The COVID-19 pandemic has meant that data-driven decisions have influenced all our lives over the last two years. But decisions made without proper data foundations, such as well-constructed and updated data models, can lead to potentially disastrous results.

For example, the Imperial College London epidemiology data model was used by the U.K. Government in 2020 to justify lockdown policy decisions based on a forecast that 500,000 deaths would occur if no action was taken. But questions have been raised about these Data Modeling predictions and the need for such stringent lockdown measures in the early days of the pandemic.

The problem was not the data but how it was interpreted. The same issues occur for businesses.

All decisions are underpinned by data, so it is important for the right data to be available to decision-makers and for that data to be high-quality and trustworthy. Data Modeling enables this through a series of data models (conceptual, logical, and physical) that start at a high level, driven by the decision-maker’s business needs, and evolve into greater technical detail for how data is to be stored, organized, and managed. 

This creates a common language across an organization, which is the starting point for a “single source of truth” for data and the effective flow of data within an organization.

Data Modeling therefore:

• provides consistency in how to treat data across an organization (which improves data quality), and 

• unlocks the real value of an organization’s data that exists in the relationships between different types of data. It assigns rules to identify those relationships, again, all based around the decision-maker’s business needs. 

This consistency is essential for any data analytics, business intelligence, or artificial intelligence application that supports an organization’s business operations. Without it, an organization’s data foundations will be fragile.

The detail behind Data Modeling is highly technical and complicated and it is recommended that organizations turn to subject matter experts that have a deep understanding of metadata (which sits at the heart of Enterprise Data Management) and Data Modeling tools. For example, my own company’s Data Modeling tools have been used extensively by the U.K. Hydrographic Office to deliver a complex digital transformation project around maritime data. The benefits pay dividends once completed. This includes:

• Exploiting data as the most valuable asset in your organization: Data has significant value and, like any other asset, needs to be managed, maintained, protected, and utilized to exploit that value. Too many organizations sit on massive enterprise-wide data holdings simply not knowing where or how to start.

• Faster and better data-driven decisions: With a complete overview of an organization’s data holdings, the data model maps how a business leader’s requirements are being fed by the right data (or not). Data can be found much more quickly but, conversely, it means that: Redundant or missing data can be identified reducing the decision errors based on missing data, and poor data quality is improved, which means better decisions. Errors in decision-making based on poor-quality data are often a significant yet hidden cost in any organization 

• Underpin digital transformation with new digital business models: With more flexible access to the reliable data, new business models can be developed as part of a digital transformation process.

• Providing a common language: In a world of fast-moving technology and blurred lines of responsibility between a business unit, CIO, CDO, and CTO, using Data Modeling as a tool to strengthen coordination and communication, with a common language and understanding, should not be underestimated. 

• Creating a data-driven culture: Data Modeling is not a one-off exercise but needs to be part of a data-driven culture. As the organization evolves, so do business needs, and therefore so do the data models to ensure the data is organized (or re-organized) in such a way to continue to deliver those evolving needs.   

This journey does not need to be a long or expensive process and the benefits can quickly outweigh costs.