Practice Group Network, 2010−2014
Data Analytics for Strategy Webinar 7 ・ January 2015
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1
Data Analytics Overview Insights and Value
2
General Principles
3
Applied Examples
4
Concluding Remarks
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1
Data Analytics Overview Insights and Value
2
General Principles
3
Applied Examples
4
Concluding Remarks
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The Rise of Big Data
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Insights from Data
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Knowing how to do data analytics benefits both analysts and decision makers.
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Today we cover basic steps of data analytics and illustrate with legal industry examples.
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What You Gain When You Use Data
Gains From Using Data I
Implement data-driven decision making in areas that are commonly evaluated by gut instincts and intuition.
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Improve business development strategy.
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Find focus and achieve overall firm goals.
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Value of Insight
The Value of Data-Driven Insights
Complexity of Analysis
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Value of Insight
The Value of Data-Driven Insights
Complexity of Analysis
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Value of Insight
The Value of Data-Driven Insights
Complexity of Analysis
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Value of Insight
The Value of Data-Driven Insights
Complexity of Analysis
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The Value of Data-Driven Insights
Value of Insight
Opportunity
Complexity of Analysis
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1
Data Analytics Overview Insights and Value
2
General Principles
3
Applied Examples
4
Concluding Remarks
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Doing Data Analysis: Four Basic Steps
Step 1. 2. 3. 4.
Formulate Question Identify Important Factors Collect, Organize, and Analyze Deliver Results
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Doing Data Analysis: Four Basic Steps
Step
What do you need?
1. 2. 3. 4.
Domain Expertise Domain Expertise Data Expertise Domain & Data Expertise
Formulate Question Identify Important Factors Collect, Organize, and Analyze Deliver Results
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Formulating the Question
Strong Questions Are: I
Focused on outcomes.
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General in nature.
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Designed to establish priorities.
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Identifying Important Factors
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First ask: What factors are important to the outcome?
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Then ask: In what way(s) do these factors likely matter?
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Data Collection and Organization
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Collect data on relevant factors (get creative).
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Clean and organize the data.
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Check for problems!
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Data Analysis
Your Question/Goal Determines Type of Analysis: Describe Produce factual statements about the firm. Explain Summarize relationships. Predict Generate expectations – the “most likely” outcome.
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Delivery of Results
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Clear, easy-to-grasp presentation of results is critical.
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Use data visualization techniques to tell data-driven stories.
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Data Visualization Best Practices
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High data-to-ink ratio.
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Graphic is sufficient.
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Interpretation is easy, the lede screams.
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Hierarchy of perception.
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Hierarchy of Perception
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1
Data Analytics Overview Insights and Value
2
General Principles
3
Applied Examples
4
Concluding Remarks
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Practice Area Government Affairs Intellectual Property Intellectual Property Intellectual Property Labor and Employment Capital Transactions Securities Litigation Real Estate Real Estate Labor and Employment Intellectual Property Labor and Employment Labor and Employment Capital Transactions Insurance and Tort Defense Capital Transactions Securities Litigation Labor and Employment Labor and Employment Labor and Employment
Hours 2 1 1 2 4 6 7 5 2 6 17 2 13 2 2 7 3 6 6 1
Dollars 220.00 57.00 27.90 153.90 514.90 1849.20 1064.00 387.00 139.03 1185.75 6800.00 225.50 2152.80 192.50 81.84 1314.42 323.00 1144.00 672.80 23.40
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Total Revenue (Millions of Dollars) 30
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Total Revenue By Practice Area $47.52
40
$28.90 $31.67
$23.75
$14.91 $19.31
10
$5.36
0 $3.47 $3.04
Practice Area
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Total Revenue By Practice Area
Labor and Employment
$47.52
Capital Transactions
$31.67
Business Litigation
$28.90
Practice Area
Insurance and Tort Defense
$23.75
Real Estate
$19.31
Intellectual Property
$14.91
Environmental
$5.36
Bankruptcy
$3.68
Government Affairs
$3.47
Securities Litigation
$3.04
Appellate
$1.86
0
10
20
30
40
50
Total Revenue (Millions of Dollars)
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Practice Area Government Affairs Intellectual Property Intellectual Property Intellectual Property Labor and Employment Capital Transactions Securities Litigation Real Estate Real Estate Labor and Employment Intellectual Property Labor and Employment Labor and Employment Capital Transactions Insurance and Tort Defense Capital Transactions Securities Litigation Labor and Employment Labor and Employment Labor and Employment
Industry Wholesale, Retail, and Service Industries Manufacturing and Production Manufacturing and Production Manufacturing and Production Wholesale, Retail, and Service Industries Health Care and Life Sciences Finance, Insurance, and Real Estate Finance, Insurance, and Real Estate Wholesale, Retail, and Service Industries Transportation Manufacturing and Production Manufacturing and Production Health Care and Life Sciences Manufacturing and Production Transportation Utilities Telecommunications and Media Wholesale, Retail, and Service Industries Manufacturing and Production Manufacturing and Production
Hours 2 1 1 2 4 6 7 5 2 6 17 2 13 2 2 7 3 6 6 1
Dollars 220.00 57.00 27.90 153.90 514.90 1849.20 1064.00 387.00 139.03 1185.75 6800.00 225.50 2152.80 192.50 81.84 1314.42 323.00 1144.00 672.80 23.40
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Total Revenue By Industry
Manufacturing and Production
$37.41
Health Care and Life Sciences
$34.01
Wholesale, Retail, and Service Industries
$33.95
Industry
Finance, Insurance, and Real Estate
$25.46
Utilities
$22.04
Transportation
$17.82
Telecommunications and Media
$4.33
Education
$3.48
Technology
$2.50
Miscellaneous
$1.30
Energy
$1.17
0
10
20
30
40
Total Revenue (Millions of Dollars)
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0
0.2
0.4
0.6
Density
0.8
1
1.2
Total Revenue By Industry and Practice Area
−1
0
1
2
3
Revenue Concentration
0.20
0.53
2.55
8.48
4.52
2.49
Manufacturing and Production
0.13
0.26
0.79
11.48
5.17
2.78
7.44
Health Care and Life Sciences
0.95
0.12
0.25
2.27
0.37
0.72
0.48
2.32
4.32
4.69
8.96
Finance, Insurance, and Real Estate
3.21
0.95
3.29
0.04
0.68
0.20
0.05
1.48
8.02
0.72
3.40
Utilities
0.36
0.14
0.09
0.13
0.09
0.01
0.08
0.16
0.64
0.10
0.71
Technology
0.60
0.02
0.00
0.00
0.00
0.01
0.04
0.08
0.24
0.06
0.24
Miscellaneous
0.32
0.00
0.24
0.01
0.00
0.01
0.03
0.16
0.27
0.02
0.10
Energy
1.15
0.58
0.10
0.03
0.32
0.07
0.04
0.22
0.21
0.59
0.17
Education
0.09
1.59
0.00
0.01
0.04
0.05
0.05
1.00
0.39
0.59
0.51
Telecommunications and Media
14.66
0.64
0.52
0.21
1.64
0.21
0.87
3.16
3.15
4.50
4.40
Wholesale, Retail, and Service Industries
14.28
0.01
0.03
0.10
0.06
0.12
0.08
1.15
0.77
0.74
0.48
Transportation
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Industry
0.13
0.22
ns
0.66
0.24
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0.60
2.08
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8.77
3.42
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Practice Area
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1
Data Analytics Overview Insights and Value
2
General Principles
3
Applied Examples
4
Concluding Remarks
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Key Challenges and Next Steps
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Lack of expertise/know-how. Cost of getting started. I I
Time. Money.
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Questions?
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