How active data governance differs from passive data governance

an image featuring two contrasting street signs. One sign symbolizes "Active Data Governance" while the other sign represents "Passive Data Governance"

Active data governance is a modern, agile approach that focuses on supporting the people in your organization who work with and create data.

Active data governance means data verification happens before data is entered into the system, typically as soon as the data is collected. This helps ensure the veracity of data and that data quality meets the standards of the organization.

Active data governance also ensures that data meets quality standards as soon as it’s added to any accessible business database.

In the context of Customer Master Data Management (CMDM), active data governance plays a crucial role as it ensures the accuracy, consistency, integrity, and security of an organization’s master data. Here’s why active data governance is so important in CMDM.

Pretectum CMDM does this at three levels, first through the data entry screens, through bulk imports, and API interactions. The key to data verification is the way that you set up your customer master data schema.

Active customer master data governance ensures the accuracy of Master Data, establishing business data rules and processes for data quality management, and defining standards, validation techniques, and guidelines for data entry.

By enforcing these standards, organizations can ensure that customer master data is accurate and reliable.

Active customer master data governance promotes consistency in Customer Master Data by providing guidelines for data standardization, naming conventions, and business rules. By establishing common data definitions and formats, data governance ensures that master data is consistent across different systems and departments.

This approach maintains the integrity of customer master data by defining roles, responsibilities, and access controls to ensure that only authorized individuals can access and modify master data. By implementing data governance practices, organizations can prevent unauthorized modifications and data tampering, and protect against data corruption. Pretectum CMDM achieves this through a matrixed Role Based Access Control (RBAC) model.

Active customer master data governance addresses the security of your customer master data through established protocols for data protection, privacy, and compliance with regulatory requirements. Data governance ensures that sensitive information is appropriately secured, and access to master data is controlled based on user roles and permissions.

Active customer master data governance also facilitates improved decisions since customer master data serves as the foundation for strategic customer portfolio business decisions. By implementing data governance practices, organizations can improve data quality, consistency, and integrity, providing a reliable basis for analysis and decision-making, personalization, and customer interaction.

Active data governance is an integral part of Pretectum CMDM’s approach to customer master data management, ensuring the quality, consistency, integrity, and security of your customer master data, thereby facilitating better decision-making and operational efficiency.

In a passive CMDM system, these practices would be implemented in a way that minimizes active data manipulation, instead, the focus is on the passive collection and integration of data from various sources.

A passive approach can help ensure data accuracy and consistency, while also reducing the need for manual data management tasks. However, it’s important to note that passive CMDM still requires robust data governance and quality assurance processes to ensure the reliability of the data.

Customer MDM Maturity Model

In considering what is best for your organization, you need to consider several factors.

The first consideration is the relative maturity of data governance processes and data management organization within your business. Highly disparate systems with siloed ownership may lend themselves more to a passive data governance model.

Pretectum CMDM can support that federated approach to customer master data management. If the organization also has limited resources for data management, passive data governance can be a cost-effective solution as it requires less active management.

Another consideration might be the sheer volume of data. Active Customer Master Data Management (ACMDM) requires a good deal of manual interception of data issues. Where the data is sourced from other systems or organizations, applying ACMDM may be a tough ask relative to the needs of the business. If the underlying systems providing the data are reliable and produce high-quality data, passive data governance can be an effective approach.

Batched and bulk processing of customer master data may be the way to go. Either way; the Pretectum CMDM provides you with a postmortem on captured data and guides you to the customer master data that fails to meet your business data governance rules as defined.

Passive customer data governance can also be beneficial when dealing with complex data structures or data from multiple sources, as it can automatically reconcile discrepancies and ensure consistency.

In some cases, regulatory requirements might favor a passive approach, especially when it comes to privacy regulations that limit the manipulation of certain types of data.

Consider also, the approaches to the implementation and adoption of CMDM.

What’s your master data management style?

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In deciding what to do next, in terms of customer master data management, it is important to understand what your organization does with its master data and how it manages it.

I say, do next, because there has to be an implicit assumption that whatever you’re doing today, there is a good chance that you want to do what you do even better!

Establishing a good understanding requires an assessment of the “maturity” of the master data management function in your organization.

It’s suggested that using a Capability Maturity Model (CMM) is a good way of determining the degree of formality and optimization of existing operational processes. This includes identifying ad hoc practices and formally defined steps in the end-to-end process.

The end result may also be Key Performance Indicators (KPIs), managed result metrics (OKR measures) and active evolutionary optimization of the data mastery practice over time.

The CMM is based on a development model created in the 1980s for the U.S. Department of Defense which funded a study of data collected from organizations that contracted with the DoD.

The MDM maturity model, a derivation of the CMM, is a means of assessing the whole process of master data management including the data point of view and also focusing on the whole operational process.

No need to boil the ocean

Investopedia Definition

A common misconception is that master information consolidation is always “the best approach to master data management”. The reality is that different parts of the business have different needs and expectations around master data and around the customer master in particular. The idea that you need to “boil” the proverbial ocean of data that you have, to reduce your data to the essential most valuable nuggets that your business requires, assumes that you know the requirements of the business.

The stark reality is that even if you do manage to converge on a single source of truth for the whole organization, the way the different stakeholders curate, manage, maintain, use and disseminate the customer master, may well be wholly incompatible with the governance choices that you make.

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No one will deny the fact that operational inefficiency, unreliable operations reporting, customer dissatisfaction and regulatory compliance issues often have roots in inadequate data management.

Customer MDM Maturity Model

Further, the implementation of advanced analytics and reporting and an increased level of interest in the “digital everything” is forcing organizations to rework their data management model. Taking stock, then of what you do today is important in deciding what decisions you should take strategically and tactically to improve data management operations.

One opportunity lies in the Gartner MDM maturity model. This proprietary model is positioned to give data and analytics leaders a framework to measure and assess their organization’s MDM capabilities, create an MDM vision, and establish a roadmap to reach it.

MDM implementation styles PPT slide 2
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Master Data can be stored in several ways and implemented in a range of styles. It is considered that there are at least four popular master data management (MDM) implementation styles, and their different characteristics suit different organizational needs. Gartner popularises these four and again, it is important to understand, in the evaluation of your own organization’s data mastery setup, which of these is most aligned with the way your business operates.

Consolidation
Support for business intelligence (BI) or data warehousing (DW) initiatives. Often considered as a downstream MDM style. MDM is applied downstream of the operating systems where master data is originally created.

Registry
An index to master data that is authored in a distributed fashion and remains fragmented across distributed systems.

Coexistence
Master data authoring is distributed, but a “golden copy” is maintained centrally in a hub. The central system publishes the golden copy of master data to subscribing systems.

Centralized
When master data is authored, stored, and accessed from one or more MDM hubs, either in a workflow or transaction-based use cases.

Pretectum Approaches to Customer MDM
Pretectum supports the four main approaches to Customer MDM – CoExistent, Centralized, Consolidated and registry

In your self-assessment consider how mature your master data management is and which of these styles is most aligned with the way you work.

When you consider a solution like the Pretectum CMDM, we’re offering support for all stages of the maturity model and all styles of MDM deployment for the customer master. How you choose to do it is at your discretion.

We have best practices but in the end, the best practice may not be the best practice for your business!