John Lucker

Experienced management consultant, innovator, practice builder and business leader with a proven track record of generating high value, end-to-end, pragmatic business solutions which allow for rapid and achievable return on investment.

Specialties: Management Consulting, Strategy, Consulting Sales & Marketing, Consulting Practice Building & Leadership, Consulting Eminence Building, Executive Leadership, Consulting Team Building and Mentoring, Professional Services Research & Development, Business Analytics Business Solutions, Advanced Analytics, Data Mining, Predictive Modeling, Rules Engines, Scoring Engines, Data Visualization, Statistical Modeling, Customer Segmentation, Price Optimization, Demand Analysis, Insurance Underwriting / Claims / Distribution

• Connecticut Rivers Council - Boy Scouts of America

  Board Member
  • January 2008 to Present

• World Affairs Council of Connecticut

  Board Member
  • September 2012 to Present

  http://www.ctwac.org - The World Affairs Council of Connecticut is a non-profit, non partisan educational organization whose mission is to create informed public opinion on global matters. Established in 1924, the Council serves the greater Hartford area to develop awareness of peoples, cultures, and governments around the world. It achieves its mission through public programs and education programs. As a member of the World Affairs Councils of America, the World Affairs Council of Connecticut is part of the largest international affairs nonprofit in the United States. The World Affairs Council's public programs bring high profile speakers and well-respected authors and scholars to the Hartford area. It counts among its accomplishments a dynamic Executive Forum series that has featured a rich array of speakers. The WAC's Model United Nations program also provides an international education experience for some 500 students representing 31 high schools (founded in 1949, making it the third oldest Model UN program in the country).

1. Analytics
2. Segmentation
3. Data Mining
4. Management Consulting
5. Pricing
6. Predictive Modeling
7. Leadership
8. Insurance
9. Underwriting
10. Business Process Improvement
11. Strategy
12. R&D
13. Statistical Modeling
14. Data Visualization
15. Rules Engines
16. Business Analytics
17. Business Strategy
18. Business Transformation
19. Business Analysis
20. Change Management
21. Business Process Re-engineering
22. Predictive Analytics
23. Consulting
24. Data Analysis
25. Strategic Consulting
26. Enterprise Risk Management
27. Operational Risk Management
28. Analysis
29. Mergers & Acquisitions
30. Financial Modeling
31. Information Technology

View All (31) Skills View Fewer Skills

• Know What Your Customers Want Before They Do

  • Harvard Business Review
  • December 2011
  Authors: John Lucker, Tom Davenport, Leandro DalleMule

  Shoppers once relied on familiar salespeople to help them find exactly what they wanted—and sometimes to suggest additional items they hadn’t even thought of. But today’s distracted consumers, bombarded with information and options, often struggle to find products or services that meet their needs.
  
  Advances in information technology, data gathering, and analytics are making it possible to deliver something like the personal advice of yesterday’s sales staffs. Using increasingly granular customer data, businesses are starting to create highly customized offers that steer shoppers to the “right” merchandise—at the right moment, at the right price, and in the right channel.
  
  But few companies can do this well. The authors demonstrate how retailers can hone their “next best offer” (NBO) capability by breaking the problem down into four steps: defining objectives, gathering data (about your customers, your products, and the purchase context), analyzing and executing, and learning and evolving. Citing successful strategies in companies such as Tesco, Zappos, Microsoft, and Walmart, they provide a framework for nailing the NBO.

• A 360 Degree View

  • Bests Review
  • July 2011
  Authors: John Lucker

  The Trend: Many insurers are not fully realizing the benefits of their predictive analytics investments. The Big Picture: The use of predictive analytics in commercial lines has evolved into a necessary core competency. What Needs to Happen: Insurers need to meld enterprise decision management with predictive analytics to enhance their information processing and decision-making sophistication.

• Beyond The Numbers: Analytics as a Strategic Capability

  • Deloitte Review
  • January 2011
  Authors: John Lucker, Jim Guszcza

  Uncovering the realities that lie behind the data is what
  business analytics is all about. Precisely because they
  are hidden to the casual observer, they lend competitive
  advantages to the organizations that discover and implement
  them in business first.

• Too Big To Ignore

  • Deloitte Review
  • January 31, 2013
  Authors: John Lucker, Jim Guszcza, David Steier, Harvey Lewis, Vivekanand Gopalkrishnan

  Much of the language surrounding big data conveys a muddled conception of what data, “big” or otherwise, means to the majority of organizations pursuing analytics strategies. Big data is shrouded in hyperbole and confusion, which can be a breeding ground for strategic errors. Big data is a big deal, but it is time to separate the signal from the noise.

• Big Data 2.0

  • Deloitte Review
  • January 31, 2013
  Authors: John Lucker, Jim Guszcza, David Steier, Harvey Lewis, Vivekanand Gopalkrishnan

  For many businesses, research suggests that the focus on efforts related to big data has been largely on improved efficiency and operations. While those opportunities are impressive, the possibilities as to how big data might be used to ask new business questions and meet market needs can be even more intriguing.

• The BI and Analytics Treadmill

  • Tech Decisions
  • March 2010
  Authors: John Lucker

• The 2009 Shift Index – Insurance Industry Metrics and Perspectives

  • Deloitte Center for the Edge
  • November 2009
  Authors: John Lucker

• In Fraud, It’s The Devil You Know

  • Tech Decisions
  • November 2009
  Authors: John Lucker, Howard Mills

  Insurance fraud isn’t new, but its growth in tough times makes fighting it ever more critical - some suggested strategies and actions to combat insurance fraud.

• Commercial Insurance Carrier’s Road to Business Agility

  • Business Rules Community
  • October 2009
  Authors: John Lucker, Mo Masud

• Rules, Rules Everywhere Rules

  • Tech Decisions
  • May 2009
  Authors: John Lucker

• The Cutting Edge

  • Tech Decisions
  • January 2009
  Authors: John Lucker

• Data Driven Organizations: Knowing The Unknown

  • Insurance & Technology
  • January 5, 2009
  Authors: John Lucker

• It’s Better to Know What You Don’t Know: Step 4 – Insights Through BI Innovation

  • Insurance & Technology
  • September 22, 2008
  Authors: John Lucker

• Predictive Analytics Aid in End-To-End Segmentation

  • Predictive Modeling News
  • May 2008
  Authors: John Lucker, Mo Masud, Susan Novak

• The Price is Right

  • Global Reinsurance
  • November 2006
  Authors: John Lucker, Catherine Barton, Mark Rothwell

• Secrets to Successful Commercial Segmentation

  • Bests Review
  • July 2006
  Authors: John Lucker, Rebecca Amoroso, Frank Zizzamia, Jim Marino

• Taking a Hard Look at Soft Fraud

  • Contingencies
  • March 2006
  Authors: John Lucker, Kevin Bingham, Mo Masud

• Making Your Data Come Alive: Step 3 – Leveraging Analytics as a Key Differentiator

  • Insurance & Technology
  • December 14, 2005
  Authors: John Lucker

• Sometimes Good is Good Enough: Step 2 – Getting Enterprise-Wide Information Ready for Use

  • Insurance & Technology
  • November 30, 2005
  Authors: John Lucker

• Swimming-Not Drowning-In Enterprise Data: Step 1 – An Enterprise-Wide Information Inventory

  • Insurance & Technology
  • October 19, 2005
  Authors: John Lucker

• It’s the Right Time for Right Pricing in Medical Malpractice Insurance

  • Contingencies
  • August 2005
  Authors: John Lucker, Kevin Bingham

• Inside the Black Box: A Look at Personal Lines Insurance Credit Scoring Models

  • Deloitte & Touche Indicator - Volume 3
  • February 2004
  Authors: John Lucker

• A View Inside the “Black Box”: A Review and Analysis of Personal Lines Insurance Credit Scoring Models Filed in the State of Virginia

  • Casualty Actuarial Society – CAS Winter 2004 Forum
  • February 2004
  Authors: John Lucker, Peter Wu

• Using Data Mining Analytics to Reduce Uncertainty in Insurance M&A and Merger Integration Transactions

  • Deloitte & Touche – Indicator Volume 1
  • October 2002
  Authors: John Lucker, Frank Zizzamia

• Predictive Modeling for Success in Property-Casualty M&A Transactions

  • Deloitte & Touche – Perspectives for Insurance M&A
  • August 2002
  Authors: John Lucker, Frank Zizzamia

• Insurance Credit Scoring and Other Regulatory Uncertainty in Insurance M&A and Merger Integration Transactions – Part Two

  • Deloitte & Touche – Perspectives for Insurance M&A
  • July 2002
  Authors: John Lucker, Frank Zizzamia

• Insurance Credit Scoring and Other Regulatory Uncertainty in Insurance M&A and Merger Integration Transactions – Part One

  • Deloitte & Touche – Perspectives for Insurance M&A
  • June 2002
  Authors: John Lucker, Frank Zizzamia

• Using Data Mining Analytics to Reduce Uncertainty in Insurance M&A and Merger Integration Transactions

  • Deloitte & Touche – Perspectives for Insurance M&A
  • March 2002
  Authors: John Lucker, Frank Zizzamia

• The Path To a Corporate Culture enlightened by business analytics

  • SearchBusinessAnalytics & Search CIO
  • December 15, 2011
  Authors: John Lucker

• Assessing an enterprise’s analytics maturity

  • SearchBusinessAnalytics & Search CIO
  • December 15, 2011
  Authors: John Lucker

• Business Analytics-Creating One Version of the Truth

  • SearchBusinessAnalytics & Search CIO
  • December 15, 2011
  Authors: John Lucker

• Analytics: Turning Data Into Dollars

  • Deloitte Forward Focus
  • December 2011
  Authors: John Lucker, Howard Mills, Jim Guszcza

• Customer Analytics - The 3 Minute Guide

  • Deloitte Analytics
  • January 17, 2012
  Authors: John Lucker

• 2012 Global Insurance Outlook

  • Deloitte
  • January 2012
  Authors: John Lucker, Other Authors

• A Delicate Balance: Organizational Barriers to Evidence-Based Management

  • Deloitte Review
  • January 2012
  Authors: John Lucker, Jim Guszcza

• Business Analytics: Fad or Fundamental?

  • Deloitte Analytics
  • February 12, 2012
  Authors: John Lucker

• It’s Time to Get Real About Analytics

  • WSJ CIO Journal
  • April 12, 2012
  Authors: John Lucker

• Why Some CEOs Are So Skeptical of Analytics

  • WSJ CIO Online
  • June 5, 2012
  Authors: John Lucker, Jim Guszcza

• 5 Reasons Analytics Projects Can Fail

  • WSJ CIO Online
  • June 6, 2012
  Authors: John Lucker, Jim Guszcza

• Customer Analytics: 5 Tips for Getting Started

  • WSJ CIO Online
  • June 19, 2012
  Authors: John Lucker, Jenny Wilson

• Leveling the Playing Field – Business Analytics for Mid-Sized Companies

  • Deloitte
  • July 2012
  Authors: John Lucker

• Delivering Analytics – The CFO’s Role in Moving from Customer Analytics Insight to Action

  • Deloitte
  • July 2012
  Authors: John Lucker

• Telematics: Driving the Automobile Market Through Distruption

  • Deloitte
  • August 3, 2012
  Authors: John Lucker, Stephen Packard, Mark Hill

• Turning Customer Analytics Insight to Action: How CFOs Can Lead the Way

  • CFO Journal for the WSJ
  • August 16, 2012
  Authors: John Lucker

• Business Analytics: Six Steps to Getting Results

  • Baseline Magazine
  • September 6, 2012
  Authors: John Lucker

• Simpson’s Paradox: A Cautionary Tale in Advanced Analytics

  • Significance Magazine - American Statistical Association
  • September 2012
  Authors: John Lucker, Steve Berman, Leandro DalleMule, Michael Greene

• Book Chapter 6: Optimize Performance, Process, and Decisions Through Big Data

  • International Institute for Analytics-Pearson Education Inc.
  • September 2012
  Authors: John Lucker, Tom Davenport, Leandro DalleMule

• The Three Minute Guide To Big Data

  • Deloitte
  • November 2012
  Authors: John Lucker, Forrest Danson

• What Does Big Data Really Mean and How Do You Create Value From It

  • Deloitte University Press Video
  • October 2012
  Authors: John Lucker, Jim Guszcza, Elea Feit

• Elements of a Successful Big Data Strategy

  • Deloitte University Press Video
  • October 2012
  Authors: John Lucker, Jim Guszcza, Elea Feit

• Examples of Success with Big Data

  • Deloitte University Press Video
  • October 2012
  Authors: John Lucker, Jim Guszcza, Elea Feit

• The Scale Paradox – Analytics Disrupts the Size Factor

  • Deloitte University Press
  • March 2013
  Authors: John Lucker, Ryan J Renner, Jerry O'Dwyer

• One Minute Video – 6 Essentials for Business Analytics Excellence

  • Insurance Networking News
  • April 2012
  Authors: John Lucker

• Licensed Professional Scoring System and Method

  • United States Patent 8,036,919
  • Issued October 11, 2011
  Inventors: John Lucker, Frank Zizzamia, Alice Kroll, Karl Knable

  A quantitative system and method that utilizes data sources external to a company, and when available, traditional data sources, e.g., internal company information, to (i) provide an easily accessible means for matching criteria such as, for example, demographic needs, to a database that can quickly provide a number of potential recruits or customers and that can also be used to screen both current and prospective company employees matching the criteria, and (ii) generate a statistical model that can be used to accurately and consistently predict future profitability and productivity of licensed professionals.

• Commercial Insurance Scoring System and Method

  • United States Patent 8,145,507
  • Issued March 27, 2012
  Inventors: John Lucker, Frank Zizzamia, Peter Wu, Matthew Carrier, Dominic Tocci

  A quantitative system and method that employs data sources external to an insurance company to generate a statistical model that may be used to more accurately and consistently predict commercial insurance profitability (the "predictive statistical model"). The system and method are able to predict individual commercial insurance policyholder profitability on a prospective basis regardless of the internal data and business practices of a particular insurance company.

• Method and system for determining the importance of individual variables in a statistical model

  • United States Patent 8,200,511
  • Issued June 12, 2012
  Inventors: John Lucker, Frank Zizzamia, Cheng-Sheng Peter Wu, Raymond Stukel, Hrisanthi Adamopolous

  A method and system for determining the importance of each of the variables that contribute to the overall score of a model for predicting the profitability of an insurance policy. For each variable in the model, an importance is calculated based on the calculated slope and deviance of the predictive variable. Since the score is developed using complex mathematical calculations combining large numbers of parameters with predictive variables, it is often difficult to interpret from the mathematical formula for example, why some policyholders receive low scores while other receive high scores. Such clear communication and interpretation of insurance profitability scores is critical if they are used by the various interested insurance parties including policyholders, agents, underwriters, and regulators.

• Licensed Professional Scoring System and Method (Divisional Patent)

  • United States Patent 8,335,700
  • Issued December 18, 2012
  Inventors: John Lucker, Frank Zizzamia, Karl Knable

  A quantitative system and method that utilizes data sources external to a company, and when available, traditional data sources, e.g., internal company information, to (i) provide an easily accessible means for matching criteria such as, for example, demographic needs, to a database that can quickly provide a number of potential recruits or customers and that can also be used to screen both current and prospective company employees matching the criteria, and (ii) generate a statistical model that can be used to accurately and consistently predict future profitability and productivity of licensed professionals.

Websites:

• Simsbury Taverneers

Interests:

Vintage Base Ball

Groups and Associations:

Information Systems Audit & Control Association (CISA)

• 
  CIGNA Alumni
• 
  Deloitte.
• 
  Dwight Englewood School Group
• 
  Global Big Data and Analytics
• 
  Real Analytics: Talk about today's business analytics
• 
  Retail Industry Professionals Group
• 
  Shawmut Bank Alumni
• 
  Theta Chi Fraternity Alumni
• 
  University of Rochester Alumni