Master Data Management Resource Guide

An Introduction to the Master Data Management Reference Architecture

MDMSOURCE — Tue, 02 Feb 2010 12:00:59 +0000

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

Master Data Management – What is it?: Dow's Master Data Management Business Processes

MDMSOURCE — Fri, 29 Jan 2010 13:19:07 +0000

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?

Master Data Management Benefits

MDMSOURCE — Fri, 29 Jan 2010 12:10:08 +0000

“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

Four Signs of Bad Data

MDMSOURCE — Fri, 29 Jan 2010 12:00:42 +0000

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

Master Data Management Best Practices: Seven Master Data Management Best Practices

MDMSOURCE — Mon, 11 Jan 2010 12:11:46 +0000

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

No Data Left Behind: Federal Student Aid A Case History

MDMSOURCE — Tue, 05 Jan 2010 14:00:42 +0000

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

Content Data ROI Issues

MDMSOURCE — Tue, 05 Jan 2010 13:00:43 +0000

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

Enterprise Data Management Optimization

MDMSOURCE — Tue, 05 Jan 2010 12:00:33 +0000

As part of a deep, technical and incredibly well-crafted presentation on Enterprise Data Management, the author looks at the performance implications of supporting Centralized MDM vs. distributed repositories for MDM. From the Resource:

“Factors that require evaluation during planning Master Data Store: Hub vs. Spoke, Data Volumes, Data Volatility (frequency of changes), Data Timeliness, Query Volatility (% of ad hoc queries), Query Complexity, Cross Functionality, and User Concurrency.” See Slide 37 and be sure to read the speakers notes for additional MDM insights.”

Link to Resource: Enterprise Data Management Optimization [8MB PowerPoint Presentation]

Source: Dr. Boris Zibitsker, BEZ Systems

MDM Resource Guide Section: Master Data Management Best Practices