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

Outsourcing

In general, we are moving away from the "not invented here" model where organizations believe that they need to build everything themselves, but there are still pockets of this view. It is the opposite view of the situation described above where some executives think that everything can be outsourced. As with most things in life, the ends of the continuum are the extreme cases and, as such, are typically found in a smaller number of organizations.

In most cases, you can outsource portions of the analytical process. Let's break it down for clarity:

  • Easy to outsource: You can outsource the following activities with the lowest risk: data acquisition, data integration, data profiling, data loading, and data visualization steps are the easiest to outsource and can lower the overall cost of operations.
  • More difficult to outsource and success is difficult to achieve: Feature engineering can be executed by an outside vendor if the company you...