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In this podcast, Matt Blumberg discussed his book Startup CXO, the insights it carries and shared how to build a thriving leadership that builds for tomorrow today. He sheds light on the importance of a good leader and how to achieve it effectively.

Matt's Recommended Read: The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers Ben Horowitz https://amzn.to/3edvsHV The Oxygen Advantage: Simple, Scientifically Proven Breathing Techniques to Help You Become Healthier, Slimmer, Faster, and Fitter by Patrick McKeown https://amzn.to/3k994TR

Matt's Book: Startup CXO: A Field Guide to Scaling Up Your Company's Critical Functions and Teams by Matt Blumberg , Peter M. Birkeland https://amzn.to/3AWuyJL

Podcast Link: iTunes: http://math.im/jofitunes Youtube: http://math.im/jofyoutube

Matt is the founder and CEO of Bolster, a new talent marketplace for on-demand executives and board members launched in 2020. Matt was previously Chairman & CEO of Return Path, the market leader in email optimization, from 1999, until its sale to Validity. Under Matt’s leadership, Return Path won numerous employer of choice awards including #2 on Fortune Magazine’s “Best Companies to Work for” list. Prior to founding Return Path, Matt founded the Internet division of MovieFone (777-FILM) and had previously worked in venture capital and management consulting. Matt is Founder and Chairman of Path Forward, a non-profit that was spun out of Return Path in 2016 whose mission is to empower people to restart their careers after time spent focused on caregiving. He is also the author of Startup CEO: A field guide to scaling up your business, second edition published by Wiley & Sons in 2020, Startup CXO: A Field Guide to Scaling Your Company’s Critical Teams, published by Wiley & Sons in 2021, and the forthcoming second edition of Startup Boards, to be published by Wiley & Sons in 2021 or 2022.

Timelines: 1:10 Matt's journey. 3:22 The need for Bolster. 6:11 Tenets of a successful startup. 8:08 The kind of leadership required for a successful startup. 11:08 Best practices building a successful culture for a startup. 13:27 Pitfalls in leading a startup. 16:40 Qualities of a successful leader. 18:48 Tenets of a good leader in a startup environment. 22:00 Differentiating team expectations in small, mid, and large organizations. 24:06 Tips on grooming leaders in an organization. 25:47 The idea behind the book "Future of Thriving Startup CXO". 30:27 Research behind the book "Future of Thriving Startup CXO". 32:48 Picking the right authors for the book "Future of Thriving Startup CXO". 35:42 How does the on-demand leadership model fit into the life of a startup? 40:39 The role of technology in getting further access to leadership talent. 41:43 The future of leadership. 43:40 Rapidfire with Matt. 45:32 Matt's success mantra. 48:50 Matt's favorite reads. 50:20 Closing remarks.

About TAO.ai[Sponsor]: TAO is building the World's largest and AI-powered Skills Universe and Community powering career development platform empowering some of the World's largest communities/organizations. Learn more at https://TAO.ai

Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapter starts with conceptual background information about the techniques, includes multiple examples using R to achieve results, and concludes with a case study. Written by Matt and Joshua F. Wiley, Advanced R Statistical Programming and Data Models shows you how to conduct data analysis using the popular R language. You’ll delve into the preconditions or hypothesis for various statistical tests and techniques and work through concrete examples using R for a variety of these next-level analytics. This is a must-have guide and reference on using and programming with the R language. What You’ll Learn Conduct advanced analyses in R including: generalized linear models, generalized additive models, mixedeffects models, machine learning, and parallel processing Carry out regression modeling using R data visualization, linear and advanced regression, additive models, survival / time to event analysis Handle machine learning using R including parallel processing, dimension reduction, and feature selection and classification Address missing data using multiple imputation in R Work on factor analysis, generalized linear mixed models, and modeling intraindividual variability Who This Book Is For Working professionals, researchers, or students who are familiar with R and basic statistical techniques such as linear regression and who want to learn how to use R to perform more advanced analytics. Particularly, researchers and data analysts in the social sciences may benefit from these techniques. Additionally, analysts who need parallel processing to speed up analytics are givenproven code to reduce time to result(s).