Data leadership is the most critical aspect for bringing data literacy within an organisation. Without a leader who understands data and uses it in the decision-making process, making organisation data literate is next to impossible. Leadership is a quality that every organisation needs.
A good leader can drive their team members toward achieving the goal that the organisation has set for itself. They lead by example by helping team members through the journey to attain the goals set. Similarly, data-driven leadership is crucial when the goal of the organisation is to develop data literacy.
A data leadership framework helps achieve a balance between the people, processes, technology, and data capabilities necessary to maximise data value. The five main areas of the framework include:
1. Access — Prepare data for use: How do we find, reach, and have the ability to work with the data that we need?
- Data security
- Data architecture
- Data wrangling
- Support, operations, and DevOps.
2. Refinement — Optimise data potential: How do we ensure sufficient data quality for our use? Do we have the right master data strategy?
- Data quality
- Master data
3. Adoption — Acting from data insights: How do we encourage participation?
- Data modeling and warehousing
- Analytics and reporting
- Interactive dashboards and visualisations
- System Integration
- Emerging data technologies.
4. Impact —Maximise organisation outcomes: How do we validate, measure, and expand the true organisation outcomes that data is having?
- Machine learning and Artificial Intelligence
- Measurements, metrics and KPIs
- Regression analysis and predictive modeling
- Organisation process automation
- Data monetisation.
5. Alignment — Engage stakeholders: What is missing on the people's side? How can we extend it to other areas of the organisation?
- Strategy, standards and policies
- Project and program management
- Marketing and communications
- Organisational training and building data culture
- Regulatory compliance.