The University of Virginia's Darden-Data Science Collaboratory for Applied Data Science in Business (DCADS) is sponsoring a research fellowship to advance our understanding of business leadership in a future where data and technology are pervasive and analytical expertise is necessary for individual and organizational success.  

The explosive growth of data and technology presents challenges and opportunities to leaders in all fields. In medicine, physician leaders must master new sources such as genomic data and integrate disparate information from electronic health records in the exam room to deliver evidence-based care. In government, civic leaders are faced with mountains of information from inside and outside government on every substantive issue and subjected to perceptions that spread with lightning speed among constituents, regardless of their accuracy. In law, legal leaders apply new tools, which increase fairness but have unintended consequences that are poorly understood and navigate laws and regulations from another era that are wholly inadequate in today’s data and technology-intensive world. Similarly, in business corporate leaders must deal with myriad impacts of this heretofore unchecked explosion.  

In business, the explosion of data and technology has changed nearly every major activity, from marketing and selling to customers, sourcing materials and producing products, managing investment and financial resources, and hiring, developing, and evaluating employees, to the very fundamental actions of communicating, managing, and making decisions every day. In many ways, the very nature of business leadership may be changing as a result of the volume of data produced by, or available to, leaders in business and the near ubiquitous access to the technology tools needed to use or misuse it.

The DCADS Fellowship in Analytical Leadership is designed to foster exploration of the leadership challenges and opportunities that result from these dramatic changes with an emphasis in two areas: leading analytics and leading analytically.  

Leading analytics should explore the leadership of analytical functions and departments in a corporate setting. This responsibility is increasingly in the hands of a designated executive, often titled Chief Analytics Officer or Chief Data Officer, which is a defined role at slightly more than half of Fortune 1000 companies. Understanding the unique leadership challenges of this new role and the essential characteristics and behaviors of the leaders who fill it successfully is an important focus.

Leading analytically should examine the changing nature of business leadership, in its many and varied forms and levels, in a world where data and technology are ubiquitous and essential to business success. In taking a broader look at business leadership as a discipline, the impact of data and technology should be considered in the context of established approaches to understanding the topic of leadership and through new avenues of inquiry that are uniquely suited to address the dramatic changes that are taking place.

The Fellowship in Analytical Leadership is intended to support multidisciplinary research efforts by scholars and/or practitioners from a variety of disciplines, including data science, leadership, management, economics, psychology, public policy, and business, focused on the problems and opportunities of analytical leadership.

Several representative examples of topics that are of interest are shown below.  These examples may be incorporated in DCADS Fellowship proposals, but they are listed here primarily to serve as guidance. They are not intended to limit the scope or focus of proposed research in any way.  

Examples include:

CAO/CDO Role, Organization, and Relationships

Examine contemporary role design, organization structure, and formal and informal relationships and their association with success of analytical individuals, teams, and organizations.

Profile and Preparation of Successful Analytical Leaders

Explore the characteristics of successful analytical leaders, including personal attributes, education, experience, and others, and identify drivers of and pathways to success.

Existing Theories of Leadership or New Approaches Needed

Assess existing theories of leadership to determine how and to what extent they consider the impact of data and technology competencies on leader behavior and success. Suggest new approaches that may better explain the path to successful analytical leadership.

Becoming Analytical

Understanding the journey to embrace analytical competencies and transform the way leaders think, work, and make decisions, at multiple levels including the individual, team, and enterprise.

Footnotes: 

1 Taylor, P. (2022). Total data volume worldwide 2010-2025. Statista.
2 Brown, S. (2020). How to build a data analytics dream team. MIT Management Sloan School.
3 NewVantage Partners (2021). Big Data and AI Executive Survey 2021.