(Feb. 26, 2014) – Most successful large organizations are organized by lines of business (LOB). This has been a very successful way to organize for the accountability of profit and loss. It gives LOB leaders autonomy to make decisions that directly benefit the bottom line of their LOB without having to worry too much about interference from other LOB. The key characteristic of this model was that the data collected during the revenue generation and cost management processes by different LOB remained mostly passive. It was stored as a record or the proof of the activity so that it could be reviewed, counted, audited and accounted at a later date like end of the month, quarter or year.
In the early 1990s, data warehousing started as a discipline which allowed organizations to centralize data from different LOB and actively use the collected data to help generate more revenue and manage cost. This made it very clear to the organizations that their data is their greatest asset and it cannot remain passive in some database. It must be moved from the operational systems to the data warehouses or data marts to allow for better decision making.
This discipline has now evolved to business intelligence which incorporates data warehouse along with tools and processes that allow end users to analyse data and predict outcomes in multiple ways, quickly and effectively. As great as this business intelligence strategy has been, it still has its limitation. It cannot analyse or make accurate predictions across lines of business because most lines of business have the autonomy to collect data in the format that was best suited for their specific group. This meant that the organization as a whole does not automatically have a harmonious and consistent view of the data that can be trusted to make important decisions.
In recent years some organizations have taken this a step further and attempted to harmonize the data across different lines of business. More and more, organizations are realizing that the ability to have a trusted view of their data across the LOB boundaries is essential to the success of their business. For some organizations this has been a strategy to improve customer experience, cross sell/up sell and cost consolidation, but others must do it to meet different regulatory requirements for their specific industry. There are several types of reference data that organizations are seeking to synchronize across LOB boundaries like customers, products, partners, suppliers, etc.
The need to have a holistic view of all customers across lines of business has existed for a long time, and various organizations have attempted to solve this problem with various degrees of success. The challenge has been that this is not only a technically complex process, but more importantly it forces the change to the culture of the organizations that has been operating comfortably with the autonomy of lines of business silos. It also raises security questions about the data as it becomes easily shareable throughout the organization, and in some cases, to external parties.
The solution is to design and implement a process and system that can address organization culture, technical complexities and data security. This process of consolidation of all customer information from various systems across all LOBs is called customer domain Master Data Management (MDM). There are two approaches to implementing the customer domain MDM, analytical and operational.
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