Market Analysis of the 200 Largest Law Firms: Part 2

A Market Analysis of the 200 Largest Law Firms: Part 2

Data Source: American Lawyer Analysis by Lawyer Metrics

Webinar 14 ăƒť February 2016

Leverage Ty Diamond Mixed Pyramid

Review of Part 1

Why are some large law ďŹ rms more proďŹ table than others?

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Figure 1: Average Partner Compensation, FY2010–FY2014 Baker Donelson K&L Gates

200

Count of Firms

150

100

Alston & Bird Orrick

50 Cravath Davis Polk Data Source: American Lawyer

0 0

2,000,000 4,000,000 Average Partner Compensation (1 Bin = $100K)

6,000,000

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What predictors differentiate more and less profitable firms?

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Conceptual Model

Outcome = Predictors + ϵ (Error Term) Profitability = Predictors + ϵ

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Potential Predictors: 1. Firm Structure (Leverage Model) 2. Geography (HQ Location/Market) 3. Geographical Concentration (Low vs. High) 4. Client Industries 5. Practice Areas/Expertise 6. Partner Demographics (Age) 7. Lateral Activity 8. Quality of Firm Management (Ďľ)

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Table 1: Average Partner Compensation by Leverage Type and Office Concentration

Office Concentration Very Diffuse Somewhat Diffuse Somewhat Concentrated Very Concentrated

Leverage Type Pyramid Mixed Diamond $1.29m $0.88m $0.55m $1.51m $0.75m $0.63m $1.39m $0.82m $0.63m $1.98m $1.15m $0.66m

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Table 2: Average Partner Compensation by Leverage Type and Office Concentration

Office Concentration Very Diffuse Somewhat Diffuse Somewhat Concentrated Very Concentrated

Leverage Type Pyramid Mixed Diamond $1.29m $0.88m $0.55m $1.51m $0.75m $0.63m $1.39m $0.82m $0.63m $1.98m $1.15m $0.66m

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Summary of Findings

Profitability is: ▶

Negatively correlated with “Diamond” leverage.

▶

Negatively correlated with more diffuse geographic footprint.

Action items: ▶

Identify firms that are outperforming their leverage and geographic endowments.

▶

Identify strategy and management factors that could explain superior performance with similar assets.

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Potential Predictors: 1. Firm Structure (Leverage Model) 2. Geography (HQ Location/Market) 3. Geographical Concentration (Low vs. High) 4. Client Industries?

5. Practice Areas/Expertise?

6. Partner Demographics (Age) 7. Lateral Activity 8. Quality of Firm Management (Ďľ)

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Client Industries

Measuring Client Industries

▶

Measure law firm-corporate client relationships using ALM’s In-House Law Departments data.

▶

Classify corporate clients by industry using Lawyer Metrics’ NAICS-based classification scheme.

▶

Data are counts of observed entries – i.e., the number of times a client relationship involved a particular industry.

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Figure 2: Fortune 500 Representation, Top 20 by Client Industry Morgan Lewis & Bockius Ogletree Deakins Littler Mendelson Jackson Lewis Jones Day Seyfarth Shaw Gibson Dunn Sidley Austin

Client Industry

Skadden Arps

Energy

Kirkland & Ellis

Finance Health Care and Life Sciences

DLA Piper

Insurance

Hunton & Williams

Manufacturing and Production Real Estate

Fulbright & Jaworski

Technology

Davis Polk

Telecommunications and Media

Bryan Cave

Transportation

Reed Smith

Utilities Wholesale, Retail, and Service Industries

Baker Botts Baker & McKenzie

Data Source: ALM Legal Intelligence Analysis and Results By Lawyer Metrics

Weil Gotshal & Manges Greenberg Traurig 0

100

200

300

400

500

Client Industry Counts

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Figure 3: Client Industry Counts and Average Partner Compensation Energy

Finance

Health Care and Life Sciences

Insurance

Manufacturing and Production

Real Estate

Technology

Telecommunications and Media

Transportation

Utilities

Wholesale, Retail, and Service Industries

15

Average Partner Compensation (Five−Year Mean, Log Scale)

14 13

15 14 13

15 14 13 0

1

2

3

4

5

0

1

2

3

4

5

0

1

2

3

4

5

Client Industry Counts (Log Scale)

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Practice Areas/Expertise

Measuring Practice Areas/Expertise

▶

Measure law firms’ practice area expertise using ALM’s In-House Law Departments data, which covers six broad areas: 1: Corporate Transactions 2: Intellectual Property 3: Labor and Employment 4: Litigation 5: Patent Prosecution 6: Securities Law

▶

Data are counts of observed entries – i.e., the number of times a client relationship involved a particular practice area.

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Figure 4: Fortune 500 Representation, Top 20 by Practice Area Morgan Lewis & Bockius Ogletree Deakins Littler Mendelson Jackson Lewis Jones Day Seyfarth Shaw Gibson Dunn Sidley Austin Skadden Arps Kirkland & Ellis

Practice Area

DLA Piper

Corporate Transactions Intellectual Property

Hunton & Williams

Labor and Employment

Fulbright & Jaworski

Litigation

Davis Polk

Patent Prosecution Securities Law

Bryan Cave Reed Smith Foley & Lardner McGuireWoods

Data Source: ALM Legal Intelligence Analysis and Results By Lawyer Metrics

Vinson & Elkins Greenberg Traurig 0

200

400

Practice Area Counts

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Figure 5: Practice Area Counts and Average Partner Compensation Corporate Transactions

Intellectual Property

Labor and Employment

Litigation

Patent Prosecution

Securities Law

Average Partner Compensation (Five−Year Mean, Log Scale)

15

14

13

15

14

13 0

2

4

6 0

2

4

6 0

2

4

6

Practice Area Counts (Log Scale)

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Regression Results

Regression Model

Outcome = Predictors + ϵ (Error Term) Profitability = Predictors + ϵ

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Multivariate Analysis of Average Partner Compensation

▶

Regression analysis was used to explore differences in compensation while accounting for numerous predictors simultaneously, including leverage model, geography, client industry and practice area expertise.

▶

Results of this analysis present the “purified” associations between average compensation and each predictor while all else is equal.

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Figure 6: Predictors of Average Partner Compensation PA: Corporate Transactions Office Concentration Leverage = Pyramid PA: Litigation

Relationship Negative Positive

Industry: Technology Industry: Telecommunications and Media Leverage = Mixed

Predictor

Industry: Energy PA: Intellectual Property PA: Labor and Employment Industry: Real Estate Industry: Finance PA: Patent Prosecution Industry: Insurance Industry: Transportation Industry: Manufacturing and Production PA: Securities Industry: Wholesale, Retail Service Industry: Utilities Industry: Health Care and Life Sciences −300K

Overall Average (~$460K)

+300K

+600K

Average Partner Compensation ($ Thousands)

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Figure 7: Average Partner Compensation: Differences by Selected Headquarters Markets New York−Northern New Jersey−Long Island, NY−NJ−PA Los Angeles−Long Beach−Santa Ana, CA Atlanta−Sandy Springs−Marietta, GA San Jose−Sunnyvale−Santa Clara, CA Boston−Cambridge−Quincy, MA−NH Washington−Arlington−Alexandria, DC−VA−MD−WV

HQ Market

Chicago−Naperville−Joliet, IL−IN−WI San Francisco−Oakland−Fremont, CA Dallas−Fort Worth−Arlington, TX San Diego−Carlsbad−San Marcos, CA Philadelphia−Camden−Wilmington, PA−NJ−DE−MD Miami−Fort Lauderdale−Pompano Beach, FL Charlotte−Gastonia−Concord, NC−SC Minneapolis−St. Paul−Bloomington, MN−WI St. Louis, MO−IL Houston−Sugar Land−Baytown, TX Seattle−Tacoma−Bellevue, WA

−500K

Overall Average (~$460K)

+500K

Average Partner Compensation ($ Thousands)

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Summary of Findings

Profitability is significantly related to both types of clients and types of work: ▶

The more technology/telecommunications clients at a firm, the higher the profitability.

▶

The more corporate transactions and (some) litigation work, the higher the profitability.

Action items: ▶

Recognize that strategic opportunities exist on both industry and practice dimensions.

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Potential Predictors: 1. Firm Structure (Leverage Model) 2. Geography (HQ Location/Market) 3. Geographical Concentration (Low vs. High) 4. Client Industries 5. Practice Areas/Expertise 6. Partner Demographics (Age)?

7. Lateral Activity?

8. Quality of Firm Management (Ďľ)?

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