Posted on June 9, 2010
Even coming from a vendor (IBM), this Resource contains helpful information on MDM including: Introduction to MDM and MDM silos, examples and benefits. Ten pages of MDM goodness.
Resource: Master Data Management: Looking Beyond the Single View to Find the Right View
Source: IBM
MDM Governance Resource Guide Section: Master Data Management Explored
Posted on June 4, 2010
An interesting look at trends that highlight the value and inevitability of MDM. From the Resource, here are the four trends that “point to MDM, making it inevitable”: 1) Data integration is booming, 2) Integration is more likely than migration and consolidation, 3) Virtualization is on the rise, and data virtualization is a subset of this trend, and 4) Many companies are still on a quest for a single view of customers and products.
Resource: Master Data Management is Inevitable… So Get Ready
Source: Philip Russom, TDWI
MDM Governance Resource Guide Section: Master Data Management User Readiness and Adoption
Posted on May 27, 2010
“…the main objective of master data management is to embody the core services necessary to support business applications’ needs to access a high quality, synchronized, and consistent view of uniquely identifiable master data objects that are used across the enterprise.”
Resource: Hit the Ground Running with Operational Master Data Management
Source: David Loshin, Knowledge Integrity
MDM Governance Resource Guide Section: Master Data Management – What is it?
Posted on February 2, 2010
A technical Resource that presents the concept of an MDM Reference Architecture as an integral tool in successful MDM implementations. From the Resource:
“The MDM Reference Architecture is an industry- and product-agnostic reference architecture that supports implementing the multiple methods of use (collaborative, operational, analytical) for MDM and multiple implementation styles (registry, coexistence, transaction style). It enables the ability to design business solutions incorporating MDM capabilities.”
Resource: An Introduction to the Master Data Management Reference Architecture
Source: Martin Oberhofer and Allen Dreibelbis, IBM
MDM Governance Resource Guide Section: Master Data Management Best Practices
Posted on January 29, 2010
Master Data Management Defined: MDM is a set of disciplines, technologies, and solutions used to create and maintain consistent, complete, contextual and accurate business data for all stakeholders (users, and applications) across and beyond the enterprise.
Resource: Dow’s Master Data Management Business Processes | PDF
Source: Jim Whyte, Dow Chemical
MDM Governance Resource Guide Section: Master Data Management – What is it?
Posted on January 29, 2010
“An MDM layer enables companies to realize internal efficiencies by reducing the cost and complexity of processes that use master data (through fewer code clashes, less data duplication, better control over business processes, and so on). It reduces manual translation and analysis to improve repeatability and speed to insight. An MDM layer improves the ability to share, consolidate, and analyze business information quickly, both globally and regionally. And it makes it possible to rapidly assemble new, composite applications (software that combines the elements of a business activity in a coordinated application and user interface) out of accurate master information and reusable business processes. Other MDM benefits include increased revenue (for example, from providing more accurate and comprehensive information to the right customers at point of sale) and regulatory compliance.”
Resource: Master Data Management
Source: Daniel Druker and Robert Rich, IBM Database Magazine
MDM Governance Resource Guide Section: Master Data Management Benefits
Posted on January 29, 2010
Four signs of bad data:
1) Discrepancies: duplicates and obsoletes have crept in swelling the inventory size above the expected level.
2) Items are difficult to find: trouble locating the right item. Even suppliers can’t locate them with the given information.
3) More non-contract spend: they can’t be located here, so go get them at expensive off-contract price.
4) Spend is out of control: Many invoices from suppliers do not match to POs.
Source: Krishna Shastry, Grihasoft
MDM Governance Resource Guide Section: Master Data Management Best Practices
Posted on January 11, 2010
A review of best practices gathered from five enterprises who have successfully deployed MDM. While a bit topical, the guidance is sound. The best practices:
1. Get business involved — or in charge.
2. Allow ample time for evaluation and planning.
3. Have a big vision, but take small steps.
4. Consider potential performance problems.
5. Institute data governance policies and processes.
6. Carefully plan deployment.
7. Consider the transition plan.
Resource: Seven Master Data Management Best Practices
Source: Hannah Smalltree, SearchCIO.com
MDM Governance Resource Guide Section: Master Data Management Best Practices
Posted on January 5, 2010
A detailed look at the US Department of Education’s Enterprise Data Management project, including project objectives, business drivers, architecture and much more. From the Resource:
“EDM is a service to the business with the following goals: Support the improvement of enterprise analytics and Decrease the cost of and improve the quality of new development projects Focus on data as an enterprise asset.”
Link to Resource: No Data Left Behind: Federal Student Aid A Case History | PowerPoint Presentation
Source: Holly Hyland & Lisa Elliott, US Department of Education
MDM Resource Guide Section: Master Data Management User Scenarios and Success Stories
Posted on January 5, 2010
According to a report prepared by industry consultants A.T. Kearney, bad data leads to a host of corporate problems:
1- Companies lose approximately $40 billion, or 3.5% of sales, each year because of supply chain information inefficiencies.
2- Nearly 30% of the item data in catalogs used by retailers and manufacturers is incorrect. Correcting those errors costs between $60 and $80 each.
3- Nearly 60% of all invoices generated have errors; each invoice error costs enterprises from $40 to $400 to reconcile.
4- 43% of all invoices result in some form of deduction.
5- New product rollouts take an average of four weeks-in large part because of inefficient and error-prone approaches for exchanging and updating new item attributes in buyer and seller systems.
Link to Resource: Content Data ROI Issues
Source: A.T. Kearney
MDM Resource Guide Section: Master Data Management – Data and Stats
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