Despite the hype and activity surrounding emerging data-centric roles, such as the chief data officer (CDO) and chief analytics officer (CAO), a surprising gap in data leadership exists for many organizations. Our data show that less than half of organizations have formalized data leadership in place, and more than one-third of them have no plans to establish it in the future. Since every organization has somewhat different goals and requirements, it is not that surprising that data leadership is not omnipresent.
However, a clear correlation exists between formal data leadership and the degree of success with business intelligence (BI) and data-related initiatives. Organizations with formal data leadership in place more frequently deliver expected business outcomes. The presence of data leadership also positively influences frequency of data-driven decision making and levels of Hyper-Decisive® maturity for trust in data. Organizations without formal data leadership risk a higher likelihood of unsuccessful BI initiatives and likely will drift further away from the goal of maximizing data-driven decision making.
Data leadership adds value and increases success of BI initiatives in several ways, including by:
- Improving the focus on governance of data—addressing quality, consistency, and risk issues, and increasing trust in data used in decision making
- Ensuring BI and analytics investments align well with strategic goals and desired business outcomes of executive leaders
- Guiding prudent and consistent investments in BI and data that leverage and optimize common capabilities
- Increasing communication and literacy, which in turn raise analytic and data skill levels in the organization
To get maximum positive impact from formalized data leadership, organizations need to determine what type of data leadership roles they need, where in the organization they should report, and what their core responsibilities will be. These roles must interact and collaborate with existing roles in the organization—such as functional leaders, data management teams, data science roles, and the BI competency center (BICC). Most importantly, all of these roles must align and “pull in the same direction”—in support of specific strategic business outcomes.
Data leaders can aid their organizations by developing strategies to implement and advance data leadership in line with business strategy. Many organizations start by setting up a new role, such as CDO or CAO, and then afterward figure out where those roles should focus and what they should do. This represents a sub-optimal approach. Instead, organizations should engage to ensure business leaders understand how data leadership can add value directly through supporting and enabling achievement of their strategic goals.
Making the value of data leadership tangible to business leaders is critical. To best achieve this, collaboratively develop metrics that express the value and influence of data leadership against specific business outcomes. Ideally, these metrics also will show how data-driven decision making adds value over ad hoc and intuitive decision-making approaches, leading to a more effective and Hyper-Decisive organization.
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