In my last post, I discussed a relatively simple business case scenario where an enterprise intends to implement MDM because their current process heavily relies on a third party supplier of customer data.
Typically, though, things aren’t quite that simple.
Today, let’s discuss a more complex MDM
As it was well explained by David Linthicum, building a business case begins with the definition of the problem domain. The drivers outlined in the previous section define most common high-level problem domains for MDM.
If your ROI and NPV estimates require a more detailed list of problem domains
From the business case methodology perspective, two high level approaches can be used to estimate an MDM impact: a traditional bottom-up approach or a less traditional Economic Value (EV) approach. But which is best?
Business processes that will be improved as a result of MDM vary by industry, company, program and even the phase of the MDM initiative. Still, there are common areas and processes that are typically improved by MDM.
At the very strategic level, the board of directors and CEO want to know how the equity value and market capitalization of the company change as a result of the MDM, MDM-empowered applications, big data and analytics.
About 50 percent of MDM programs are driven by IT organizations as an IT strategy initiative. This scenario makes MDM business cases more challenging since, typically, IT management cannot approach the business case problem with the same level of power and authority as business executive management
The concern about consumer data privacy has never been higher. For example, 86% of Americans are concerned with data collection from Internet browsing and how it is used, and 70% of Europeans are concerned about the reuse of their personal data. With data breaches and issues such as the NSA’s
Big Data promises to intelligently join and mine hundreds of millions, and even billions, of records for various applications that require trusted data about customers, products, locations and other entities. Without quantifiable and verifiable confidence in data, the information originated from
To help enterprises create trusted insight as the volume, velocity and variety of data continue to explode, IBM offers several solutions designed to help organizations uncover previously unavailable insights and use them to support and inform decisions across the business. Combining the power of
Master data management has been around for many years. Now, with the emergence of big data technologies, MDM is seeing a resurgence in popularity and importance. Rick Clements, program director of Master Data Management Product Marketing, explains why MDM is a foundational aspect of a big data