Scalable processes & organization

Data Fluency

Konstantinos Kattidis

Data Analytics Lead

The power of scalable processes

• A mature data ecosystem relies on efficient processes
• They ensure that as the organization grows, the way users work with data remains efficient and effective
• Processes cover everything from data collection and development of data products to insights communication and decision-making

Collaboration processes

• Data producers and data consumers collaborate to define data requirements and generate actionable insights
• Processes can establish feedback loops where data consumers provide input to data producers
• Such processes encourage collaboration, clear communication channels and ensure that data insights are relevant, accessible, and comprehensible

Quality control processes

 

• Quality control processes involve the use of data validation checks and automated tests to verify data accuracy and integrity
• Version control processes track changes made to data and code to audit and reproduce accurately
• Product deployment processes make sure the deployment of new data products is done without issues

Processes for sharing insights

• Processes to share insights from data products, aligning refresh schedules with business needs
• For example, a sales dashboard's data source scheduled to refresh before a 10 am sales review meeting, enabling timely decision-making
• Automated processes can trigger alerts when specific data thresholds or anomalies are detected in important KPIs

Process standardization

• Data-fluent data producers focus on the standardization of processes to enable scalability and efficiency
• For example, creating templates and standardized spreadsheet formats to make it easier to develop financial models and reports

The organizational structure

• It refers to how the teams and roles are structured to enable scalable decision-making

Centralized organizational structure

• Centralized structure where data expertise is consolidated within a single team or department

De-centralized organizational structure

• Decentralized structure where data experts are embedded within various business units
• Each unit has its own analytics team responsible for data activities specific to its function

Hybrid structure for data fluency

• Mature data-fluent organizations often utilize a hybrid structure that combines elements of both centralized and decentralized approaches
• It includes a central data team
• Simultaneously, data analysts are embedded within different business units

Let's practice!

Data Fluency