Challenges data and analytics leaders face in 2021

Mike Rollings, Distinguished VP Analyst Amid global uncertainty, seven in 10 boards of directors have accelerated their digital business initiatives, and it is impossible to succeed in digital without a focus on data and analytics. Some of the biggest challenges chief data officers tell us they are facing right now include:

• Establishing the vision for a data-driven enterprise and leading transformation
• Driving culture change and improving data literacy
• Treating data and analytics as assets and maximizing their economic value
• Defining a modern operating model that balances service delivery, collaboration and competency building

The desire to accelerate data-driven transformation is unprecedented. Our research helps clients succeed in these critical endeavors.

Accelerating digital business is top of mind for high-performing enterprises. D&A leaders should implement trust-based data sharing, internally and externally, to speed digital transformation. Digital transformation cannot exist without data. Yet many organizations inhibit access to data, preserving data silos and discouraging data sharing. This unnecessarily undermines efforts to maximize business and social value from data and analytics — at a time when COVID-19 is driving demand for data and analytics to unprecedented levels.

D&A leaders have a path forward by adopting the Gartner “must share data unless” model. The model has five steps to take, starting with targeting digital business outcomes and recalibrating risk to uncover the lost opportunities from failing to share data. Then focus on establishing trust mechanisms for data, including metadata, and for the data source the technology creating or transmitting the data, and the internal roles handling ingested data. The IT environment should then adapt to data sharing, recognizing it as a business necessity to enable digital business, including adopting adaptive data governance to maximize the benefits of sharing data. The final step is to engage in the augmented data ecosystem, leveraging increased data availability to create more robust analytics or to train AI algorithms in support of digital business. Organizations that promote data sharing will outperform their peers on most business value metrics, including accelerating digital business.

For each of the past three years, cultural challenges to the acceptance of change and poor data literacy have been among the top three obstacles to the success of data and analytics teams, according to respondents to the Gartner CDO Survey. Becoming a data-driven enterprise requires explicit and persistent organizational change management to achieve measurable business outcomes, and employees know their organization is serious about corporate cultural change only when they see their leaders changing their own behavior. CDOs need to promote cultural change and orchestrate “leadership moments” in which they act as role models, exemplifying new cultural traits at critical points. Central to their success will be the ability to guide the workforce by addressing both data literacy (“skills”) and data-driven culture (“will”). As long as they fail in this regard, they will continue to fall short in terms of delivering measurable business outcomes.

How can data and analytics leaders, both in IT and in the business domains:

1. Build a data and analytics strategy and operating model that can support and scale, measurable business impact?
2. Apply trusted (governance, ethics, privacy, …) data and analytics in their decision making?
3. Create a business case to support data and analytics monetization and innovation?
4. Develop a data and analytics-driven culture, literacy and employee behavior?

Organizations are looking to their CDOs and data and analytics leaders as central players in helping them to shift, accelerate and thrive amid unprecedented change and uncertainty – often in a cost constrained environment.  Developing the right data and analytics strategy aligned to business value that enables new and agile approaches and business models has become a top priority. Executing on the strategy by combining the right talent, processes and technology to operationalize analytics including AI at scale across the enterprise and beyond has become essential.  Along with establishing governed and trusted data, insights and AI, creating a data and analytics-centric culture where critical thinking and creativity are fundamental competencies are the biggest obstacles to success.