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
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13
Index

Data or algorithms – the knee of the curve or the inflection point

We have reached, and passed, an inflection point in our engagement with data and analytics.

We have heard the arguments that algorithms and math are the seat or source of competitive advantage. We have been told that if you are smart, innovative, and own your own algorithm(s) or approach, then you have mastery over all your competitors and the road to success is nearly assured.

Also, we have heard, sometimes from the same experts who asserted the previous point, that the pathway to all success in analytics is through the ownership, control, management, and proactive use of data—large amounts of typically fast-moving data.

Why are we discussing data and algorithms now, as part of a chapter on organizational engagement? The topic is salient and relevant at this juncture in our discussion. I have had to refute the argument from functional managers numerous times, and I expect that you will as...