net interest income + non-interest income).","example":"$180M ÷ $300M = 60%.","benchmark":"below 50% is excellent for a bank, 50–60% is solid, and above ~70% signals cost pressure (lower is better)","weakStrong":"\"Cut costs\" → \"Bring the efficiency ratio below 58% within two quarters, owned by the COO via branch consolidation\"."},{"name":"Non-Performing Loan (NPL) Ratio","type":"Lagging","group":"industry","category":"Banking & Financial Services KPIs","definition":"The proportion of the loan portfolio that is in or near default.","formula":"Non-performing loans ÷ total gross loans.","example":"$40M ÷ $2B = 2.0%.","benchmark":"","weakStrong":""},{"name":"Common Equity Tier 1 (CET1) Capital Ratio","type":"Lagging","group":"industry","category":"Banking & Financial Services KPIs","definition":"A bank's core equity capital measured against its risk-weighted assets, the central regulatory solvency gauge.","formula":"CET1 capital ÷ risk-weighted assets.","example":"$600M ÷ $5B = 12%.","benchmark":"","weakStrong":""},{"name":"Loan-to-Deposit Ratio","type":"Leading","group":"industry","category":"Banking & Financial Services KPIs","definition":"How much of a bank's deposits are lent out, signaling liquidity and lending appetite.","formula":"Total loans ÷ total deposits.","example":"$2B ÷ $2.5B = 80%.","benchmark":"","weakStrong":""},{"name":"Cost of Funds","type":"Leading","group":"industry","category":"Banking & Financial Services KPIs","definition":"The average interest rate a bank pays to fund its assets through deposits and borrowings.","formula":"Total interest expense ÷ average interest-bearing liabilities.","example":"$45M ÷ $2.25B = 2.0%.","benchmark":"","weakStrong":""},{"name":"Deposit Growth Rate","type":"Leading","group":"industry","category":"Banking & Financial Services KPIs","definition":"The pace at which a bank's deposit base is expanding over a period.","formula":"(Ending deposits − beginning deposits) ÷ beginning deposits.","example":"($2.5B − $2.3B) ÷ $2.3B = 8.7%.","benchmark":"","weakStrong":""},{"name":"Non-Interest (Fee) Income Ratio","type":"Lagging","group":"industry","category":"Banking & Financial Services KPIs","definition":"The share of total revenue coming from fees and services rather than lending spread.","formula":"Non-interest income ÷ total revenue.","example":"$90M ÷ $300M = 30%.","benchmark":"","weakStrong":""},{"name":"Customer Acquisition Cost","type":"Leading","group":"industry","category":"Banking & Financial Services KPIs","definition":"The average marketing and onboarding cost to win one new banking customer.","formula":"Total acquisition spend ÷ new customers acquired.","example":"$3M ÷ 15,000 = $200.","benchmark":"","weakStrong":""},{"name":"Digital Adoption Rate","type":"Leading","group":"industry","category":"Banking & Financial Services KPIs","definition":"The percentage of customers actively using digital banking channels.","formula":"Active digital users ÷ total customers.","example":"480,000 ÷ 600,000 = 80%.","benchmark":"","weakStrong":""},{"name":"Overall Equipment Effectiveness (OEE)","type":"Lagging","group":"industry","category":"Manufacturing KPIs","definition":"A composite score of how fully manufacturing equipment is utilized, combining availability, performance, and quality.","formula":"Availability × Performance × Quality.","example":"90% × 95% × 98% = 83.8%.","benchmark":"85% OEE is the textbook gold-standard mark; ~60% is typical for discrete manufacturers, and under 40% signals major hidden losses","weakStrong":"\"Run the lines better\" → \"Raise Line 3 OEE from 83% to 88% by year-end, owned by the plant manager via downtime root-cause fixes\"."},{"name":"Scrap Rate","type":"Lagging","group":"industry","category":"Manufacturing KPIs","definition":"The share of produced material discarded as unusable waste.","formula":"Scrapped units ÷ total units produced.","example":"600 ÷ 30,000 = 2.0%.","benchmark":"","weakStrong":""},{"name":"First Pass Yield","type":"Lagging","group":"industry","category":"Manufacturing KPIs","definition":"The percentage of units made correctly the first time without rework or scrap.","formula":"Good units (no rework) ÷ total units started.","example":"28,500 ÷ 30,000 = 95%.","benchmark":"the best lines approach 99%+ first pass yield; the gap to 100% is your hidden cost of poor quality","weakStrong":"\"Reduce defects\" → \"Lift first pass yield from 95% to 97% on the assembly cell within one quarter, owned by the quality engineer\"."},{"name":"On-Time Delivery","type":"Lagging","group":"industry","category":"Manufacturing KPIs","definition":"The proportion of customer orders shipped by the promised date.","formula":"Orders delivered on time ÷ total orders shipped.","example":"4,750 ÷ 5,000 = 95%.","benchmark":"","weakStrong":""},{"name":"Inventory Turns","type":"Lagging","group":"industry","category":"Manufacturing KPIs","definition":"How many times inventory is sold and replaced over a period, indicating working-capital efficiency.","formula":"Cost of goods sold ÷ average inventory.","example":"$48M ÷ $8M = 6.0 turns.","benchmark":"","weakStrong":""},{"name":"Unplanned Downtime","type":"Leading","group":"industry","category":"Manufacturing KPIs","definition":"The share of scheduled production time lost to unexpected equipment stoppages.","formula":"Unplanned downtime hours ÷ scheduled production hours.","example":"60 ÷ 600 = 10%.","benchmark":"","weakStrong":""},{"name":"Throughput","type":"Leading","group":"industry","category":"Manufacturing KPIs","definition":"The volume of good units a process produces per unit of time.","formula":"Total good units produced ÷ time period.","example":"24,000 units ÷ 20 hours = 1,200 units/hour.","benchmark":"","weakStrong":""},{"name":"Defects Per Million (PPM)","type":"Lagging","group":"industry","category":"Manufacturing KPIs","definition":"The number of defective parts expected per one million produced, a precision quality measure.","formula":"(Defective units ÷ total units) × 1,000,000.","example":"(15 ÷ 30,000) × 1,000,000 = 500 PPM.","benchmark":"","weakStrong":""},{"name":"Safety Incident Rate","type":"Lagging","group":"industry","category":"Manufacturing KPIs","definition":"The frequency of recordable workplace injuries normalized to hours worked (OSHA TRIR basis).","formula":"(Recordable incidents × 200,000) ÷ total hours worked.","example":"(5 × 200,000) ÷ 400,000 = 2.5.","benchmark":"","weakStrong":""},{"name":"Cost Per Unit","type":"Lagging","group":"industry","category":"Manufacturing KPIs","definition":"The fully loaded production cost to make one unit of output.","formula":"Total production costs ÷ total units produced.","example":"$1.5M ÷ 30,000 = $50.","benchmark":"","weakStrong":""},{"name":"Conversion Rate","type":"Leading","group":"industry","category":"Retail & E-commerce KPIs","definition":"The share of visitors or shoppers who complete a purchase.","formula":"Transactions ÷ total visits (or visitors).","example":"4,000 ÷ 160,000 = 2.5%.","benchmark":"e-commerce conversion typically runs 2–3%; well-optimized stores clear 4%+","weakStrong":"\"Sell more online\" → \"Raise site conversion from 2.5% to 3.1% by Q3, owned by the ecommerce lead via checkout redesign\"."},{"name":"Average Order Value (AOV)","type":"Lagging","group":"industry","category":"Retail & E-commerce KPIs","definition":"The average revenue collected per order placed.","formula":"Total revenue ÷ number of orders.","example":"$340,000 ÷ 4,000 = $85.","benchmark":"there is no universal number — grow it against your own baseline via bundling and free-ship thresholds, and always watch it alongside margin","weakStrong":"\"Get bigger baskets\" → \"Grow AOV from $85 to $95 within two quarters, owned by merchandising via bundles and free-ship thresholds\"."},{"name":"Sales Per Square Foot","type":"Lagging","group":"industry","category":"Retail & E-commerce KPIs","definition":"Revenue generated per unit of selling floor space, a core store-productivity measure.","formula":"Net sales ÷ selling square footage.","example":"$2.5M ÷ 5,000 = $500/sq ft.","benchmark":"","weakStrong":""},{"name":"Inventory Turnover","type":"Lagging","group":"industry","category":"Retail & E-commerce KPIs","definition":"How many times stock is sold through and replenished over a period.","formula":"Cost of goods sold ÷ average inventory.","example":"$6M ÷ $1.2M = 5.0 turns.","benchmark":"","weakStrong":""},{"name":"Gross Margin Return on Investment (GMROI)","type":"Lagging","group":"industry","category":"Retail & E-commerce KPIs","definition":"The gross margin earned for every dollar invested in inventory.","formula":"Gross margin ÷ average inventory cost.","example":"$3M ÷ $1.2M = $2.50.","benchmark":"","weakStrong":""},{"name":"Cart Abandonment Rate","type":"Leading","group":"industry","category":"Retail & E-commerce KPIs","definition":"The share of shoppers who add items to a cart but leave without buying.","formula":"1 − (completed purchases ÷ carts created).","example":"1 − (4,000 ÷ 16,000) = 75%.","benchmark":"","weakStrong":""},{"name":"Same-Store (Comparable) Sales Growth","type":"Lagging","group":"industry","category":"Retail & E-commerce KPIs","definition":"Revenue growth from stores open at least a year, stripping out new-location effects.","formula":"(Current-period comp sales − prior-period comp sales) ÷ prior-period comp sales.","example":"($10.5M − $10M) ÷ $10M = 5%.","benchmark":"","weakStrong":""},{"name":"Return Rate","type":"Lagging","group":"industry","category":"Retail & E-commerce KPIs","definition":"The proportion of sold items that customers send back.","formula":"Units returned ÷ units sold.","example":"400 ÷ 4,000 = 10%.","benchmark":"","weakStrong":""},{"name":"Customer Lifetime Value (CLV)","type":"Lagging","group":"industry","category":"Retail & E-commerce KPIs","definition":"The total gross profit expected from a customer across their entire relationship.","formula":"Average order value × purchase frequency × customer lifespan × gross margin.","example":"$85 × 4 orders/yr × 3 yrs × 50% = $510.","benchmark":"","weakStrong":""},{"name":"Foot Traffic / Sessions","type":"Leading","group":"industry","category":"Retail & E-commerce KPIs","definition":"The count of in-store visitors or online sessions reaching the channel, the top of the sales funnel.","formula":"Total store visits or website sessions in a period.","example":"160,000 sessions in a month.","benchmark":"","weakStrong":""},{"name":"Monthly Recurring Revenue (MRR)","type":"Lagging","group":"industry","category":"SaaS KPIs","definition":"The predictable subscription revenue normalized to a monthly amount.","formula":"Sum of all active monthly subscription fees (annual plans ÷ 12).","example":"1,000 customers × $200/mo = $200,000 MRR.","benchmark":"","weakStrong":""},{"name":"Annual Recurring Revenue (ARR)","type":"Lagging","group":"industry","category":"SaaS KPIs","definition":"The annualized value of recurring subscription revenue.","formula":"MRR × 12.","example":"$200,000 × 12 = $2.4M ARR.","benchmark":"","weakStrong":""},{"name":"Customer Churn Rate","type":"Lagging","group":"industry","category":"SaaS KPIs","definition":"The share of customers who cancel within a period.","formula":"Customers lost in period ÷ customers at start of period.","example":"20 ÷ 1,000 = 2% monthly.","benchmark":"","weakStrong":""},{"name":"Net Revenue Retention (NRR)","type":"Lagging","group":"industry","category":"SaaS KPIs","definition":"Revenue retained from existing customers including expansion, net of downgrades and churn.","formula":"(Starting MRR + expansion − contraction − churn) ÷ starting MRR.","example":"($200K + $30K − $8K − $12K) ÷ $200K = 105%.","benchmark":"100% NRR means expansion fully offsets churn; the strongest SaaS companies sustain 120%+, the single strongest growth signal","weakStrong":"\"Keep customers happy\" → \"Lift NRR from 105% to 115% this fiscal year, owned by the Head of CS via an expansion playbook\"."},{"name":"Customer Acquisition Cost (CAC)","type":"Leading","group":"industry","category":"SaaS KPIs","definition":"The fully loaded sales and marketing cost to acquire one new customer.","formula":"Total sales & marketing spend ÷ new customers acquired.","example":"$600,000 ÷ 100 = $6,000.","benchmark":"","weakStrong":""},{"name":"Customer Lifetime Value (LTV)","type":"Lagging","group":"industry","category":"SaaS KPIs","definition":"The total gross profit a customer generates over their entire subscription life.","formula":"(Average revenue per account × gross margin) ÷ churn rate.","example":"($2,400/yr × 80%) ÷ 0.20 = $9,600.","benchmark":"","weakStrong":""},{"name":"CAC Payback Period","type":"Leading","group":"industry","category":"SaaS KPIs","definition":"The number of months of gross profit needed to recover the cost of acquiring a customer.","formula":"CAC ÷ (monthly revenue per customer × gross margin).","example":"$6,000 ÷ ($200 × 80%) = 37.5 months.","benchmark":"under 12 months is healthy for most SaaS; under ~6 months is exceptional","weakStrong":"\"Make acquisition pay off faster\" → \"Cut CAC payback from 37 months to under 18 months by Q4, owned by the CMO via channel mix shift\"."},{"name":"Activation Rate","type":"Leading","group":"industry","category":"SaaS KPIs","definition":"The share of new users who reach a defined first-value milestone.","formula":"Users reaching activation event ÷ total new signups.","example":"650 ÷ 1,000 = 65%.","benchmark":"","weakStrong":""},{"name":"DAU/MAU Ratio","type":"Leading","group":"industry","category":"SaaS KPIs","definition":"A stickiness measure comparing daily to monthly active users.","formula":"Daily active users ÷ monthly active users.","example":"12,000 ÷ 40,000 = 30%.","benchmark":"","weakStrong":""},{"name":"Gross Margin","type":"Lagging","group":"industry","category":"SaaS KPIs","definition":"The share of revenue left after the direct cost of delivering the software service.","formula":"(Revenue − cost of revenue) ÷ revenue.","example":"($2.4M − $480K) ÷ $2.4M = 80%.","benchmark":"","weakStrong":""},{"name":"Program Efficiency Ratio","type":"Lagging","group":"industry","category":"Nonprofit KPIs","definition":"The share of total spending that goes directly to programs rather than overhead.","formula":"Program expenses ÷ total expenses.","example":"$850,000 ÷ $1,000,000 = 85%.","benchmark":"charity evaluators often look for ~65–75%+ of spend going to programs, though context matters and an extreme ratio can mean starved infrastructure","weakStrong":"\"Spend more on the mission\" → \"Raise program efficiency from 85% to 88% this fiscal year, owned by the Finance Director via overhead reduction\"."},{"name":"Fundraising ROI","type":"Lagging","group":"industry","category":"Nonprofit KPIs","definition":"The dollars raised for every dollar invested in fundraising.","formula":"Funds raised ÷ fundraising expenses.","example":"$1.2M ÷ $300,000 = $4.00.","benchmark":"","weakStrong":""},{"name":"Donor Retention Rate","type":"Lagging","group":"industry","category":"Nonprofit KPIs","definition":"The share of prior-period donors who give again in the current period.","formula":"Returning donors ÷ total donors from prior period.","example":"2,700 ÷ 6,000 = 45%.","benchmark":"average donor retention hovers around ~45%, and first-time-donor retention is far lower (~20–25%), so even small gains compound fundraising dramatically","weakStrong":"\"Keep donors giving\" → \"Lift donor retention from 45% to 55% within one year, owned by the Development Manager via a stewardship program\"."},{"name":"Cost Per Dollar Raised","type":"Lagging","group":"industry","category":"Nonprofit KPIs","definition":"The expense incurred to raise each dollar of contributions, the inverse of fundraising ROI.","formula":"Fundraising expenses ÷ funds raised.","example":"$300,000 ÷ $1.2M = $0.25.","benchmark":"","weakStrong":""},{"name":"Program Outcome Achievement","type":"Lagging","group":"industry","category":"Nonprofit KPIs","definition":"The degree to which programs hit their stated impact targets.","formula":"Outcomes achieved ÷ outcomes targeted.","example":"900 ÷ 1,000 people served = 90%.","benchmark":"","weakStrong":""},{"name":"Volunteer Retention Rate","type":"Leading","group":"industry","category":"Nonprofit KPIs","definition":"The share of volunteers who continue serving from one period to the next.","formula":"Returning volunteers ÷ total volunteers from prior period.","example":"480 ÷ 600 = 80%.","benchmark":"","weakStrong":""},{"name":"Administrative Cost Ratio","type":"Lagging","group":"industry","category":"Nonprofit KPIs","definition":"The portion of spending consumed by management and general administration.","formula":"Administrative expenses ÷ total expenses.","example":"$100,000 ÷ $1,000,000 = 10%.","benchmark":"","weakStrong":""},{"name":"Grant Success Rate","type":"Leading","group":"industry","category":"Nonprofit KPIs","definition":"The share of submitted grant applications that are awarded funding.","formula":"Grants awarded ÷ grant applications submitted.","example":"12 ÷ 40 = 30%.","benchmark":"","weakStrong":""}],"categories":{"Sales KPIs":{"group":"function","spoke":"/blog/sales-kpis"},"Marketing KPIs":{"group":"function","spoke":""},"Financial KPIs":{"group":"function","spoke":"/blog/the-financial-kpi-library"},"HR & Human Capital KPIs":{"group":"function","spoke":"/blog/human-capital-kpis-scorecard-measures"},"Operations & Supply Chain KPIs":{"group":"function","spoke":""},"Customer Service & Success KPIs":{"group":"function","spoke":""},"IT KPIs":{"group":"function","spoke":""},"Project Management KPIs":{"group":"function","spoke":"/blog/important-project-management-kpis"},"Local Government KPIs":{"group":"industry","spoke":"/blog/143-local-government-kpis-scorecard-measures"},"Healthcare KPIs":{"group":"industry","spoke":"/blog/25-healthcare-metrics-kpis"},"Higher Education KPIs":{"group":"industry","spoke":"/blog/key-performance-indicators-in-education"},"Utilities & Energy KPIs":{"group":"industry","spoke":""},"Banking & Financial Services KPIs":{"group":"industry","spoke":"/blog/bank-kpis"},"Manufacturing KPIs":{"group":"industry","spoke":""},"Retail & E-commerce KPIs":{"group":"industry","spoke":""},"SaaS KPIs":{"group":"industry","spoke":""},"Nonprofit KPIs":{"group":"industry","spoke":""}},"meta":{"count":210,"source":"ClearPoint KPI Library","updated":"2026-09-08"}}