Building optimal scheduling models is difficult. Spending months developing the perfect optimal scheduling model by defining the problem, collecting the data, refining the model, enhancing the user interface and including customer feedback and then …
This summer, amidst the whirlwind of travel, I found time to revisit a topic close to my heart: the challenge of getting people to adopt and utilize analytical models. Dr. Wilson Price and I co-authored a chapter on this very subject in the first edition of a book, and I recently updated it for the second edition.
The Field Guide to Compelling Analytics is out everywhere! Just got my hard copy versions today in the mail. I think the book is the perfect size to fit into the same size pocket as you would use for the iPhone 14.
Field Guide to Compelling Analytics is written for Analytics Professionals (APs) who want to increase their probability of success in implementing analytical solutions. In the past, soft skills such as presentation and persuasive writing techniques …
This presentation attempts to answer that question by exploring all the areas of the application of analytics in sports. The final point the brief makes is that by using sports data to teach k-means clustering, students are more interested in learning advanced analytical concepts.
Why are people afraid of math? Can the mere mention of statistics bring gloom over a conference room?
This is a very large barrier for those of us that use analytics by bringing math and data together to provide insight.
In today's special Team CANA spotlight episode, our host Rob Cranston will be talking with a handful of active military and veteran TEAM CANA members, about some of the special military workforce transitioning programs that are available, how to get involved in those programs, what it's like making the transition to the civilian workforce, and how the team at CANA and the CANA Foundation are involved. A big thanks goes out to Hannah Wallace, Walt DeGrange, Cornelious Young, and Kenny McRostie for being part of today's Team CANA veteran spotlight interview.
This is an ongoing analysis project to quantify the effects of analytics on the big four US professional sports teams. The ESPN Great Analytics Rating in 2015 http://www.espn.com/espn/feature/story/_/id/12331388/the-great-analytics-rankings is used for the team analytics ratings. I had to give the Las Vegas Golden Knights a rating of 4 since ESPN never did the rankings again and the NHL decided to expand. The presentation has been presented at the 2017, 2018, and 2019 INFORMS Annual Meeting and at several MORS Critical Skills for Analytics Professionals (CSAP) courses. It was also presented for the NC State Sports Analytics Club in March of 2019 and at a Meetup.com event in April 2019. www.Spotrac.com is used for salary data. Cash salary is used for NBA, MLB, and NFL. The cap difference is used for the NHL. Teams are ranked from 1 (paying highest salary) to the last team (paying the lowest salary).
Analytics is wonderful since it can be applied to anything that has data. Everyone has interests that can be combined with analytics in unique ways to make them the world's leading analytics expert in that specific interest area.