Many companies embark on Master Data Management (MDM) project in order to improve the quality of their information which has a ripple effect by impacting the quality of their Business Intelligence (BI) and Corporate Performance Management (CPM) initiatives to mention a few. However, the projects can deliver unsuccessful results if not carefully planned and executed, rendering them useless….and costing the proverbial arm and leg. However, there is a paradigm shift that can unlock the value of a MDM project – by taking a business process driven approach.
MDM is a formal initiative to improve and sustain the quality of master data, usually involving specific technologies, as well as the governance policies and process changes. But as with many similar initiatives, they are more than often not successful, leaving businesses disappointed and disillusioned in the expensive technology that is supposed to be the panacea to all their MDM challenges.
“The challenge for most projects is that the definition of master data varies from person to person, and company to company. This makes it very difficult to accurately scope and priorities these projects. Our approach makes this task simpler and is a prerequisite to making sensible technology choices” continues Allemann.
“Successful master data management implementations are those that have shifted from a technology/data driven approach to a business process driven approach, often enhancing the functionality that technology delivers. Business need to understand that a multi-domain, process driven approach is critical to achieving business returns.”
Process driven data management approaches, whether for data governance, data quality or master data management help companies to achieve another critical goal – managing data by business value. By focusing on business processes that support key business initiatives, users get returns quickly in areas that have the highest impact. For example, the Revenue Assurance process may be identified as the key process supporting a business imperative of “Reduce Debtor’s Days by 5%”.
This process may in turn require master data from multiple domains, including Customer, Channel and Product. However, it is unlikely that all Customer data attributes are necessary to support this process. So the project need not manage data that is extraneous to requirements cutting and can focus on the issues necessary to address the key challenge.
Gary Alleman, MD at Master Data Management, a South African provider of solutions for data quality, data governance and master data management, will be addressing this challenge at Software AG’s ProcessForum 2012 on the 6th of June 2012. The presentation titled “Master Data Management – a recipe for success” will discuss this paradigm shift and illustrate how this approach enables business returns by ensuring that technical implementations focus on the correct data.