(as of Jun 14,2021 00:18:46 UTC – Details)
Master the skills necessary to hire and manage a team of highly skilled individuals to design, build, and implement applications and systems based on advanced analytics and AI
- Learn to create an operationally effective advanced analytics team in a corporate environment
- Select and undertake projects that have a high probability of success and deliver the improved top and bottom-line results
- Understand how to create relationships with executives, senior managers, peers, and subject matter experts that lead to team collaboration, increased funding, and long-term success for you and your team
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.
What you will learn
- Avoid organizational and technological pitfalls of moving from a defined project to a production environment
- Enable team members to focus on higher-value work and tasks
- Build Advanced Analytics and Artificial Intelligence (AA&AI) functions in an organization
- Outsource certain projects to competent and capable third parties
- Support the operational areas that intend to invest in business intelligence, descriptive statistics, and small-scale predictive analytics
- Analyze the operational area, the processes, the data, and the organizational resistance
Who this book is for
This book is for senior executives, senior and junior managers, and those who are working as part of a team that is accountable for designing, building, delivering and ensuring business success through advanced analytics and artificial intelligence systems and applications. At least 5 to 10 years of experience in driving your organization to a higher level of efficiency will be helpful.
Table of Contents
- An Overview of Successful and High-Performing Analytics Teams
- Building an Analytics Team
- Managing and Growing an Analytics Team
- Leadership for Analytics Teams
- Managing Executive Expectations
- Ensuring Engagement with Business Professionals
- Selecting Winning Projects
- Operationalizing Analytics – How to Move from Projects to Production
- Managing the New Analytical Ecosystem
- The Future of Analytics – What Will We See Next?
From the Publisher
Analytics expert John K. Thompson
Building Analytics Teams
Learn to create an operationally effective advanced analytics team in a corporate environment
Select & undertake projects that have a high probability of success and deliver improved top and bottom-line results
Avoid organizational and technological pitfalls of moving from a defined project to a production environment
What are the key takeaways from your book?
Building Analytics Teams is focused on the practical challenges faced by people who are building and managing high performance analytics teams and the staff members who make up those teams.
Readers will gain a detailed understanding of how they can build, manage and grow a high-performance analytics team, and can refer to the book over time to understand what path to take in situations that may seem complex and confusing.
The key points are:
The relationship of the analytics leader with their peers and executives of the company is critically important to the success of the analytics team
Providing challenging and valuable work in the form of a personal project portfolio of work for a data scientist can and needs to be done to ensure productivity, job satisfaction, and value delivery
Analytics teams are different than any other team in the organization
What are the fundamental concepts of building and managing a high-performing analytics team?
It is critically important to remember that data scientists are creative and intelligent people. They cannot be managed well in a command and control environment.
Data scientists need a tailored portfolio of projects that they own and manage to have a sense of autonomy. If they have a portfolio of projects and can manage their time and effort, the productivity of the team will be much higher than what is typically seen in teams managed in a traditional manner. It is very important to realize that most analytics project fail at the point of where analytical models are to be implemented in production systems.
My book examines the process of building and managing a team from a holistic view. The book considers the organization framework, the required processes, the people, the projects, the problems, and pitfalls. The content of the book guides the reader through how to navigate these challenges and provides illustrations and examples of how to be successful.
Table of Contents
Overview of Successful & High Performing Analytics Teams
Building, Managing & Growing an Analytics team
Leadership for an Analytics Team
Selecting Winning Projects
Ensuring Engagement with Business Professionals
Operationalizing Analytics: How to move from projects to production
Managing the New Analytical Ecosystem
Future of Analytics Teams: what will we see in the next 50 years?