Book Image

Building Analytics Teams

By : John K. Thompson
5 (1)
Book Image

Building Analytics Teams

5 (1)
By: John K. Thompson

Overview of this book

In Building Analytics Teams, John K. Thompson, with his 30+ years of experience and expertise, illustrates the fundamental concepts of building and managing a high-performance analytics team, including what to do, who to hire, projects to undertake, and what to avoid in the journey of building an analytically sound team. The core processes in creating an effective analytics team and the importance of the business decision-making life cycle are explored to help achieve initial and sustainable success. The book demonstrates the various traits of a successful and high-performing analytics team and then delineates the path to achieve this with insights on the mindset, advanced analytics models, and predictions based on data analytics. It also emphasizes the significance of the macro and micro processes required to evolve in response to rapidly changing business needs. The book dives into the methods and practices of managing, developing, and leading an analytics team. Once you've brought the team up to speed, the book explains how to govern executive expectations and select winning projects. By the end of this book, you will have acquired the knowledge to create an effective business analytics team and develop a production environment that delivers ongoing operational improvements for your organization.
Table of Contents (14 chapters)
12
Other Books You May Enjoy
13
Index

AI in the education system

Over a decade ago, I was asked by the university where I did my undergraduate degree to review their new curriculum for teaching students the skills needed to be a business analyst. My input centered on the fact that there were no courses to impart communications skills and emphasize teamwork in the program. Reviewing the current course catalog, it appears that the suggestions I offered were added and remain in the program, and now, Ferris State University offers a program referred to as Data Analytics. [11]

I have spoken with administrators and staff members at the University of Illinois, Oklahoma State University, and the University of Michigan about data science, teaching data science, and preparing students for the changing world of data, data science, advanced analytics, and artificial intelligence. Clearly, my sample is small and limited to the university staff that I have been able to meet and talk with personally. What I have seen and observed is that teaching data science is being done most effectively and creatively outside the colleges of engineering. Engineering, unfortunately, has, in general, been slow to respond to the opportunities provided by AI.

The old…

The engineering curriculums are time tested and proven to produce graduates who excel in the disciplines required to be a successful engineer in the chosen field of study; fields like chemical engineering, civil engineering, mechanical engineering, electrical engineering, and many more. However, to be successful at the global, societal, national, and company levels, we need more qualified professionals than all the engineering schools in the world could produce each year.

Michael Webb of Stanford University, when talking about the need for universities to broaden their ability to produce well prepared graduates who can work in the fields of advanced analytics and data science, remarked:

New technologies create winners and losers in the labor market. They change relative demands for occupations, even as they improve productivity and standards of living. Understanding these distributional consequences is important for many purposes. For example, it allows policymakers to design appropriate education and skills policies, and helps individuals make good choices about what careers to pursue. [12]

The US and global educational system changes slowly, but it does shift according to the market. I have been working with New Trier High School for over a decade. Working as part of the advisory board, in collaboration with Jason Boumstein, we have reviewed and brought in courses related to engineering and artificial intelligence.

Tom Finholt, Dean and Professor of Information, School of Information, at the University of Michigan, has taken what was a program focused on library science and transformed the offering into a curriculum that focuses on teaching, training, and preparing students to be leaders in the fields of data science, UX design, and more.

Tom has moved the program away from the previous paradigm, that is, of forcing left-brained students to memorize and execute technical strictures and structures in a rigid and driven manner.

I experienced the old style of teaching in my undergraduate and graduate programs. It does not work for large segments of the student population. I remember sitting in my Introduction to Assembly Programming class as a freshman. My professor said something similar to, "This class will be hard; 50% of you will not be here after the midterm. If you are a computer science major, you will need to take this class as many times as needed to pass in order to remain in the computer science program." No comforting sentiments in that speech.

…and the new

Dean Finholt and his team have created a program and approach that is more inclusive and diverse in how it attracts, evaluates, accepts, and educates tomorrow's leaders in data science. I am very excited to see how this new approach increases the number and quality of people entering the fields of data engineering, data science, advanced analytics, and related fields of work.

One of the more accessible methods for people of all levels of interest is online learning. The School of Information at the University of Michigan is using Coursera to broaden their reach. The course—Programming for Everybody (Getting Started with Python)—has enrolled nearly 950,000 students and has garnered over 73,000 reviews with an aggregate score of 4.8 out of 5. The instructor, Charles Severance (also known as Dr. Chuck), was tasked with creating an introductory course for people who were creative, open, and possess the ability to learn in a non-traditional manner. [13]

I do not see much interest from the colleges of engineering in augmenting or changing how they are teaching students to be data scientists. As I said, my sample is very small and quite limited, but I do see a significant amount of innovation and change in business schools, newly created colleges like the School of Information at the University of Michigan, and other schools and universities to attract new types of students in new and innovative ways.

If we continue to believe that the only way to provide society with the talent and skills needed in the future is to push people through rigid, and in some cases, outdated curriculums while sitting in lecture halls listening to graduate students, we will not deliver for the students, our communities, and the world in general.

The main points that I would like you to take away from this section is that our education system needs to evolve, and whether you are an adult returning to school, a high school student preparing to attend university, a parent of a student about to attend, or in the midst of attending university, you need to look closely at the educational offerings and curriculum of the school or program you or your child will be attending.

The old ways of teaching what are considered traditionally technical skills and imparting a body of knowledge, in some cases, are outmoded. This means they will not work for the broad audience that society needs to attend and graduate from university, with the skills needed to be successful in data science and advanced analytics.

The education system is changing, but as you or your child are entering that system, you need to be aware of what the current offerings are and how they can prepare you or your child for the realities of today and the future.

We have discussed how the educational system of today needs to change to serve a broader audience in the future. Let's now turn our attention to how people who are drawn to analytics and analytical thinking are unique, and how we can best support our colleagues, coworkers, and employees in our journey to deliver value to our companies and societies through data and analytics.