The Data Management Capability Assessment Model (DCAM) is a tool developed by the EDM Council to help organizations evaluate their data management practices and identify areas for improvement. By using this framework, businesses can ensure that their data is accurate, secure, and accessible, which can lead to better decision-making and improved performance. In this article, we’ll explore the key components of the model and provide tips for getting started.

Why is it important to assess your organization’s data management practices?

Assessing your organization’s data management practices is important for several reasons. First, it helps you identify areas where your data may be at risk, such as security breaches or data loss. Second, it allows you to minimise potential errors by establishing processes and policies for usage and building trust in the data being used to make decisions across your organization. Finally, it helps you ensure that your data is accessible to those who need it, when they need it, which can improve overall organizational performance. By using the Data Management Capability Assessment Model, you can take a proactive approach to managing your data and ensure that it is a valuable asset for your organization.

What is the DCAM?

DCAM stands for the Data Management Capability Assessment Model, which is a framework for data management and analytics developed by the EDM Council. It is a formal model to assess data management capability within the financial industry, and is pitched as “the industry standard framework for data management”. The framework consists of 38 required data management capabilities with 136 sub-capabilities, spanning objectives, questions, artefacts of evidence and criteria for scoring.

DCAM is based on practical experience from 150 participants from leading financial institutions in collaboration with the EDM Council. It is a capabilities-orientation framework that uses a standard scoring model to measure data management capabilities and progress. The scoring model evaluates engagement and processes with auditable evidence. The capabilities are organized into eight components, each with a different number of sub-capabilities. The components are:

1. Data Management Strategy which defines the framework for the data management program
2. Data Management Program and Funding which provides the justification for the program
3. Data Architecture which focuses on the core concepts of data as meaning
4. Technology Architecture which addresses the relationship with the physical IT infrastructure
5. Data Quality which establishes the processes for fit-for-purpose data
6. Data Governance which defines the rules of engagement and aligns stakeholders
7. the Data Control Environment which refers to the process by which the organisation’s data assets are managed to maximise value.
8. and Analytics management which covers building and maturing a robust data analytics capability

More details can be found on our training course page: https://www.masterdata.co.za/index.php/dcam-training-and-certification

Why is the DCAM important?

The DMCA model is important because it provides a structured approach to assessing data management capabilities. By using the model, organizations can identify areas of weakness and take steps to improve their data management practices. This can improve data quality, increase efficiency, and lead to better decision-making.

In addition, the DMCA model can help organizations ensure compliance with relevant regulations, such as the the Protection of Personal Information Act (PoPIA), General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA).

How is the DCAM model used?

The DCAM model is typically used through a series of assessments, which involve collecting data and feedback from various stakeholders within the organization. The assessments are based on a set of questions that relate to each of the six dimensions of data management.

The scoring model uses a scale of 1 to 6 to rate the maturity of an organization’s data management capabilities. The scale ranges from “Not Initiated” to “Embedded into the Culture of the Organization”.

DCAM is not a certification, but rather a model that organizations can use to assess their data management capabilities. However, DCAM Certification is provided to those who take a DCAM training course and successfully pass the DCAM exam.

After the assessments have been completed, the results are analyzed and a report is generated, which provides a comprehensive view of the organization’s data management capabilities. The report also includes recommendations for areas of improvement.

Benefits of using the DCAM model

DCAM is used to assess and identify the capabilities an organization requires investments in to mature their data management and analytics.

It provides objective metrics as well as peer group benchmark comparisons which can be presented to stakeholders to secure the necessary funding for the program. DCAM assessments provide demonstrable and auditable evidence to market authorities on the adoption of data management best-practice.

Compliance in any industry is greatly dependent on the accuracy of, and access to, data. DCAM directly maps to many compliance and regulatory requirements, such as the risk data principles of BCBS 239 and data privacy regulations such as PoPIA.

Furthermore, DCAM is used by various regulators in publishing their guidelines to the marketplace. So using DCAM often means that you are using the same framework as the regulators.

DCAM incorporates consistent terminology and definitions to resolve differences in meaning and ensure a consistent understanding of data concepts across lines of business and geographies. DCAM also includes standard definitions within the scoring models to produce objective outcomes as well as a Data Management Business Glossary for ongoing reference.

One of the benefits of DCAM is that it enables organizations to have trust and confidence that their data and analytics programs are built on industry best practices and have been proven across the industry. DCAM provides a consistent scoring model that organizations can use to evaluate their current data management capabilities and benchmark against their peers.

It also provides a roadmap for organizations to improve their data management capabilities and become more data-driven. DCAM is a valuable tool for organizations that want to improve their data management programs and meet regulatory requirements.

Other benefits may include:

Improved data quality

By identifying areas of weakness in data management, organizations can take steps to improve the quality of their data. This can lead to more accurate and reliable data, which can in turn improve decision-making.

Increased efficiency

Improved data management can lead to increased efficiency, as data can be retrieved and analyzed more quickly and easily.

Better decision-making

Improved data management can lead to better decision-making, as data is more accurate and reliable.

How do I start with DCAM?

Our DCAM training and certification program, delivered in partnership with the EDM Council, provides a comprehensive perspective on the capabilities needed to develop and implement a practical data management function.

The curriculum is organized into eight core components covering over 100 essential data management capabilities and sub-capabilities. Each capability is supported by a series of requirement statements including specific objectives, scoring guidance, implementation advice and artefacts needed for the evaluation of data management programs.

The latest DCAM v2 Course includes new capabilities for provisioning data to advanced analytics and AI/ML initiatives and includes data ethics.

Contact us for pricing and availability

Conclusion

The DCAM is a valuable tool for assessing an organization’s data management capabilities.

By using the model, organizations can identify areas of weakness and take steps to improve their data management practices. This can improve data quality, increase efficiency, and better decision-making.