SagerĪn Introduction to Lean and Six Sigma for Law Firms– on JD SupraĪt the Intersection of Process Improvement and Project Management by Fred Esposito and Catherine Alman MacDonagh on Legal Executive Institute Why? Because we all recognize that lawyers are not necessarily the most qualified people to run a business.Ĭollaborative Improvement by Catherine Alman MacDonagh and Thomas L. The Lean Arm of the Law – Louisiana Law Firm Embraces Lean Six Sigma to Streamline its ProcessesĮlevateNext interview with Catherine Alman MacDonagh, CEO, Legal Lean Sigma Institute: Q: What do you predict will be the two biggest changes in the legal profession as of 2025 and why? First, in 2025, anyone can be a law firm owner. Mo Zain Ajaz, COO for Legal and GC at National Grid, recognised by the FT for his work in-house work, and founder of Lex360. Fred’s work has been published by the American Bar Association, Thomson Reuters and Bloomberg. Catherine MacDonagh, author of Lean Six Sigma for Law Firms and the founder and CEO of the Legal Lean Sigma Institute, Fred Esposito, COO of Rivkin Radler and financial, strategic and operatonal management executive.
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Interview with Legal Lean Sigma Institute – Panache Software Panachecast: This week we have a star-studded line up with three outstanding guests.Legal Management Talk: Learn how firms can foster efficiency to increase value to clients and gain competitive advantage.
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The Case for Improving the Timekeeping Process – A short tutorial from the Legal Lean Sigma Institute LLC (on how to develop a business case for improving a timekeeping process.On 13 July 2021, Centre for Legal Innovation launched a new Innovation and Legal Ops Leaders Special Interest Group (formerly the Chief Innovation Officers Forum) – part of CLI’s Legalpreneurs Lab – with this two-part workshop with Catherine Alman MacDonagh, CEO and Founder of Legal Lean Sigma Institute – WATCH HERE!.To access this complementary program led by Merry Neitlich and Audrey Rubin, please use passcode: cx1*Hy=6
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And, suppose, independent of the first sample, \(Y_1, Y_2, \dots, Y_m\) is another random sample of size m from a normal population with \(\mu_Y\) and variance \(\sigma^2_Y\). Suppose \(X_1, X_2, \dots, X_n\) is a random sample of size n from a normal population with mean \(\mu_X\) and variance \(\sigma^2_X\). Let's now recall the theory necessary for developing a hypothesis test for testing the equality of two population variances.