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

Analytical and production cycles and systems – initial projects

In the cases where the analytics team is simply looking to improve a well-known process (that is, a non-discovery oriented improvement process), the analytics team should be able to give the functional team, sponsors, and interested executives a fairly reliable estimate of when the analytics process will start and produce the desired model, application, or result. In the first iteration of approaching a business challenge, we should have a reasonably accurate sense of how long the complete analytical project and cycle will take.

Figure 8.3: The analytics cycle

In contrast, as we discussed above, discovery-oriented processes are different and will take more time, and it is notoriously difficult to estimate and predict when the discovery will be unearthed.

Also, as we discussed in the finance scenario outlined above, we need to be clear with our collaborators from functional teams that their deadlines...