For organizations struggling to manage the growing volume of product data, effective MDM provides a solution. MDM provides a unified repository of common data definitions that not only reduces data inconsistency but also paves the way for better customer experiences.
However, the lack of proper data governance practices can bring the entire MDM strategy crumbling down. That’s why organizations need to take an Agile approach to MDM that is collaborative and self-organizing in nature. Agile MDM projects are known to collate and maintain high-quality data. This approach is best suited to meet the changing needs of customers in a cost-effective and timely manner.
Let’s look at how poor data governance impacts enterprise MDM projects and how Agile can pave the way for a Governance MVP.
The challenge of data governance
A significant challenge confronting all organizations in the effective execution of their Master Data methodologies is Data Governance. The lack of Data Governance can be a major stumbling block in how organizations use data to support business outcomes. It can come in the way of the ability of the product content to meet precise standards and business rules. This can also greatly impact the control the organization has over the management of critical product data assets.
Although data governance can help in listing the set of data rules to be followed and defining processes needed to ensure compliance, it is a big challenge for organizations to implement:
- Management support: For organizations that do not have support from the management, implementing Data Governance becomes a major challenge. With no way to quantify the business value of their Data Governance initiatives and no executive sponsorship for enterprise-wide implementation, organizations struggle to derive the right outcomes from their Data Governance efforts.
- Data leadership: Many organizations fail to identify data owners who are accountable for the data being used across the enterprise. There is no one to work towards developing strategies across data security, usage, and retention. In the absence of the right data leadership, teams often struggle to classify data correctly – thus impacting overall Data Governance.
- Data documentation: Despite the various processes that organizations use data across, Data Governance takes a back seat without proper data documentation. With no information on what data needs to be collected, how it needs to be collected, who can access it, and what it will be used for, enabling governance becomes a real struggle.
- Roles and responsibilities: Organizations that have never set roles and responsibilities or built accountability on how data will be used also struggle to enable the right Data Governance. Since people are unaware of their roles, they fail to determine who is accountable for implementing and maintaining the Data Governance strategy overtime.
The power of Agile
Clearly, there is a host of Data Governance challenges that can prevent organizations from achieving success from their MDM projects. As responding to changing demands becomes a core business requirement – especially in an age of constantly increasing data volumes – addressing the difficulties with Data Governance requires organizations to take an agile approach to MDM. Such an approach centers around a Governance Minimum Viable Product (MVP), so organizations can keep pace with customers’ expectations. Since it evolves with evolving business and customer requirements, it helps in providing contextually relevant product data for an unbeatable customer experience.
Here’s how you can use Agile to build a Governance MVP and overcome the challenges associated with modern MDM projects:
- Define data structures and enterprise data definitions: The first step towards building a Governance MVP is to define data structures and enterprise data definitions and align them with the goals of your business. This means you need to understand your business requirements, define your initial scope, and benchmark it against your master data.
- Ensure the right data quality: For any MDM project to deliver optimal results, it is critical that business decisions be based on accurate and relevant data. This means you need to devise well-defined data quality standards that ensure consistency, completeness, and accuracy of data.
- Create the right metrics: Once you have the right data quality standards in place, you need to build the right metrics to measure every aspect of your data. Using modern BI tools is a great way to accelerate the implementation of your Governance MVP and ensure its long-term success.
- Define relationships: Another critical component of a successful Governance MVP is defining relationship hierarchies. Since the relationship between your business and the customers, suppliers, and distributors you interact with is different, with a robust hierarchy definition, you can maintain individual functional definitions while still facilitating a common enterprise-wide definition.
- Manage change: Given how quickly data changes, you also need to constantly monitor change and roll out processes that help you keep up with the pace of change. Make sure to constantly apply governance policies to changes affecting the data elements that are within the scope of your governance program
An agile approach to implementing a Governance MVP can significantly improve the success of your MDM project. So, embrace Agile today to drive growth, better manage risk, increase efficiency, and enable business transformation.