A featured contribution from Leadership Perspectives, a curated forum for enterprise technology leaders, nominated by our subscribers and vetted by the CIOApplications Editorial Board.
Winshuttle
Data Management for Enterprise Applications in the Era of Digital Transformation and Advanced Analytics
Data is Becoming a Strategic Asset Best Owned by the Business
In this digital journey, most organizations understand the importance of data and are starting to treat data as a strategic asset. They recognize that just like other important enterprise assets, data should be owned by business teams such as marketing or supply chain, and not by the information technology (IT) organization.
The most important data that these business teams need to pay attention to is stored in enterprise applications, like ERP or CRM. These applications store critical enterprise data like financial data, customer data, and product data.
Data in Your Enterprise Applications Need to be Governed and Managed
To leverage the technology trends of e-commerce, machine learning, etc., data in these enterprise applications need to be accurate and timely. Poor data quality in these applications not only has a big operational cost, but can also prevent your organization from participating in digital business.
The number one reason for poor data quality is the lack of proper data governance and stewardship processes in the enterprise. Many enterprises still use manual data entry, while others use spreadsheets and email for many of their critical business processes. This leads to data errors, delays, and lack of confidence in the enterprise application data.
Master Data Verses Application Data
When organizations search for solutions for data stewardship and governance, most gravitate toward master data management (MDM) frameworks. Many have struggled with MDM because they assumed all data in the enterprise needed to be managed the same way. The technology and the practice of governance and stewardship with MDM led to too much work and not enough value.
It’s important to understand the difference between true master data and application data.
Organizations can leverage MDM and ADM technologies strategically to improve data quality in enterprise applications
As shown in the Figure below, true master data that should be managed by MDM are data that are shared between multiple applications. Gartner estimates that this represents only ten percent of the structured data in the enterprise. Application data makes up the rest of the data that’s needed for the business processes supported by the specific applications. While master data must be managed centrally by IT organizations, application data should be managed in a decentralized way by business teams.
Using MDM in Conjunction with ADM
Gartner defines application data management (ADM) as:
ADM is a technology-enabled discipline designed to help users govern and steward the application (reference) data required to operate specific business applications, such as CRM, ERP, or supply chain planning. Such data may include master data — even if there is a separate master data management (MDM) solution. It is implemented within the context of the specific application or suite, so typically it uses the same persistent data and data model.
An ADM framework provides critical data management capabilities like data maintenance, process automation, and data quality, which are not typically found in enterprise applications.
ADM can be used alongside MDM systems in an enterprise. While MDM is used by IT to centrally manage the critical shared data, ADM is used by distributed business teams to manage data in specific applications like ERP or CRM. ADM tools can be supported by the central IT team in terms of the infrastructure and security; however, the data management functions are carried out by the business teams using ADM.
For Single Instance ERP, Use ADMas a Hubless MDM
Many organizations who have a single instance of ERP as the central storage hub for all their data don’t experience any benefit from implementing MDM. These organizations need a more efficient solution than MDM to set up and manage ERP data with data quality embedded in their processes.
ADM can be considered a hubless MDM system and used instead of MDM. Hubless MDM systems leverage the central ERP system as the hub, and focus on the other data management capabilities – data maintenance, process automation, and data quality.
Digital Winners of Tomorrow
Organizations can leverage MDM and ADM technologies strategically to improve data quality in enterprise applications, and increase the level of trust and confidence in data. Improving data will shorten business cycles, reduce operational costs, and allow you to participate and thrive in the digital tomorrow.
Learn more about how to utilize the application data management framework to stay ahead in the digital economy in my new book “Application Data Management – Empower Business Teams to Get Data Right.”
