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VC Diversity October 2015 Methodology Write-up The composite score for firms is shown here. The remainder of this document explains the methodology behind the ranking. Ranking List, Grouped by $ AUM

AUM$$$Mil. Gender$Score Ethnic$Score Age$Score

(per$Venture Gender$Divrs. Gender$Score Ethnic$Divrs. Ethnic$Score Age Avg. Composite

Firm Headcount Source) Male Female %$Women Prob.$(Pg) (1GPg)*10 White Asian Black Hispanic Other Prob.$(Pr) (1GPr)*10 Avg. Score Score

Greater$Than$$1$Billion$AUM

– 1. Social*Capital 8 $*1,155 4 4 50.0% 43% 5.7 4 4 – – – 43% 5.7 38.5 8.8 6.74– 2. Battery*Ventures 10 4,500 9 1 10.0% 80% 2.0 8 2 – – – 64% 3.6 42.1 9.8 5.10– 3. GGV*Capital 4 2,705 4 – – 100% 0.0 3 1 – – – 50% 5.0 44.8 10.0 5.00– 4. Trinity*Ventures 9 1,500 7 2 22.2% 61% 3.9 4 5 – – – 44% 5.6 51.3 5.5 4.99– 5. Kleiner*Perkins*Caufield*&*Byers 10 4,600 7 3 30.0% 53% 4.7 7 3 – – – 53% 4.7 47.7 5.5 4.95– 6. Greylock*Partners 11 3,016 10 1 9.1% 82% 1.8 7 4 – – – 49% 5.1 45.4 7.9 4.93– 7. Accel*Partners 8 7,790 8 – – 100% 0.0 5 3 – – – 46% 5.4 39.5 8.8 4.71– 8. Khosla*Ventures 8 2,263 8 – – 100% 0.0 3 5 – – – 46% 5.4 44.7 8.7 4.68– 9. Google*Ventures 12 2,000 11 1 8.3% 83% 1.7 10 1 1 – – 68% 3.2 38.0 8.9 4.58– 10.Bain*Capital*Ventures 11 3,000 11 – – 100% 0.0 6 4 – 1 – 38% 6.2 45.0 7.4 4.53– 11.Lightspeed*Venture*Partners 13 3,135 13 – – 100% 0.0 6 7 – – – 46% 5.4 42.9 8.1 4.51– 12.Charles*River*Ventures 9 1,500 8 1 11.1% 78% 2.2 7 1 – 1 – 58% 4.2 41.2 6.8 4.38– 13.Scale*Venture*Partners 7 1,200 4 3 42.9% 43% 5.7 7 – – – – 100% 0.0 46.9 7.3 4.32– 14.Softbank*Capital 10 2,596 8 2 20.0% 64% 3.6 8 2 – – – 64% 3.6 46.6 5.6 4.25– 15.Venrock 9 2,450 8 1 11.1% 78% 2.2 8 1 – – – 78% 2.2 46.8 8.2 4.21– 16.Canaan*Partners 12 3,500 9 3 25.0% 59% 4.1 10 2 – – – 70% 3.0 49.1 5.5 4.19– 17.Norwest*Venture*Partners 13 5,000 12 1 7.7% 85% 1.5 9 3 – 1 – 50% 5.0 50.8 5.9 4.16– 18.Draper*Fisher*Jurvetson 11 5,760 9 2 18.2% 67% 3.3 9 2 – – – 67% 3.3 49.7 5.6 4.04– 19.Shasta*Ventures 6 1,025 6 – – 100% 0.0 4 2 – – – 47% 5.3 48.2 6.8 4.03– 20.Foundation*Capital 9 2,782 9 – – 100% 0.0 6 3 – – – 50% 5.0 48.6 6.7 3.90– 21.DCM*Ventures 4 2,800 4 – – 100% 0.0 3 1 – – – 50% 5.0 49.3 6.3 3.77– 22.Benchmark 6 3,302 6 – – 100% 0.0 5 1 – – – 67% 3.3 44.5 7.9 3.76– 23.NEA 30 16,442 28 2 6.7% 87% 1.3 24 6 – – – 67% 3.3 48.4 6.3 3.64– 24. Institutional*Venture*Partners 8 5,400 8 – – 100% 0.0 6 2 – – – 57% 4.3 47.3 6.6 3.62– 25.General*Catalyst*Partners 11 3,000 11 – – 100% 0.0 8 3 – – – 56% 4.4 45.6 6.5 3.62– 26.Crosslink*Capital 6 1,600 6 – – 100% 0.0 4 2 – – – 47% 5.3 51.8 5.5 3.60– 27.Spark*Capital 9 1,825 9 – – 100% 0.0 8 1 – – – 78% 2.2 42.4 8.5 3.58– 28.Menlo*Ventures 11 2,000 10 1 9.1% 82% 1.8 9 2 – – – 67% 3.3 51.1 5.5 3.53– 29.Tiger*Global*Management 3 10,000 3 – – 100% 0.0 3 – – – – 100% 0.0 37.7 10.0 3.33– 30.Sequoia*Capital 14 4,470 14 – – 100% 0.0 12 2 – – – 74% 2.6 46.0 6.8 3.16– 31.Founders*Fund 6 2,160 6 – – 100% 0.0 6 – – – – 100% 0.0 38.2 9.4 3.13– 32.Mayfield*Fund 5 3,000 5 – – 100% 0.0 – 5 – – – 100% 0.0 43.4 9.3 3.10– 33.FirstMark*Capital 14 2,200 14 – – 100% 0.0 13 1 – – – 86% 1.4 45.7 7.8 3.09– 34.Redpoint*Ventures 13 3,800 13 – – 100% 0.0 11 2 – – – 72% 2.8 46.3 6.3 3.05– 35. Index*Ventures 3 3,733 3 – – 100% 0.0 3 – – – – 100% 0.0 42.0 8.9 2.98– 36.Foundry*Group 4 1,128 4 – – 100% 0.0 4 – – – – 100% 0.0 46.0 8.5 2.84– 37. Andreessen*Horowitz 16 4,289 15 1 6.3% 88% 1.3 15 1 – – – 88% 1.3 50.0 6.1 2.85– 38.US*Venture*Partners 6 1,225 5 1 16.7% 67% 3.3 6 – – – – 100% 0.0 50.3 4.9 2.74– 39.Matrix*Partners 9 5,050 9 – – 100% 0.0 8 – – 1 – 78% 2.2 49.2 6.0 2.73– 40.August*Capital 7 1,300 7 – – 100% 0.0 6 1 – – – 71% 2.9 51.0 4.9 2.59– 41.Tenaya*Capital 5 1,487 5 – – 100% 0.0 5 – – – – 100% 0.0 47.0 7.3 2.43– 42.Bessemer*Venture*Partners 13 5,600 13 – – 100% 0.0 13 – – – – 100% 0.0 45.0 7.0 2.33– 43.Meritech*Capital*Partners 6 2,064 6 – – 100% 0.0 6 – – – – 100% 0.0 45.8 6.3 2.09– 44.Atlas*Life*Sciences 5 2,545 5 – – 100% 0.0 5 – – – – 100% 0.0 51.0 6.1 2.02– 45.Madrona*Venture*Group 6 1,300 6 – – 100% 0.0 6 – – – – 100% 0.0 53.8 5.4 1.79– 46.Bluerun*Ventures 2 1,065 2 – – 100% 0.0 2 – – – – 100% 0.0 53.0 3.9 1.29

$250$Million$to$$1$Billion

– 1. Y*Combinator 11 1,000 10 1 9.1% 82% 1.8 6 4 1 – – 38% 6.2 36.4 8.1 5.35– 2. Formation*8 10 948 9 1 10.0% 80% 2.0 6 4 – – – 47% 5.3 34.6 7.2 4.84– 3. Upfront*Ventures 6 658 5 1 16.7% 67% 3.3 5 – 1 – – 67% 3.3 47.3 7.3 4.65– 4. True*Ventures 7 890 7 – – 100% 0.0 4 3 – – – 43% 5.7 47.0 7.9 4.54– 5. Iconiq*Capital 5 528 5 – – 100% 0.0 4 1 – – – 60% 4.0 40.8 9.4 4.46– 6. Thrive*Capital 6 597 6 – – 100% 0.0 3 3 – – – 40% 6.0 32.5 7.3 4.44– 7. Emergence*Capital 7 575 6 1 14.3% 71% 2.9 6 – – 1 – 71% 2.9 47.6 6.6 4.12– 8. Storm*Ventures 6 825 6 – – 100% 0.0 2 3 – 1 – 27% 7.3 53.2 4.8 4.05– 9. Greycroft*Partners 9 593 8 1 11.1% 78% 2.2 9 – – – – 100% 0.0 47.6 7.8 3.35– 10.RRE*Ventures 6 810 6 – – 100% 0.0 5 1 – – – 67% 3.3 54.2 5.6 2.97– 11.First*Round*Capital 7 748 7 – – 100% 0.0 7 – – – – 100% 0.0 47.4 7.2 2.38– 12.Pelion*Venture*Partners 5 610 5 – – 100% 0.0 5 – – – – 100% 0.0 47.6 7.1 2.38– 13.Sutter*Hill*Ventures 7 700 7 – – 100% 0.0 7 – – – – 100% 0.0 49.3 6.2 2.06– 14.Union*Square*Ventures 5 883 5 – – 100% 0.0 5 – – – – 100% 0.0 52.8 4.6 1.53

$250$Million$and$Less

– 1. Floodgate 2 224 1 1 50.0% – 10.0 1 1 – – – – 10.0 42.5 9.3 9.78– 2. Cowboy*Ventures 2 97 1 1 50.0% – 10.0 1 1 – – – – 10.0 39.0 9.2 9.74– 3. Felicis*Ventures 4 245 3 1 25.0% 50% 5.0 2 2 – – – 33% 6.7 38.8 10.0 7.22– 4. Aspect*Ventures 2 150 – 2 100.0% 100% 0.0 1 1 – – – – 10.0 48.0 7.6 5.87– 5. SoftTech*VC 3 155 3 – – 100% 0.0 2 – 1 – – 33% 6.7 40.3 9.6 5.41– 6. Ribbit*Capital 3 224 3 – – 100% 0.0 2 – – 1 – 33% 6.7 39.7 9.2 5.30– 7. Canvas*Venture*Fund 5 175 4 1 20.0% 60% 4.0 4 1 – – – 60% 4.0 51.6 5.7 4.58– 8. Lowercase*Capital 2 30 2 – – 100% 0.0 2 – – – – 100% 0.0 36.0 8.8 2.95– 9. Accomplice*VC 7 200 7 – – 100% 0.0 7 – – – – 100% 0.0 45.4 6.9 2.29– 10.SV*Angel 5 100 5 – – 100% 0.0 5 – – – – 100% 0.0 37.8 5.7 1.91– 11.Blumberg*Capital 2 240 2 – – 100% 0.0 2 – – – – 100% 0.0 52.0 4.8 1.61

Total 546 $$166,467 505 41 7.5% 86% 1.4 425 110 4 7 – 65% 3.5 45.9 7.0 3.98

 

 

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Ranking List, Grouped by Headcount of Senior Investment Team Members

AUM$$$Mil. Gender$Score Ethnic$Score Age$Score

(per$Venture Gender$Divrs. Gender$Score Ethnic$Divrs. Ethnic$Score Age Avg. Composite

Firm Headcount Source) Male Female %$Women Prob.$(Pg) (1GPg)*10 White Asian Black Hispanic Other Prob.$(Pr) (1GPr)*10 Avg. Score Score

Greater$than$10$People

– 1. Y%Combinator 11 $%1,000 10 1 9.1% 82% 1.8 6 4 1 – – 38% 6.2 36.4 8.1 5.35– 2. Greylock%Partners 11 3,016 10 1 9.1% 82% 1.8 7 4 – – – 49% 5.1 45.4 7.9 4.93– 3. Google%Ventures 12 2,000 11 1 8.3% 83% 1.7 10 1 1 – – 68% 3.2 38.0 8.9 4.58– 4. Bain%Capital%Ventures 11 3,000 11 – – 100% 0.0 6 4 – 1 – 38% 6.2 45.0 7.4 4.53– 5. Lightspeed%Venture%Partners 13 3,135 13 – – 100% 0.0 6 7 – – – 46% 5.4 42.9 8.1 4.51– 6. Canaan%Partners 12 3,500 9 3 25.0% 59% 4.1 10 2 – – – 70% 3.0 49.1 5.5 4.19– 7. Norwest%Venture%Partners 13 5,000 12 1 7.7% 85% 1.5 9 3 – 1 – 50% 5.0 50.8 5.9 4.16– 8. Draper%Fisher%Jurvetson 11 5,760 9 2 18.2% 67% 3.3 9 2 – – – 67% 3.3 49.7 5.6 4.04– 9. NEA 30 16,442 28 2 6.7% 87% 1.3 24 6 – – – 67% 3.3 48.4 6.3 3.64– 10.General%Catalyst%Partners 11 3,000 11 – – 100% 0.0 8 3 – – – 56% 4.4 45.6 6.5 3.62– 11.Menlo%Ventures 11 2,000 10 1 9.1% 82% 1.8 9 2 – – – 67% 3.3 51.1 5.5 3.53– 12.Sequoia%Capital 14 4,470 14 – – 100% 0.0 12 2 – – – 74% 2.6 46.0 6.8 3.16– 13.FirstMark%Capital 14 2,200 14 – – 100% 0.0 13 1 – – – 86% 1.4 45.7 7.8 3.09– 14.Redpoint%Ventures 13 3,800 13 – – 100% 0.0 11 2 – – – 72% 2.8 46.3 6.3 3.05– 15.Andreessen%Horowitz 16 4,289 15 1 6.3% 88% 1.3 15 1 – – – 88% 1.3 50.0 6.1 2.85– 16.Bessemer%Venture%Partners 13 5,600 13 – – 100% 0.0 13 – – – – 100% 0.0 45.0 7.0 2.33

6$to$10$People

– 1. Social%Capital 8 1,155 4 4 50.0% 43% 5.7 4 4 – – – 43% 5.7 38.5 8.8 6.74– 2. Battery%Ventures 10 4,500 9 1 10.0% 80% 2.0 8 2 – – – 64% 3.6 42.1 9.8 5.10– 3. Trinity%Ventures 9 1,500 7 2 22.2% 61% 3.9 4 5 – – – 44% 5.6 51.3 5.5 4.99– 4. Kleiner%Perkins%Caufield%&%Byers 10 4,600 7 3 30.0% 53% 4.7 7 3 – – – 53% 4.7 47.7 5.5 4.95– 5. Formation%8 10 948 9 1 10.0% 80% 2.0 6 4 – – – 47% 5.3 34.6 7.2 4.84– 6. Accel%Partners 8 7,790 8 – – 100% 0.0 5 3 – – – 46% 5.4 39.5 8.8 4.71– 7. Khosla%Ventures 8 2,263 8 – – 100% 0.0 3 5 – – – 46% 5.4 44.7 8.7 4.68– 8. Upfront%Ventures 6 658 5 1 16.7% 67% 3.3 5 – 1 – – 67% 3.3 47.3 7.3 4.65– 9. True%Ventures 7 890 7 – – 100% 0.0 4 3 – – – 43% 5.7 47.0 7.9 4.54– 10.Scale%Venture%Partners 7 1,200 4 3 42.9% 43% 5.7 7 – – – – 100% 0.0 46.7 7.7 4.48– 11.Thrive%Capital 6 597 6 – – 100% 0.0 3 3 – – – 40% 6.0 32.5 7.3 4.44– 12.Charles%River%Ventures 9 1,500 8 1 11.1% 78% 2.2 7 1 – 1 – 58% 4.2 41.2 6.8 4.38– 13.Softbank%Capital 10 2,596 8 2 20.0% 64% 3.6 8 2 – – – 64% 3.6 46.6 5.6 4.25– 14.Emergence%Capital 7 575 6 1 14.3% 71% 2.9 6 – – 1 – 71% 2.9 47.6 6.6 4.12– 15.Storm%Ventures 6 825 6 – – 100% 0.0 2 3 – 1 – 27% 7.3 53.2 4.8 4.05– 16.Shasta%Ventures 6 1,025 6 – – 100% 0.0 4 2 – – – 47% 5.3 48.2 6.8 4.03– 17.Venrock 9 2,450 8 1 11.1% 78% 2.2 8 1 – – – 78% 2.2 47.9 7.5 3.99– 18.Foundation%Capital 9 2,782 9 – – 100% 0.0 6 3 – – – 50% 5.0 48.6 6.7 3.90– 19.Benchmark 6 3,302 6 – – 100% 0.0 5 1 – – – 67% 3.3 44.5 7.9 3.76– 20. Institutional%Venture%Partners 8 5,400 8 – – 100% 0.0 6 2 – – – 57% 4.3 47.3 6.6 3.62– 21.Crosslink%Capital 6 1,600 6 – – 100% 0.0 4 2 – – – 47% 5.3 51.8 5.5 3.60– 22.Spark%Capital 9 1,825 9 – – 100% 0.0 8 1 – – – 78% 2.2 42.4 8.5 3.58– 23.Greycroft%Partners 9 593 8 1 11.1% 78% 2.2 9 – – – – 100% 0.0 47.6 7.8 3.35– 24.Founders%Fund 6 2,160 6 – – 100% 0.0 6 – – – – 100% 0.0 38.2 9.4 3.13– 25.RRE%Ventures 6 810 6 – – 100% 0.0 5 1 – – – 67% 3.3 54.2 5.6 2.97– 26.US%Venture%Partners 6 1,225 5 1 16.7% 67% 3.3 6 – – – – 100% 0.0 50.3 4.9 2.74– 27.Matrix%Partners 9 5,050 9 – – 100% 0.0 8 – – 1 – 78% 2.2 49.2 6.0 2.73– 28.August%Capital 7 1,300 7 – – 100% 0.0 6 1 – – – 71% 2.9 51.0 4.9 2.59– 29.First%Round%Capital 7 748 7 – – 100% 0.0 7 – – – – 100% 0.0 47.4 7.2 2.38– 30.Accomplice%VC 7 200 7 – – 100% 0.0 7 – – – – 100% 0.0 45.4 6.9 2.29– 31. Meritech%Capital%Partners 6 2,064 6 – – 100% 0.0 6 – – – – 100% 0.0 45.8 6.3 2.09– 32.Sutter%Hill%Ventures 7 700 7 – – 100% 0.0 7 – – – – 100% 0.0 49.3 6.2 2.06– 33.Madrona%Venture%Group 6 1,300 6 – – 100% 0.0 6 – – – – 100% 0.0 53.8 5.4 1.79

5$or$Less$People

– 1. Floodgate 2 224 1 1 50.0% – 10.0 1 1 – – – – 10.0 42.5 9.3 9.78– 2. Cowboy%Ventures 2 97 1 1 50.0% – 10.0 1 1 – – – – 10.0 39.0 9.2 9.74– 3. Felicis%Ventures 4 245 3 1 25.0% 50% 5.0 2 2 – – – 33% 6.7 38.8 10.0 7.22– 4. Aspect%Ventures 2 150 – 2 100.0% 100% 0.0 1 1 – – – – 10.0 48.0 7.6 5.87– 5. SoftTech%VC 3 155 3 – – 100% 0.0 2 – 1 – – 33% 6.7 40.3 9.6 5.41– 6. Ribbit%Capital 3 224 3 – – 100% 0.0 2 – – 1 – 33% 6.7 39.7 9.2 5.30– 7. GGV%Capital 4 2,705 4 – – 100% 0.0 3 1 – – – 50% 5.0 44.8 10.0 5.00– 8. Canvas%Venture%Fund 5 175 4 1 20.0% 60% 4.0 4 1 – – – 60% 4.0 51.6 5.7 4.58– 9. Iconiq%Capital 5 528 5 – – 100% 0.0 4 1 – – – 60% 4.0 40.8 9.4 4.46– 10.DCM%Ventures 4 2,800 4 – – 100% 0.0 3 1 – – – 50% 5.0 49.3 6.3 3.77– 11.Tiger%Global%Management 3 10,000 3 – – 100% 0.0 3 – – – – 100% 0.0 37.7 10.0 3.33– 12.Mayfield%Fund 5 3,000 5 – – 100% 0.0 – 5 – – – 100% 0.0 43.4 9.3 3.10– 13. Index%Ventures 3 3,733 3 – – 100% 0.0 3 – – – – 100% 0.0 42.0 8.9 2.98– 14.Lowercase%Capital 2 30 2 – – 100% 0.0 2 – – – – 100% 0.0 36.0 8.8 2.95– 15.Foundry%Group 4 1,128 4 – – 100% 0.0 4 – – – – 100% 0.0 46.0 8.5 2.84– 16.Tenaya%Capital 5 1,487 5 – – 100% 0.0 5 – – – – 100% 0.0 47.0 7.3 2.43– 17.Pelion%Venture%Partners 5 610 5 – – 100% 0.0 5 – – – – 100% 0.0 47.6 7.1 2.38– 18.Atlas%Life%Sciences 5 2,545 5 – – 100% 0.0 5 – – – – 100% 0.0 51.0 6.1 2.02– 19.SV%Angel 5 100 5 – – 100% 0.0 5 – – – – 100% 0.0 37.8 5.7 1.91– 20.Blumberg%Capital 2 240 2 – – 100% 0.0 2 – – – – 100% 0.0 52.0 4.8 1.61– 21.Union%Square%Ventures 5 883 5 – – 100% 0.0 5 – – – – 100% 0.0 52.8 4.6 1.53– 22.Bluerun%Ventures 2 1,065 2 – – 100% 0.0 2 – – – – 100% 0.0 53.0 3.9 1.29

Total 546 $$166,467 505 41 7.5% 86% 1.4 425 110 4 7 – 65% 3.5 45.9 7.0 3.98

 

 

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Ranking List Overall of Senior Investment Team Members

AUM$$$Mil. Gender$Score Ethnic$Score Age$Score

(per$Venture Gender$Divrs. Gender$Score Ethnic$Divrs. Ethnic$Score Age Avg. Composite

Firm Headcount Source) Male Female %$Women Prob.$(Pg) (1GPg)*10 White Asian Black Hispanic Other Prob.$(Pr) (1GPr)*10 Avg. Score Score

Overall$Scores

– 1. Floodgate 2 $.224 1 1 50.0% – 10.0 1 1 – – – – 10.0 42.5 9.3 9.78– 2. Cowboy.Ventures 2 97 1 1 50.0% – 10.0 1 1 – – – – 10.0 39.0 9.2 9.74– 3. Felicis.Ventures 4 245 3 1 25.0% 50% 5.0 2 2 – – – 33% 6.7 38.8 10.0 7.22– 4. Social.Capital 8 1,155 4 4 50.0% 43% 5.7 4 4 – – – 43% 5.7 38.5 8.8 6.74– 5. Aspect.Ventures 2 150 – 2 100.0% 100% 0.0 1 1 – – – – 10.0 48.0 7.6 5.87– 6. SoftTech.VC 3 155 3 – – 100% 0.0 2 – 1 – – 33% 6.7 40.3 9.6 5.41– 7. Y.Combinator 11 1,000 10 1 9.1% 82% 1.8 6 4 1 – – 38% 6.2 36.4 8.1 5.35– 8. Ribbit.Capital 3 224 3 – – 100% 0.0 2 – – 1 – 33% 6.7 39.7 9.2 5.30– 9. Battery.Ventures 10 4,500 9 1 10.0% 80% 2.0 8 2 – – – 64% 3.6 42.1 9.8 5.10– 10. GGV.Capital 4 2,705 4 – – 100% 0.0 3 1 – – – 50% 5.0 44.8 10.0 5.00– 11. Trinity.Ventures 9 1,500 7 2 22.2% 61% 3.9 4 5 – – – 44% 5.6 51.3 5.5 4.99– 12. Kleiner.Perkins.Caufield.&.Byers 10 4,600 7 3 30.0% 53% 4.7 7 3 – – – 53% 4.7 47.7 5.5 4.95– 13. Greylock.Partners 11 3,016 10 1 9.1% 82% 1.8 7 4 – – – 49% 5.1 45.4 7.9 4.93– 14. Formation.8 10 948 9 1 10.0% 80% 2.0 6 4 – – – 47% 5.3 34.6 7.2 4.84– 15. Accel.Partners 8 7,790 8 – – 100% 0.0 5 3 – – – 46% 5.4 39.5 8.8 4.71– 16. Khosla.Ventures 8 2,263 8 – – 100% 0.0 3 5 – – – 46% 5.4 44.7 8.7 4.68– 17. Upfront.Ventures 6 658 5 1 16.7% 67% 3.3 5 – 1 – – 67% 3.3 47.3 7.3 4.65– 18. Google.Ventures 12 2,000 11 1 8.3% 83% 1.7 10 1 1 – – 68% 3.2 38.0 8.9 4.58– 19. Canvas.Venture.Fund 5 175 4 1 20.0% 60% 4.0 4 1 – – – 60% 4.0 51.6 5.7 4.58– 20. True.Ventures 7 890 7 – – 100% 0.0 4 3 – – – 43% 5.7 47.0 7.9 4.54– 21. Bain.Capital.Ventures 11 3,000 11 – – 100% 0.0 6 4 – 1 – 38% 6.2 45.0 7.4 4.53– 22. Lightspeed.Venture.Partners 13 3,135 13 – – 100% 0.0 6 7 – – – 46% 5.4 42.9 8.1 4.51– 23. Scale.Venture.Partners 7 1,200 4 3 42.9% 43% 5.7 7 – – – – 100% 0.0 46.7 7.7 4.48– 24. Iconiq.Capital 5 528 5 – – 100% 0.0 4 1 – – – 60% 4.0 40.8 9.4 4.46– 25. Thrive.Capital 6 597 6 – – 100% 0.0 3 3 – – – 40% 6.0 32.5 7.3 4.44– 26. Charles.River.Ventures 9 1,500 8 1 11.1% 78% 2.2 7 1 – 1 – 58% 4.2 41.2 6.8 4.38– 27. Softbank.Capital 10 2,596 8 2 20.0% 64% 3.6 8 2 – – – 64% 3.6 46.6 5.6 4.25– 28. Canaan.Partners 12 3,500 9 3 25.0% 59% 4.1 10 2 – – – 70% 3.0 49.1 5.5 4.19– 29. Norwest.Venture.Partners 13 5,000 12 1 7.7% 85% 1.5 9 3 – 1 – 50% 5.0 50.8 5.9 4.16– 30. Emergence.Capital 7 575 6 1 14.3% 71% 2.9 6 – – 1 – 71% 2.9 47.6 6.6 4.12– 31. Storm.Ventures 6 825 6 – – 100% 0.0 2 3 – 1 – 27% 7.3 53.2 4.8 4.05– 32. Draper.Fisher.Jurvetson 11 5,760 9 2 18.2% 67% 3.3 9 2 – – – 67% 3.3 49.7 5.6 4.04– 33. Shasta.Ventures 6 1,025 6 – – 100% 0.0 4 2 – – – 47% 5.3 48.2 6.8 4.03– 34. Venrock 9 2,450 8 1 11.1% 78% 2.2 8 1 – – – 78% 2.2 47.9 7.5 3.99– 35. Foundation.Capital 9 2,782 9 – – 100% 0.0 6 3 – – – 50% 5.0 48.6 6.7 3.90– 36. DCM.Ventures 4 2,800 4 – – 100% 0.0 3 1 – – – 50% 5.0 49.3 6.3 3.77– 37. Benchmark 6 3,302 6 – – 100% 0.0 5 1 – – – 67% 3.3 44.5 7.9 3.76– 38. NEA 30 16,442 28 2 6.7% 87% 1.3 24 6 – – – 67% 3.3 48.4 6.3 3.64– 39. Institutional.Venture.Partners 8 5,400 8 – – 100% 0.0 6 2 – – – 57% 4.3 47.3 6.6 3.62– 40. General.Catalyst.Partners 11 3,000 11 – – 100% 0.0 8 3 – – – 56% 4.4 45.6 6.5 3.62– 41. Crosslink.Capital 6 1,600 6 – – 100% 0.0 4 2 – – – 47% 5.3 51.8 5.5 3.60– 42. Spark.Capital 9 1,825 9 – – 100% 0.0 8 1 – – – 78% 2.2 42.4 8.5 3.58– 43. Menlo.Ventures 11 2,000 10 1 9.1% 82% 1.8 9 2 – – – 67% 3.3 51.1 5.5 3.53– 44. Greycroft.Partners 9 593 8 1 11.1% 78% 2.2 9 – – – – 100% 0.0 47.6 7.8 3.35– 45. Tiger.Global.Management 3 10,000 3 – – 100% 0.0 3 – – – – 100% 0.0 37.7 10.0 3.33– 46. Sequoia.Capital 14 4,470 14 – – 100% 0.0 12 2 – – – 74% 2.6 46.0 6.8 3.16– 47. Founders.Fund 6 2,160 6 – – 100% 0.0 6 – – – – 100% 0.0 38.2 9.4 3.13– 48. Mayfield.Fund 5 3,000 5 – – 100% 0.0 – 5 – – – 100% 0.0 43.4 9.3 3.10– 49. FirstMark.Capital 14 2,200 14 – – 100% 0.0 13 1 – – – 86% 1.4 45.7 7.8 3.09– 50. Redpoint.Ventures 13 3,800 13 – – 100% 0.0 11 2 – – – 72% 2.8 46.3 6.3 3.05– 51. Index.Ventures 3 3,733 3 – – 100% 0.0 3 – – – – 100% 0.0 42.0 8.9 2.98– 52. RRE.Ventures 6 810 6 – – 100% 0.0 5 1 – – – 67% 3.3 54.2 5.6 2.97– 53. Lowercase.Capital 2 30 2 – – 100% 0.0 2 – – – – 100% 0.0 36.0 8.8 2.95– 54. Andreessen.Horowitz 16 4,289 15 1 6.3% 88% 1.3 15 1 – – – 88% 1.3 50.0 6.1 2.85– 55. Foundry.Group 4 1,128 4 – – 100% 0.0 4 – – – – 100% 0.0 46.0 8.5 2.84– 56. US.Venture.Partners 6 1,225 5 1 16.7% 67% 3.3 6 – – – – 100% 0.0 50.3 4.9 2.74– 57. Matrix.Partners 9 5,050 9 – – 100% 0.0 8 – – 1 – 78% 2.2 49.2 6.0 2.73– 58. August.Capital 7 1,300 7 – – 100% 0.0 6 1 – – – 71% 2.9 51.0 4.9 2.59– 59. Tenaya.Capital 5 1,487 5 – – 100% 0.0 5 – – – – 100% 0.0 47.0 7.3 2.43– 60. First.Round.Capital 7 748 7 – – 100% 0.0 7 – – – – 100% 0.0 47.4 7.2 2.38– 61. Pelion.Venture.Partners 5 610 5 – – 100% 0.0 5 – – – – 100% 0.0 47.6 7.1 2.38– 62. Bessemer.Venture.Partners 13 5,600 13 – – 100% 0.0 13 – – – – 100% 0.0 45.0 7.0 2.33– 63. Accomplice.VC 7 200 7 – – 100% 0.0 7 – – – – 100% 0.0 45.4 6.9 2.29– 64. Meritech.Capital.Partners 6 2,064 6 – – 100% 0.0 6 – – – – 100% 0.0 45.8 6.3 2.09– 65. Sutter.Hill.Ventures 7 700 7 – – 100% 0.0 7 – – – – 100% 0.0 49.3 6.2 2.06– 66. Atlas.Life.Sciences 5 2,545 5 – – 100% 0.0 5 – – – – 100% 0.0 51.0 6.1 2.02– 67. SV.Angel 5 100 5 – – 100% 0.0 5 – – – – 100% 0.0 37.8 5.7 1.91– 68. Madrona.Venture.Group 6 1,300 6 – – 100% 0.0 6 – – – – 100% 0.0 53.8 5.4 1.79– 69. Blumberg.Capital 2 240 2 – – 100% 0.0 2 – – – – 100% 0.0 52.0 4.8 1.61– 70. Union.Square.Ventures 5 883 5 – – 100% 0.0 5 – – – – 100% 0.0 52.8 4.6 1.53– 71. Bluerun.Ventures 2 1,065 2 – – 100% 0.0 2 – – – – 100% 0.0 53.0 3.9 1.29

Total 546 $$166,467 505 41 7.5% 86% 1.4 425 110 4 7 – 65% 3.5 45.9 7.0 3.98

%"of"total 92.5% 7.5% 77.8% 20.1% 0.7% 1.3% –

 

 

  4

This methodology walk-through addresses the following areas: (i)   Firm selection (ii)   People selection (iii)   Demographic variable estimation (iv)   Ranking methodology (v)   Appendix: Supplementary schedules are included at the end

I. Firm Selection To compose a study of VC demographics, we wanted to select a representative number of funds with the following characteristics:

(i)   Firms based in the US: We are focusing on the diversity decisions of US firms, so international firms were excluded

(ii)   Traditional technology VC firms: We are focused on VC firms that invest mainly in technology-related startups; notably this excludes biomedical / life science-focused VC firms or firms (though we include life sciences team members if within a broader fund); we oriented around firms that have a Series A / Series B practice but included any investors in growth stage products if broken out (e.g. DFJ, Sequoia)

(iii)   Largest Firms: Using a combination of VentureSource and Mattermark, we force-ranked VC firms by AUM and only looked at funds above $275M of AUM – we wanted to capture the firms which on a $ capital basis represented a sizable portion of the market.

(iv)   Active Firms: We did not include any firms that are less active which we estimated as either not having raised a new fund in the last 5 years or that were not building their portfolio with new investments; this was based on public signals or VentureSource

(v)   High Mindshare: We included certain firms that commanded a high mindshare score from Mattermark to the extent they weren’t already included (e.g. if below $275M AUM)

This resulted in a list of 71 firms representing over $160B in AUM, per VentureSource (see p. 1). We consider this a starting point and can add additional peer firms as time goes on. II. People Selection For each of the firms, we wanted to measure the diversity of the “investment team leadership”. We are defining “investment team leadership” as anyone holding the title of General Partner, Partner, Managing Director, and any other variation of the senior investment titles on the investment team. We also include active Venture Partners and Board Partners to the extent they are actively involved on the investment team. For A16Z, KPCB, Sequoia and Y-Combinator who designate all their team members as “Partner”, we approximated the leadership team based on tenure, experience, leading deals and taking board seats. We do not include any junior investment team members (e.g. Associates, Vice Presidents or Principals) or other teams (operating or growth teams, finance team, or other non-investment team functions). We also excluded people based in international offices of US VC firms as we are focusing on team diversity within the US. This gave us a list of 546 investment team leaders across the 71 firms. There are a few reasons to focus on “investment team leaders”:

(i)   Leaders drive the direction of the firm: These individuals most directly make decisions that affect the direction of the firm, have investment-decision power and represent the firm on boards

(ii)   Total would paint a different picture: People have already caught on that the few women hired in VC tend to be hired in non-senior positions and/or non-investment team roles1; Appendix 1 has our results on this disparity

(iii)   Data is stable and consistent: Firms more consistently disclose the leaders on the website versus other team members, so data availability is an issue for a total view. In addition, turnover is significantly higher at the junior level, even on the investment team, as firms have different policies (e.g. 2-year programs).

III. Demographic Variable Estimation For each of the individuals, we measured the following:

(i)   Gender (ii)   Race / Ethnicity: We used the same definitions as the 2010 US census, which the large public tech firms also

follow in their diversity monitoring. Categories are the following:

                                                                                                               1 CNBC (http://www.cnbc.com/2015/03/27/waiting-for-pao-verdict-where-are-women-at-top-vc-funds.html); Fortune (http://fortune.com/2014/02/06/venture-capitals-stunning-lack-of-female-decision-makers/)

 

  5

a.   “White” refers to a person having origins in any of the original peoples of Europe, the Middle East, or North Africa

b.   “Black or African American” refers to a person having origins in any of the Black racial groups of Africa c.   “Asian” refers to a person having origins in any of the original peoples of the Far East, Southeast Asia, or

the Indian subcontinent d.   “Hispanic” refers to people who identify their origin as Hispanic, Latino or Spanish e.   “Other” includes Native Hawaiian, Other Pacific Islander, American Indian or Alaskan Native

(iii)   Age: We calculated age based on publicly available date-of-birth information. In instances where the date-of-birth wasn’t available, we estimated age with LinkedIn by taking high school graduation year minus 18 or college graduation year minus 22 and used 6/30 as the month/day. NOTE: We were only able to find a data point for age for 532 individuals (97% of total).

IV. Ranking Methodology The ranking methodology combines 3 variables:

(i)   A gender diversity score (ii)   A race diversity score (iii)   An age score

For the gender diversity score and the ethnic diversity score, we use a diversity index based on probability to measure the degree of concentration when individuals are classified into types. Simply stated, we create a diversity score based on the probability that two investment team leaders taken at random from a VC firm will represent the same type. This approach uses the same principal as the Simpson index (ecology) and Herfindahl index (economics)2 and has already been used in population diversity studies3. Gender Diversity Score The gender diversity score is calculated using the probability that any two individuals selected at random will be the same gender. This is calculated as follows:

𝑃" =  1

𝑁(𝑁 − 1)× 𝑀 𝑀 − 1 +𝑊 𝑊 − 1

Pg = probability that two people randomly selected are the same (i.e. randomly select two men or two women) N = total senior investment team members at a firm M = number of men W = number of women Therefore, for a firm with 2 men and 2 women, the probability of randomly picking two people that are the same is:

𝑃" =  1

4(4 − 1)× 2 2 − 1 + 2 2 − 1 = 33.3%

The gender score is simply 1 – this calculated probability, multiplied by 10 (for a scale of 0 to 10), or in the above example, 6.7.

𝐺𝑒𝑛𝑑𝑒𝑟  𝐷𝑖𝑣𝑒𝑟𝑠𝑖𝑡𝑦  𝑆𝑐𝑜𝑟𝑒 = 1 − 𝑃" ×10 The benefit of this methodology is that absolute diversity (i.e. agnostic to gender) is valued. In other words, a firm with only men will receive a probability of picking 2 people at random that are the same of 100% which would translate into a gender score of 0, but a firm with only women would also receive a gender score of 0. The higher the score, the better the diversity profile. Ethnic Diversity Score The ethnicity score is based on the same principle as the gender score, only expanded to all the racial/ethnic categories: White, Asian, Black, Latino/Hispanic, Other.

𝑃B =  1

𝑁(𝑁 − 1)× 𝑊 𝑊 − 1 + 𝐴 𝐴 − 1 + 𝐵 𝐵 − 1 + 𝐻 𝐻 − 1 + 𝑂 𝑂 − 1

                                                                                                               2 Diversity Index: https://en.wikipedia.org/wiki/Diversity_index#Simpson_index 3 USAToday: http://usatoday30.usatoday.com/news/nation/census/county-by-county-diversity.htm  

 

  6

Pr = probability that two people randomly selected are the same (e.g. randomly select two While individuals) N = total senior investment team members W = number of White individuals A = number of Asian individuals B = number of Black individuals H = number of Latino/Hispanic individuals O = number of individuals with racial/ethnic category of “Other” In this case, the ethnic diversity score is also 1 – this calculated probability, multiplied by 10 (for a scale of 0 to 10).

𝐸𝑡ℎ𝑛𝑖𝑐  𝐷𝑖𝑣𝑒𝑟𝑠𝑖𝑡𝑦  𝑆𝑐𝑜𝑟𝑒 = 1 − 𝑃" ×10 Below is an example of the Ethnic Diversity Score across a hypothetical 10 person firm with varying allocations.

W A B H O N Pr Score 2 2 2 2 2 10 11% 8.9 4 2 2 2 0 10 20% 8.0 6 2 2 0 0 10 38% 6.2 8 2 0 0 0 10 64% 3.6

10 0 0 0 0 10 100% 0 Note that while the 1st orientation has a perfectly equal balance, there is always some chance that the two randomly selected individuals will be the same (resulting in a score of 8.9 instead of intuitively a ‘perfect’ score); this is not an issue because for similarly-sized firms, the score will still be better than the less diverse firms with similar headcount. For this reason we have attempted to create sub-lists based on size (discussed below). Age Score The Age Score assigns a value to each senior investment team member based on his/her age. To figure out what ages receive a perfect score, we looked at how old partners who did the best deals were when they invested in those deals’ Series A or Series B, the earliest venture rounds where product-market fit is not readily apparent. To do this, we looked at VentureSource’s list of top venture outcomes (defined as largest exits via M&A or IPO of VC-backed companies) and compiled a list of all the partners who led the rounds in the corresponding Series A and/or B of these outcomes. The results can be seen in the cumulative distribution function (CDF) below and the table with deals used can be seen in Appendix 3.

Looking at this chart, 60% of the Series A’s and B’s of the largest exists were done by partners between the age of 35 and 46 (20% and 80%, respectively).

–

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

CDF  of  Ages  @  Series  A/B  of  Best  Deals

20%:  35  yrs

80%:  46  yrs

Median:  41

 

  7

For the age score, we assigned any individual with the age between 35 and 46 to a perfect score of 10. Before 35 (to a minimum of 22) and after 46 (to a maximum of 65) a decreased score was given. In order to give more “future credit” to those younger than 35, we decreased the scores below 35 linearly and after 46 exponentially (i.e. a score 1 year outside the alley on the low end, 34, will be higher than the score 1 year outside the alley on the high end, 47). A firm’s age score is simply the average of the age scores of the individuals.

The argument for considering age is that younger partners are:

(i)   More likely to be connected to newer technology (ii)   More likely to be connected to younger founders (iii)   More likely to be hungrier in their career

Note that this is purely conjecture to explain the data. Composite Score: The Composite Score is the simple average between the Gender Diversity Score, Ethnic Diversity Score and the Age Score. Calculating the composite score this way reflects the position that gender, ethnicity and age are equally relevant variables in evaluating a fund’s future relevance. Ultimately when comparing firms, we also grouped firms of similar size together and considered two approaches to do so, presented on the first two pages of this document:

(i)   By AUM: a.   Funds up to $250M AUM b.   Funds from $251M to $1.0B AUM c.   Funds with greater than $1.0B AUM

(ii)   By Headcount of “senior investment team” members: a.   Funds with 5 people or less b.   Funds with 6-10 people c.   Funds with over 10 people

We submitted data points to firms in a request for comment to allow firms the ability to fact check the information.

–

2.0

4.0

6.0

8.0

10.0

22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65

Score  Ascribed  to  Each  Age

 

  8

Appendix 1: Investment Team Leadership vs. Full Team The first three bars are based on data collected:

(i)   Senior Investment Team: Representation of main data collected. Includes General Partners, Partners, Managing Directors, Venture Partners etc. on the investment team

(ii)   Junior Investment Team: Other members of the investment team such as Principals, VPs, Associates, Analysts, Advisers, etc.

(iii)   Non-investment team: Generally includes operational / support roles such as finance, legal, etc. NOTE: Categories (ii) and (iii) have an issue of data availability (i.e. not all firms show their finance team) and should be considered more “directional”. Regarding gender, it is clear that women are hired more frequently into the junior ranks but do not have the same presence on the senior team. Further, many more women exist outside of the team. The US population estimates for 2020 is shown on the far right – both the VC community and the tech industry is far from the 50/50 split. Regarding race, the senior investment team in venture capital is 78% white which is less diverse than the large tech companies and significantly worse than the US population estimates for 2020.

92%  80%  

60%  

89%  77%  

49%  

8%  20%  

40%  

11%  23%  

51%  

Senior  Investment  Team Junior  Investment  Team Non-­‐Investment  Team Y-­‐Combinator  (W'14) Large  Tech  Avg.  (Leaders) US  in  2020

Gender  Distribution

%  Men %  Women

78%  63%  

86%  70%  

60%  

20%  32%  

13%  21%  

6%  

1%   2%   1%   2%  

12%  

1%   2%   1%   3%  19%  

0%  3%  

Senior  Investment  Team Junior  Investment  Team Non-­‐Investment  Team Large  Tech  Avg.  (Leaders) US  in  2020

Race/Ethnic  Distribution

%  White %  Asian Black Hispanic Other  /  2+

 

  9

An updated scatter-plot of % women and % minorities can be found below. The vast majority of funds are below where the US will be, and the magnitude of the disparity is largest when looking at representation of women vs. the US (i.e. firms are very far away from 50%).

–

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

– 20% 40% 60% 80% 100%

%  Women

%  Minority

Felicis

Trinity

Mayfield

KPCB

Floodgate,  Cowboy,Social  Capital

Khosla

Scale

Canaan

US2020:  51%  Women

US2020:  39%  Minorities

Storm

Aspect

Tech Giants

 

  10

Appendix 2: US and Tech Giant Comps The US Census data broken out is shown below.

The array of corresponding statistics for the leadership of large tech firms is below:

Our 2020Designation Classification 2013 Stats %sWhite  alone    (non-­‐Hispanic) White 62.6% 199,400 59.6%Black  or  African  American  alone Black 13.2% 41,594 12.4%American  Indian  /  Alaskan  Native  alone Other  /  2+ 1.2% 2,432 0.7%Asian  alone Asian 5.3% 19,255 5.8%Native  Hawaiian  and  other  pacific  islander  alone Other  /  2+ 0.2% 595 0.2%Two  or  more Other  /  2+ 2.4% 7,678 2.3%Hispanic  or  Latino Hispanic 15.1% 63,551 19.0%

100.0% 334,505 100.0%

White 62.6% 59.6%Asian 5.3% 5.8%Black 13.2% 12.4%Hispanic 15.1% 19.0%Other  /  2+ 3.8% 3.2%Total 100.0% 100.0%

US  Ethnic  Score 44% 41%

Male 155.7 165,036 49%Female 160.8 169,467 51%

316.5 334,503 100%

US  Gender  Score 50% 50%

72% 75% 75% 77% 77% 77% 78% 83% 89% 92%

28% 25% 25% 23% 23% 23% 22% 17% 11% 8%

AAPL LNKD AMZN YHOO FB Tech  AVG GOOG MSFT YC  Founders(W'14)

Senior  VCs

Gender

%  Men %  Women

63% 65% 71% 70% 71% 72% 73% 78% 78%

37% 35% 29% 30% 29% 28% 27% 22% 22%

AAPL LNKD MSFT Tech  AVG AMZN GOOG FB YHOO YC  Founders(W'14)

Senior  VCs

Ethnicity

%  White %  Minority

 

  11

Appendix 3: Best Venture Outcomes The following table shows the data used to calculate the distribution of ages of the partners who led the Series A / Series B rounds of the best US-based deals. Highlighted rows indicate deals for which we could not find the partner, firms or dates, or the company became insolvent shortly after exit—of these top 100 deals, 50 deals were used.

Name Round  Type Invested Post-­Valuation Closed  Date Series  A  Date Series  B  Date1. Facebook IPO 6,840 104,178 5/18/2012 5/1/2005 4/1/20062. Google IPO 1,202 24,640 8/19/2004 6/7/1999 n/a3. WhatsApp Acquisition 19,000 10/6/2014 4/8/2011 n/a4. Twitter IPO 1,820 15,650 11/7/2013 7/1/2007 5/1/20085. Corvis IPO 1,139 14,168 7/28/2000 n/a n/a6. Groupon IPO 700 13,384 11/4/2011 1/1/2008 12/1/20097. Continental  Cablevision Acquisition 11,800 12/22/1996 n/a n/a8. Zynga IPO 1,000 9,044 12/16/2011 1/15/2008 7/18/20089. MetroPCS IPO 863 8,489 4/19/2007 10/1/1994 n/a10. Cerent Acquisition 6,900 11/1/1999 n/a 4/1/199711. Webvan IPO 375 6,426 11/4/1999 n/a n/a12. LendingClub IPO 755 6,302 12/11/2014 8/23/2007 3/19/200913. Workday IPO 637 5,411 10/12/2012 12/6/2006 n/a14. Fitbit IPO 448 5,122 6/18/2015 10/10/2008 9/10/201015. LinkedIn IPO 217 5,053 5/19/2011 11/1/2003 10/1/200416. Clearwire IPO 600 4,925 3/8/2007 6/1/2004 n/a17. Chromatis  Networks Acquisition 4,756 6/28/2000 10/1/1998 9/27/199918. Siara  Systems Acquisition 4,500 3/8/2000 11/15/1998 4/20/199919. GoPro IPO 214 3,696 6/24/2014 5/5/2011 n/a20. ONI  Systems IPO 200 3,639 6/1/2000 12/1/1997 3/1/199821. Sirocco  Systems Acquisition 3,487 9/7/2000 4/27/1999 4/27/199922. Palo  Alto  Networks IPO 197 3,406 7/20/2012 1/1/2006 6/25/200723. Arista  Networks IPO 226 3,348 6/5/2014 n/a n/a24. Hyperion  Solutions Acquisition 3,300 3/1/2007 n/a n/a25. Vonage IPO 531 3,290 5/24/2006 n/a 11/24/200326. First  Republic  Bank IPO 105 3,270 12/9/2010 n/a n/a27. Xros Acquisition 3,227 6/1/2000 1/15/1999 8/15/199928. Nest  Labs Acquisition 3,200 2/7/2014 9/21/2010 8/1/201129. Oplink  Communications IPO 247 3,177 10/4/2000 n/a n/a30. Pandora  Media IPO 96 3,145 6/15/2011 1/1/2000 n/a31. DoubleClick Acquisition 3,100 3/12/2008 6/10/1997 2/20/199832. Transmeta IPO 273 3,036 11/7/2000 n/a n/a33. NorthPoint  Communications IPO 360 3,031 5/5/1999 n/a n/a34. Sycamore  Networks IPO 284 3,029 10/21/1999 n/a n/a35. Qtera Acquisition 3,004 1/28/2000 8/12/1998 4/19/199936. zulily IPO 140 3,000 11/15/2013 12/17/2009 8/4/201037. International  Power  Technology Acquisition 3,000 12/31/1991 n/a n/a38. Veeva  Systems IPO 194 2,971 10/16/2013 n/a 6/5/200839. Handspring IPO 200 2,919 6/21/2000 n/a n/a40. Cygnus  Solutions Acquisition 2,875 1/7/2000 2/15/1997 n/a41. FireEye IPO 304 2,849 9/20/2013 1/1/2005 8/23/200642. ServiceNow IPO 162 2,830 6/29/2012 7/5/2005 n/a43. TriZetto  Group Acquisition 2,700 11/3/2014 n/a n/a44. StorageNetworks IPO 243 2,676 6/30/2000 n/a n/a45. CoSine  Communications IPO 230 2,659 9/26/2000 n/a n/a46. Wayfair IPO 305 2,553 10/2/2014 6/21/2011 n/a47. Beats  Electronics  LLC Acquisition 2,500 8/1/2014 n/a n/a48. National  Computer  Systems Acquisition 2,500 7/31/2000 n/a n/a49. HomeAway IPO 160 2,469 6/29/2011 1/1/2005 1/1/200650. GT  Solar  International IPO 500 2,457 7/24/2008 n/a n/a51. CIENA IPO 115 2,410 2/7/1997 4/1/1994 12/1/199452. Fanch  Communications Acquisition 2,400 11/1/1999 n/a n/a53. Magma  Copper IPO 2,400 1/4/1996 n/a n/a54. Akamai  Technologies IPO 234 2,378 10/28/1999 12/14/1998 4/30/199955. Avanex IPO 216 2,375 2/4/2000 6/29/1998 3/25/199956. eToys IPO 166 2,334 5/19/1999 n/a n/a57. Ikaria Acquisition 2,300 4/17/2015 9/26/2005 n/a58. LS  Power  Group Acquisition 2,300 4/2/2007 n/a n/a59. Tritel IPO 237 2,296 12/13/1999 n/a n/a60. Priceline.com IPO 160 2,277 3/30/1999 n/a n/a61. Tableau  Software IPO 155 2,274 5/17/2013 1/1/2004 n/a62. FreeMarkets IPO 173 2,177 12/9/1999 n/a n/a63. Juno  Therapeutics IPO 265 2,131 12/19/2014 12/3/2013 8/5/201464. Intergraph  Corp. Acquisition 2,125 10/28/2010 n/a n/a65. Tellium IPO 135 2,121 5/17/2001 n/a n/a66. MP3.com IPO 346 2,004 7/21/1999 n/a n/a67. Splunk IPO 213 2,001 4/19/2012 12/1/2004 1/1/200668. Oculus  VR Acquisition 2,000 7/21/2014 6/17/2013 12/12/201369. Fusion-­io IPO 204 1,990 6/9/2011 3/31/2008 4/7/200970. Etsy IPO 213 1,987 4/16/2015 11/1/2006 1/1/200771. Telecorp  PCS IPO 184 1,966 11/22/1999 n/a n/a72. Box IPO 175 1,902 1/23/2015 10/1/2006 1/23/200873. Websense Acquisition 1,900 6/1/2015 n/a n/a74. Tradex  Technologies Acquisition 1,860 3/8/2000 n/a 3/1/199875. Nimble  Storage IPO 168 1,836 12/13/2013 12/21/2007 12/24/200876. Broadband  Access  Systems Acquisition 1,835 9/29/2000 7/1/1998 n/a77. Juniper  Networks IPO 163 1,816 6/24/1999 6/11/1996 8/5/199678. Green  Dot  Corp. IPO 1,816 7/22/2010 1/1/2003 n/a79. Onvia.com IPO 168 1,806 3/1/2000 n/a n/a80. AutoTrader.com Acquisition 1,800 1/3/2014 n/a n/a81. Niku IPO 192 1,790 2/29/2000 n/a n/a82. NetZero IPO 160 1,782 9/23/1999 n/a n/a83. Legent Acquisition 1,780 5/25/1995 n/a n/a84. VA  Linux  Systems IPO 132 1,755 12/9/1999 n/a n/a85. KiOR IPO 150 1,754 6/24/2011 n/a n/a86. Alios  BioPharma Acquisition 1,750 11/7/2014 n/a n/a87. NetSuite IPO 161 1,727 12/20/2007 n/a n/a88. Demand  Media IPO 77 1,720 1/26/2011 n/a n/a89. Rackspace  Hosting IPO 159 1,716 8/8/2008 n/a 3/27/200090. AXT IPO 25 1,716 5/20/1998 n/a n/a91. Liberty  Dialysis  LLC Acquisition 1,700 2/28/2012 n/a n/a92. Castlight  Health IPO 178 1,675 3/14/2014 8/1/2009 n/a93. Bindley  Western  Industries Acquisition 1,670 12/5/2000 n/a n/a94. KAR  Auction  Services IPO 300 1,660 12/11/2009 n/a n/a95. Reliant  Pharmaceuticals Acquisition 1,650 12/19/2007 n/a n/a96. YouTube Acquisition 1,650 11/13/2006 11/1/2005 n/a97. aQuantive IPO 126 1,632 2/29/2000 n/a n/a98. Avici  Systems IPO 217 1,617 7/28/2000 5/1/1997 n/a99. OnDeck  Capital IPO 200 1,612 12/17/2014 1/1/2006 1/1/2007100. Bright  Horizons  Family  Solutions IPO 222 1,605 1/25/2013 n/a n/a

 

  12

We have a total of 127 datapoints across the 50 of the largest exits above for which we have the actual or estimated age of the partner at the time of the Series A or B.

Name Fund Investment Series Deal  Date Age  @  Deal1. Jim  Breyer Accel  Partners Facebook Series  A 5/1/05 432. Reid  Hoffman Greylock  Partners Facebook Series  A 5/1/05 373. Peter  Thiel Founders  Fund Facebook Series  B 4/1/06 384. David  Sze Greylock  Partners Facebook Series  B 4/1/06 435. Paul  Madera Meritech  Capital  Partners Facebook Series  B 4/1/06 496. Ron  Conway SV  Angel Facebook Series  B 4/1/06 557. John  Doerr Kleiner  Perkins  Caufield  &  Byers Google Series  A 6/7/99 478. Michael  Moritz Sequoia  Capital Google Series  A 6/7/99 449. Jim  Goetz Sequoia  Capital WhatsApp Series  A 4/8/11 4510. Brian  Pokorny SV  Angel Twitter Series  A 7/1/07 2611. Ron  Conway SV  Angel Twitter Series  A 7/1/07 5612. George  Zachary Charles  River  Ventures Twitter Series  A 7/1/07 4013. Fred  Wilson Union  Square  Ventures Twitter Series  A 7/1/07 4514. Chris  Sacca Lowercase  Capital Twitter Series  A 7/1/07 3115. Marc  Andreessen Andreessen  Horowitz Twitter Series  A 7/1/07 3616. Mike  Maples  Jr. Floodgate Twitter Series  A 7/1/07 3817. Steve  Anderson Baseline  Ventures Twitter Series  A 7/1/07 3718. Bijan  Sabet Spark  Capital Twitter Series  B 5/1/08 3819. Joi  Ito MIT  Media  Lab Twitter Series  B 5/1/08 4120. Harry  Weller NEA Groupon Series  A 1/1/08 3721. Kevin  Efrusy Accel  Partners Groupon Series  B 12/1/09 3622. Fred  Wilson Union  Square  Ventures Zynga Series  A 1/15/08 4623. Andy  Russell Pilot  Group Zynga Series  A 1/15/08 3624. Rich  Levandov Avalon  Ventures Zynga Series  A 1/15/0825. Brad  Feld Foundry  Group Zynga Series  A 1/15/08 4226. Peter  Thiel Founders  Fund Zynga Series  A 1/15/08 4027. Reid  Hoffman Greylock  Partners Zynga Series  A 1/15/08 4028. Brian  Pokorny SV  Angel Zynga Series  A 1/15/08 2729. John  Doerr Kleiner  Perkins  Caufield  &  Byers Zynga Series  B 7/18/08 5730. Sandy  Miller Institutional  Venture  Partners Zynga Series  B 7/18/08 5831. Vinod  Khosla Khosla  Ventures Cerent Series  B 4/1/97 4232. Dan  Ciporin Canaan  Partners LendingClub Series  A 8/23/07 4833. Jeff  Crowe Norwest  Venture  Partners LendingClub Series  A 8/23/07 4934. Rebecca  Lynn Canvas  Venture  Fund LendingClub Series  B 3/19/09 3635. Jeff  Clavier SoftTech  VC FitBit Series  A 10/10/08 4036. Jon  Callaghan True  Ventures FitBit Series  A 10/10/08 3937. Brad  Feld Foundry  Group FitBit Series  B 9/10/10 4438. Aydin  Senkut Felicis  Ventures Fitbit Series  B 9/10/10 3939. Mark  Kvamme Sequoia  Capital LinkedIn Series  A 11/1/03 4240. Josh  Kopelman First  Round  Capital LinkedIn Series  A 11/1/03 3241. David  Sze Greylock  Partners LinkedIn Series  B 10/1/04 4142. Dave  Flanagan Intel  Capital Clearwire Series  A 6/1/04 3443. Seth  Neiman Crosspoint Chromatis  Networks Series  A 10/1/98 4444. Vinod  Khosla Khosla  Ventures Siara  Systems Series  A 11/15/98 4345. Promod  Haque Norwest  Venture  Partners Siara  Systems Series  A 11/15/98 5046. Michael  Marks Riverwood  Capital GoPro Series  A 5/5/11 5947. Ned  Gilhuly Sageview  Capital GoPro Series  A 5/5/11 5048. John  Ball Steamboat  Ventures GoPro Series  A 5/5/11 4749. Chris  Rust Cyphort GoPro Series  A 5/5/11 4550. Lip-­‐Bu  Tan Walden  International GoPro Series  A 5/5/11 5151. Kevin  Compton Kleiner  Perkins  Caufield  &  Byers ONI  Systems Series  A 12/1/97 3952. Jon  Feiber Mohr  Davidow ONI  Systems Series  A 12/1/97 4053. Felda  Hardymon Bessemer  Venture  Partners Sirocco  Systems Series  A 4/27/99 5154. Roger  Evans Greylock  Partners Sirocco  Systems Series  A 4/27/99 4955. Barry  Eggers Lightspeed  Venture  Partners Sirocco  Systems Series  A 4/27/99 3556. Jim  Goetz Sequoia  Capital Palo  Alto  Networks Series  A 1/1/06 4057. Asheem  Chandna Greylock  Partners Palo  Alto  Networks Series  A 1/1/06 4158. Harry  Weller NEA Vonage Series  B 11/24/03 3359. Thomas  Bredt Menlo  Ventures XROS Series  A 1/15/99 5760. Randy  Komisar Kleiner  Perkins  Caufield  &  Byers Nest  Labs Series  A 9/21/10 5461. Rob  Coneybeer Shasta  Ventures Nest  Labs Series  A 9/21/10 4062. Bill  Maris Google  Ventures Nest  Labs Series  B 8/1/11 3563. Peter  Nieh Lightspeed  Venture  Partners Nest  Labs Series  B 8/1/11 4564. Larry  Kubal Labrador  Ventures Pandora  Media Series  A 1/1/00 4765. Doug  Barry Selby  Ventures Pandora  Media Series  A 1/1/00 3666. Larry  Marcus Walden  International Pandora  Media Series  A 1/1/00 4867. Dave  Strohm Greylock  Partners DoubleClick Series  A 6/10/97 4868. Deepak  Kamra Canaan  Partners DoubleClick Series  A 6/10/97 4069. Ray  Rothrock Venrock DoubleClick Series  A 6/10/97 3970. Todd  Dagres Spark  Capital Qtera Series  A 8/12/98 3771. Todd  Brooks Mayfield  Fund Qtera Series  B 4/19/99 3872. Jason  Stoffer Maveron Zulily Series  A 12/17/09 3273. Eric  Carlborg August  Capital Zulily Series  B 8/4/10 4574. Gus  Tai Trinity  Ventures Zulily Series  B 8/4/10 4475. Gordon  Ritter Emergence  Capital Veeva  Systems Series  B 6/5/08 4376. Dave  Strohm Greylock  Partners Cygnus  Solutions Series  A 2/15/97 4877. John  Johnston August  Capital Cygnus  Solutions Series  A 2/15/97 4178. Matthew  Howard Norwest  Venture  Partners FireEye Series  A 1/1/05 4079. Gaurav  Garg Sequoia  Capital FireEye Series  A 1/1/05 3880. Joe  Horowitz Icon  Ventures FireEye Series  B 8/23/0681. Paul  Barber JMI  Equity ServiceNow Series  A 7/5/05 4282. Alex  Finkelstein Spark  Capital Wayfair Series  A 6/21/11 3483. Neeraj  Agrawal Battery  Ventures Wayfair Series  A 6/21/11 3884. Michael  Kumin Great  Hill  Partners Wayfair Series  A 6/21/11 3785. Ian  Lane HarvourVest Wayfair Series  A 6/21/11 3386. Phil  Siegel Austin  Ventures HomeAway Series  A 1/1/05 3987. Jeff  Brody Redpoint  Ventures HomeAway Series  A 1/1/05 4388. Todd  Chaffee Institutional  Venture  Partners HomeAway Series  B 1/1/06 4589. John  Moragne Trident  Capital HomeAway Series  B 1/1/06 4590. Berry  Cash InterWest CIENA Series  A 4/1/94 5291. David  Cowan Bessemer  Venture  Partners CIENA Series  B 12/1/94 2892. Scott  Tobin Battery  Ventures Akamai  Technologies Series  A 12/14/98 2793. Todd  Chaffee Institutional  Venture  Partners Akamai  Technologies Series  A 12/14/98 3894. Andrew  Schwab 5am  Ventures Ikaria Series  A 9/26/05 3395. Robert  Nelsen ARCH  Venture  Partners Ikaria Series  A 9/26/05 4196. Bryan  Roberts Venrock Ikaria Series  A 9/26/05 3797. Forest  Baskett,  PhD NEA Tableau  Software Series  A 1/1/04 6098. Robert  Nelsen ARCH  Venture  Partners Juno  Therapeutics Series  A 12/3/13 5099. Bong  Koh Venrock Juno  Therapeutics Series  A-­‐2 12/3/13 40100. David  Hornik August  Capital Splunk Series  A 12/1/04 36101. Thomas  Neustaetter JK&B  Capital Splunk Series  B 1/1/06 53102. Antonio  Rodriguez Matrix  Partners Oculus  VR Series  A 6/17/13 38103. Santo  Politi Spark  Capital Oculus  VR Series  A 6/17/13 46104. Joe  Lonsdale Formation  8 Oculus  VR Series  A 6/17/13 30105. Brian  Singerman Founders  Fund Oculus  VR Series  A 6/17/13 34106. Chris  Dixon Andreessen  Horowitz Oculus  VR Series  B 12/12/13 40107. Scott  Sandell NEA Fusion-­‐io Series  A 3/31/08 43108. Chris  Schaepe Lightspeed  Venture  Partners Fusion-­‐io Series  B 4/7/09 43109. Blake  Modersitzki Pelion  Venture  Partners Fusion-­‐io Series  B 4/7/09 39110. Fred  Wilson Union  Square  Ventures Etsy Series  A 11/1/06 45111. Josh  Stein Draper  Fisher  Jurvetson Box Series  A 10/1/06 32112. Winston  Fu US  Venture  Partners Box Series  B 1/23/08 41113. Steve  Jurvetson Draper  Fisher  Jurvetson TradeX  Technologies Series  B 3/1/98 30114. Ping  Li Accel  Partners Nimble  Storage Series  A 12/21/07 35115. Jim  Goetz Sequoia  Capital Nimble  Storage Series  A 12/21/07 42116. Barry  Eggers Lightspeed  Venture  Partners Nimble  Storage Series  B 12/24/08 45117. Andrew  Marcuvitz Matrix  Partners Broadband  Access  Systems Series  A 7/1/98118. Vinod  Khosla Khosla  Ventures Juniper  Networks Series  A 6/11/96 41119. Seth  Neiman Crosspoint Juniper  Networks Series  B 8/5/96 42120. Andy  Rachleff Benchmark  Capital Juniper  Networks Series  B 8/5/96 37121. Geoff  Yang Redpoint  Ventures Juniper  Networks Series  B 8/5/96 36122. Peter  Barris NEA Juniper  Networks Series  B 8/5/96 43123. Michael  Moritz Sequoia  Capital Green  Dot  Corp. Series  A 1/1/03 48124. Douglas  Leone Sequoia  Capital Rackspace  Hosting Series  B 3/27/00 41125. George  Still Norwest  Venture  Partners Rackspace  Hosting Series  B 3/27/00 41126. Bryan  Roberts Venrock Castlight  Health Series  A 8/1/09 41127. Roelof  Botha Sequoia  Capital Youtube Series  A 11/1/05 33128. Jim  Swartz Accel  Partners Avici  Systems Series  A 5/1/97129. Matt  Gorin Contour  Venture  Partners OnDeck  Capital Series  A 1/1/06130. Matt  Harris Bain  Capital  Ventures OnDeck  Capital Series  A 1/1/06 33131. David  Weiden Khosla  Ventures OnDeck  Capital Series  B 1/1/07 34132. James  Robinson  III RRE  Ventures OnDeck  Capital Series  B 1/1/07 71