a great article by Jackie Roberts on data governance for Product MDM
This article captured a session presented at the recent conference of the Data Governance Special Interest Group of the Americas SAP User Group (ASUG) by Sally Cheadle, VP Enterprise Finance Organization Center of Practice for Baker Hughes. Read more
Business and IT alignment is a topic repeated ad nauseam. There seems to be a belief that the Holy Grail of IT is achieved once that alignment is in place. This belief applies strongly to Master Data Management (MDM) as well. Read more
Hub Designs is an associate member of SAP’s alliance program, and on September 23rd, Dan Power from Hub Designs will be speaking at an SAP virtual trade show being put on by SearchSAP.com and TechTarget.
This free virtual seminar is focused on best practices for maximizing SAP performance. The day long virtual event features expert presentations, live panels and expert networking opportunities to help you make the most of your SAP environment, and will cover the hottest topics in SAP right now – including business intelligence, virtualization, master data management and mobile technologies. You’ll learn tips that you can put into practice immediately and you’ll get unbiased advice for long-term strategy development. At this unique online event, go beyond the hype and get insight into the latest technologies and best practices you can use to improve operational efficiency in SAP environments.
Dan Power’s session will be at 1:30 pm EDT, and will cover topics such as:
- Definitions of master data management, data governance and data quality
- The five essential elements of MDM
- Why companies are doing MDM and what this means to you
- Getting started on an MDM roadmap
- Is your organization ready?
- Creating the MDM business case
- MDM software selection
- Some important best practices
For more information, please visit
, and to register, please click here.
Andrew picked up on my comment “If CRM and ERP platforms were better able to manage master data, perhaps we wouldn’t need MDM solutions.” He goes on to say that “these applications were designed in an era when there was no need to take account of information requirements ACROSS the enterprise.”
The operating assumption for most CRM and ERP platforms, unfortunately, was that you were going to run your ENTIRE business on them. This rarely, if ever, turns out to be the case, particularly if the business does a lot of acquisitions. One business unit or geography certainly. And the count may grow over time. But there are always going to be areas of the business “outside the pale” – not included in that particular CRM or ERP solution’s purview. This leads to silos of data, which create many problems in the management and analysis of information in the enterprise.
That’s why an MDM hub makes so much sense. It provides a neutral place for customer, product and other master data from all over the enterprise to be created, read, updated and managed. Increasingly, today’s CRM and ERP applications are being used in concert with a robust MDM hub. Even now, CRM and ERP products just aren’t designed to manage master data effectively. They don’t have the built-in data quality and data governance processes that are needed to ensure a single view of accurate, complete, timely and consistent master data across the enterprise.
You can read the article by Andrew White of Gartner Research at
The Gartner MDM Summit in Las Vegas wraps up today, and this morning I caught a session by Kalido’s President and CEO Bill Hewitt and Jonathan Starkey, the Director of Business Intelligence at AB InBev North America.
AB InBev purchased Anheuser Busch in 2008 to become the largest brewer in the world, with over 116,000 employees worldwide and $39 billion in annual revenue.
AB InBev sees master data as a foundation element supporting supply chain management (SCM), enterprise resource planning (ERP) and customer relationship management (CRM). All of that data winds up in a data warehouse and is used for reporting and planning. This shared focus on both reporting and analysis, and planning and forecasting makes up their philosophy on business intelligence.
This integration approach is being to bring together the Canadian and US operations gradually over time, but to integrate the SCM, ERP and CRM pillars of the US and Canadian operations of such a large enterprise realistically is going to take three to five years.
Turning more to the master data side of things, the first way AB InBev is using Kalido is to synchronize and cross-reference product and customer information across SCM and ERP systems. Secondly, they’re using Kalido to look for active exceptions across all of the various domains – between plants and products, between employees in HR and in ERP, between any two systems where master data is not in agreement. Thirdly, they’re using Kalido to kick off requests for new master data – new employees, new products, etc. that then get passed to various systems around the company.
The “real world” benefits from Kalido at AB InBev include procurement savings, strategic inventory optimization, overhead and budget tracking, people and resource movement tracking.
AB InBev went through a rigorous selection process, and selected Kalido in large part because of its ability to change rapidly as their business needs changed. Jonathan Starkey said ”Kalido does a very good job at managing change over time”.
I really enjoyed this session. Both Bill Hewitt and Jonathan Starkey did a great job, and it was enlightening to hear how a large global enterprise has addressed their MDM and business intelligence needs. Hub Designs recently became a Kalido partner, and one of our goals for this Gartner MDM Summit was to learn more about the company and their products, and this session definitely helped us do that.
For more information on Kalido, please visit www.kalido.com.
I’m attending the Gartner MDM Summit in Las Vegas, and this morning I caught a great session by Andrew White on the evolution from master data management (MDM) of product data to “multidomain MDM”.
Andrew started by talking by talking about the strong intersection of product MDM with enterprise resource planning (ERP), workflow, product configuration, and business rules. The market for product MDM is fairly healthy and is actually a little larger than the market for customer MDM.
The initial need to master product data usually arises from having too many copies of product data in different places around the enterprise. Then typically, product data quality issues need to be addressed, but that needs to be addressed as a continuing process, not as a one-time process.
Multi-channel commerce is known as the “sell side” of product MDM, and procurement is known as the “buy side”. There’s involvement with fulfillment and supply chain management, and with ERP and operations. There are many different silos that need to be connected and synchronized (one client I worked with last year had 175 different applications, systems and databases, most of which used or created product data in some way).
At some point, governance has to be addressed. Companies have to go from departmental or business unit governance to enterprise-wide data governance, and expand from single domain (typically customer) to multidomain (customer and product) master data governance.
Andrew mentioned the level of Product MDM adoption – there was software license spending of $432 million in 2008. Certain industries such as discrete and process manufacturing, communications, retailing, and healthcare providers are classified as “hot” according to Gartner (as of Q1, 2010). Retail in particular is almost post-recession. Healthcare providers has more awareness on the buy side.
A common scenario for some is to have a product MDM hub as a system of record, connected to CRM systems for sales & marketing and customer service, to PLM (product lifecycle management) as a system of reference, and to ERP systems (which need the data for their Item Masters). So the CRM, PLM and ERP systems are process owners, but the MDM platform provides the product and material master data, attributes, hierarchies and so on, for consumption by the other systems.
Andrew talked about how the inquiries he gets break down: ERP and MDM: 50%, product data quality: 33%, information exchange: 15%, metadata management: 10% and content management: 20%, and “can I use my CDI hub to master product data?”: 10%.
Andrew talked briefly about the current vendors in the product MDM space: the specialists (handling just product data) such as Hybris Software, Heiler, QAD, Pindar, Tribold, Requisite Technology, EnterWorks. He categorized Stibo Systems, Riversand and Tribold as being somewhere in the middle between specialists and generalists (handling other domains).
Oracle, IBM and SAP are strong on product MDM and customer MDM. Tibco and Informatica (formerly Siperian) are customer MDM providers that are moving towards handling the product MDM domain. Microsoft is entering the MDM space but their solution (when it is released later this year) is really suited more for analytical use.
And other vendors such as Data Foundations and Orchestra Networks can model any domain of data, including product data.
Through the end of 2013, you might need two MDM platforms. IBM has three MDM products (IBM InfoSphere MDM Server, MDM Server for PIM which handles complex workflow, and their recent acquisition of Initiate). Other strong vendors include SAP, Oracle and Stibo Systems.
The five-year market growth rate is projected at 18%. The Top Five products have 51% of the market. Vendors to watch include Teradata, INformatica, Tibco and Hybris.
Over the next 12 months, product configuration remains an unsolved problem. Companies typically define business rules all over the place. Over the long term, in MDM, that doesn’t work – those business rules themselves need to be governed centrally. The master data and the business rules both need to be governed. Successful product MDM requires business rules governance.
Reference data is another area – price is NOT master data but it behaves like master data in a lot of ways. It needs to be governed and managed. Business process management and its intersection with MDM is another area of development.
Data quality for product data has its foibles. You need to know where you’re starting from. Most importantly, data quality is not a once and done thing, it’s an ongoing process.
The product master data life cycle looks like: Author > Store > Publish / Synchronize > Enrich > Consume > Analyze.
The picture for the future – there are three main “provinces” for MDM: the “thing” province, the “party” province and the “place” province. But vendors typically have a history in a single domain.
Andrew gave a couple of great example of companies that went through the evolutionary process of going from a single domain of MDM to multiple domains over time.
Andrew closed with recommendations for people beginning their MDM process: create a vision of what could be achieved with a “single view of product data”, to start small but think big and deliver value early, and to define data and process metrics early and then to revise then as needed as you go along.
I’ve been a big fan of Andrew White for several years now, and I thought he did a great job today (as usual). He brings a great deal of analysis to bear on the questions involved in product MDM, and provides clarity and insight into where the MDM market is headed over the next several years. If you’re attending the Gartner MDM Summit in Las Vegas, or have a chance to catch his sessions at a future event, I think you’d find those sessions very rewarding.
Today, at the Gartner Master Data Management Summit in Las Vegas, Hub Designs and Equifax jointly announced a new product, Hub Designs Equifax Integration for Oracle, bringing the power of Equifax Commercial Information Solutions data to the Oracle E-Business Suite and Oracle Customer Data Hub platforms.
The solution smoothly integrates Equifax data into Release 12 of Oracle’s enterprise resource planning (ERP) and master data management (MDM) suites.
Hub Designs Equifax Integration for Oracle provides access to vital credit and marketing data in Oracle’s MDM and ERP modules including:
- Oracle Customers Online
- Oracle Sales Online
- Oracle Receivables
Equifax commercial information helps businesses to:
- Make credit decisions, expedite collections, reduce bad debt and pre-qualify prospects;
- Reveal linkage between related companies;
- Standardize name & address information and prevent duplicates;
- Enrich prospect and customer records with marketing and credit information from Equifax;
- Increase productivity by creating new parties and party relationships in Oracle automatically
The joint press release describes the solution in more detail, and a one-page overview is available as well. If you’re interested in learning more, please contact us via our web site or drop by Booth #7 during the exhibit hall hours at the Gartner MDM Summit.
This afternoon at Oracle OpenWorld, I attended a great session led by Darrin Pohlman, Enterprise Architect at LexisNexis and MK Rizwan from Infosys.
They talked about the enterprise transformation program at LexisNexis, and the strategic use of technology to enable and drive that transformation effort.
MK started by pointing out the constraints of the single, global instance application strategy. You’re constrained by the vendor’s application architecture, and not all the functionality is best-of-breed across the entire suite. There are inevitable customizations and extensions which pile up over time, which leads to ever-increasing Total Cost of Ownership. It’s difficult to introduce industry-specific functionality, and it takes a long time to introduce new business models or capabilities.
The trend recently has been toward unbundling of the packages through SOA integration such as Oracle’s Application Integration Architecture (AIA) and the accompanying Process Integration Packs (PIPs). Further trends include vendor consolidation – Oracle acquiring Siebel, Hyperion, BEA, etc.
Interestingly, MK mentioned the important of prioritizing master data management, which got my attention, and he mentioned that would be particularly as people started to migrate in the future to the Fusion Applications products.
They went on to talk about AIA, particularly foundation packs, process integration packs and direct integrations. The foundation pack provides shared services, design patterns and standards. It runs on Fusion Middleware.
Darrin discussed the pro’s of AIA: good reference model for building composite applications, standards-based, extensible for unique characteristics of your business, and where Oracle is eager to demonstrate successful implementations. On the con side, PIPs can be tightly coupled, and the versioning of the AIA foundation pack can depend on specific versions of Siebel and other Oracle applications. Also, there are change management considerations of the IT team. There are licensing and maintenance considerations as well.
LexisNexis is an early adopter of this technology but has to plan for multiple upgrades over the next 12-18 months.
The audience was very engaged and asked some great questions during the session.
I found the session very helpful in better understanding the underlying enterprise architecture and technology strategy that LexisNexis is pursuing, and how Oracle’s Application Integration Architecture fits into that strategy, and Darrin and MK did a great job in explaining the pro’s and con’s of the approach and the experience that LexisNexis has had with it so far.
Oracle showed a funny video today in Thomas Kurian’s keynote address on Day 2 of Oracle OpenWorld.
Using a fictional company with lots of systems and applications issues, Thomas walked everyone through how Oracle would solve a lot of those problems.
There were some great customer cameos from companies like Ingersoll-Rand and Office Depot. It was a little on the sales-y side, as Oracle keynotes can sometimes be, but it was well done and wasn’t over the top.
This session was a good reminder of the breadth and depth of Oracle’s offerings in the technology and applications space, and frankly it made my head hurt. I’m glad that Hub Designs specializes in master data management – the Oracle universe has gotten so big, it’s a little overwhelming for most people.
I’ll write more later today on the MDM track sessions.
We had a very successful webinar on Feb. 5th with Siperian, on the “Top 5 Reasons Not To Master Your Data in SAP ERP”.
A lot of organizations use SAP Enterprise Resource Planning (ERP) for their transaction processing, but struggle to manage their non-transactional (or master) data on customers, products, suppliers, etc.
These types of data typically require a separate Master Data Management (MDM) system – to streamline business processes, reduce costs, and increase revenue by creating a single view of the customer, product, or supplier.
To view the replay, please click here.
She pointed out that Andrew White of Gartner thought the webinar raises some good questions in his recent blog article.
Andrew White said “ERP might be a good place to master data. The real question for the user is this: where is the right source of master data for you?”
Andrew is on the right track. In the webinar, we’ll outline the differences between SAP ERP and Siperian MDM, and when it makes sense to have a separate MDM hub.
I think companies should evaluate whether their ERP system is helping them solve business problems involving master data – or causing them.
To register for the webinar, please click here.
Siperian, an innovative provider of Master Data Management (MDM) solutions, is teaming up with Dan Power from Hub Solution Designs on a webinar titled “Top Five Reasons Not To Master Your Data in SAP ERP”.
A lot of organizations use SAP Enterprise Resource Planning (ERP) for their transaction processing, but struggle to manage their non-transactional (or master) data, including customer, product, and supplier information. These types of data require a separate Master Data Management (MDM) system – to streamline business processes, reduce costs, and increase revenue by creating a single view of the customer, product, or supplier.
Dan Power will discuss the following topics during this 45-minute webinar:
- Why SAP ERP is not the right place to master data
- Why a separate MDM system is required for streamlining business operations
- How MDM and SAP ERP coexist
- The technical attributes, strengths and weaknesses of SAP and Siperian MDM products
- The requirements of an effective MDM system and best practices for implementation
This free webinar will be held on Thursday, Feb. 5, 2009 at 11:00 AM Pacific (y:00 PM Eastern), and will include a live question & answer session.
To register, please visit
If not Master Data Management, what?
Enterprise Resource Planning (ERP) – the “back office” – has been around forever, and the “customer master” function in most ERPs is adequate, but due to acquisitions, many companies have more than one ERP system, and some companies let major business units build their own separate technology architecture.
Customer Relationship Management (CRM) – the “front office” – was supposed to be a “silver bullet”, bringing businesses closer to their customers, delivering 1-to-1 marketing, and increasing sales.
And data warehousing and business intelligence were supposed to deliver performance management and analytics, enabling better decision-making and deep analyses, but have sometimes proven to be difficult to deliver and extend.
But to varying extents, all of the technologies failed to deliver on all of their promises.
So circa 2004, along came Customer Data Integration (CDI) and Master Data Management (MDM). I call it the “hole in the donut”. MDM takes information from source systems like CRM and ERP, and eventually passes it on to downstream applications like data warehousing and business intelligence. But a lot of magic happens in that “hole in the donut”.
Information is consolidated into an MDM hub, usually using service-oriented architecture based integration technology. It’s cleansed using data quality software and completed or enriched with third party information. And it’s managed by a data governance organization. For more details on the end-to-end MDM process, see our earlier post on the “Five Essential Elements of MDM“.
So that would give you the Single View of the Customer (or Product, or Supplier, or whatever data domain you were mastering).
And from there, most companies would, in fact, flow the consolidated / cleansed / completed information into a data warehouse or business intelligence application.
Organizations are waking up to this, realizing that they’ve got “the donut” i.e. key pieces of the puzzle (plenty of source systems, decent integration technology, tons of third party data) but no data quality tools and no central MDM hub.
If you want the Single View (the “whole donut”), you need to invest in those missing pieces.
I was reading a whitepaper by Aaron Zornes today (“2007-2008 Scorecards for Data Governance in the Global 5000 Enterprise”) and came across an interesting quote:
“Although many organizations have improved end-to-end business processes through CRM implementations, the challenge of developing a unified customer or product view has not been fully addressed by the application suite vendors. For example, enterprise CRM solutions such as Siebel Systems supposedly were to integrate sales, marketing and service functions but in reality provided mostly automation of the sales force with arduous and fragile interfaces between sales, service and marketing. Concurrently, enterprise resource planning (ERP) was marketed as the integration among accounting, manufacturing and distribution. In practice, large enterprises are now turning to MDM as the service-oriented architecture means of unifying both CRM and ERP individually as well to integrate the front office (CRM) and the back office (ERP) together. “
In my experiences over the past twenty years or so, the enterprise software implementations I’ve been part of have treated data and process integration as a “necessary evil”. Almost like a difficult proof in a college math class, where the professor takes you up to a certain point, and then as the class ends, calls out that “the rest of the proof is left as an exercise for the class”.
I’ve seen projects where several systems were supposed to be integrated but never were, or where the front office and back office were integrated through “manual integration”, i.e. manual re-keying of key customer and product information between the two systems.
Little wonder, then, that ERP and CRM investments in many cases failed to deliver their expected return on investment. And now large enterprises are turning to Master Data Management (MDM). Given that successful MDM implementations requires five essential elements (data governance, a hub platform, integration, data quality and external enrichment capabilities), the temptation is there for people to de-scope important aspects of MDM.
Just as critical interfaces were de-scoped from earlier ERP and CRM projects, we’ve started to see people trying to do MDM without data quality, and even without adequate integration.
But let’s collectively resist these temptations. MDM and data governance are “hot” right now because they offer the promise of accurate, complete, timely and consistent information across the enterprise.
If we start to compromise on the essential elements of MDM, or fail to address MDM’s interconnected nature of people, processes, technology and information by focusing only on the technology, then in the not-too-distant future, MDM will not only go through Gartner’s “Trough of Disillusionment”, but it will be largely discredited. The industry will miss out on some huge future opportunities, and global enterprises will miss out on the ability to invest in their people, redesign their processes, implement new technology for MDM and service-oriented architecture, and weave in external information to supplement their internal data.
We all understand the pressure in the corporate world to deliver results in one quarter or less, but let’s make sure our short term approach doesn’t compromise the long term vision so much that the longer term return on investment becomes unachievable.
“Data governance is critical to these master data management efforts and ultimately is the tipping point as to whether the MDM program’s business outcome achieves its intended ROI and long-term sustainability.”
So resist the temptation to identify the need for Master Data Management, and then immediately run out and engage a systems integrator to help you evaluate, select and deploy some MDM technology. Remember to invest (either up front or in parallel with your MDM selection and deployment) in defining a workable data governance organization with accompanying business processes.
By paying attention to the integration between data governance (i.e. the people and processes) and the MDM techology (hub platform, integration, data quality and external enrichment), you’ll dramatically increase your chances for the successful delivery of expected functionality and ROI, on time and on budget.
In an earlier article, we covered the similarities between ERP and MDM. In this piece, we want to touch on some differences.
Timing of the Data Analysis Stage: Unlike ERP, Data Analysis needs to come in the very first stage of an MDM project. Doing a data analysis (including data profiling) at the onset of an MDM initiative will help define the project strategy and scope. The discoveries from data profiling and analysis will lead you to identification of faulty business processes and outline the framework for how MDM will help re-engineer those processes.
Team Composition: The team makeup will be different for an MDM project than for ERP. You not only need the “business representation” from the individual source systems with which you are integrating, but you also need to create a Data Governance Council that can strategize and approve the “ownership” of data moving forward.
Multiple “Buy-ins”:As part of the MDM initiative, the “owners” of the source systems have to agree to let the Hub readfrom their systems, then match, enrich and deduplicate the data and then write back to the source systems. You have to ensure this expectation is clearly conveyed to the source system owners, and then get each individual owner’s buy-in to achieve the benefits of an MDM initiative. Do this right up front, no matter how painful, or your MDM initiative will face a huge risk.
Security and Access: Unlike an ERP system, you need to devise a data-level security policy and link it to role-based CRUD (Create, Read, Update and Replace) privileges. This may also lead to changes in some security policies of the source applications, leading them to expose or hide certain data. Given the high profile security breaches we’ve seen lately, this is likely to be a big focus area for your project. You can’t bring together sensitive information from all over the enterprise without making business owners very nervous, unless you completely nail down the security & access aspects of your project.
Define Post “go live” Key Performance Indicators (KPIs) for enterprise data: Life for a data steward begins after going live with the MDM project. Assuming the Data Governance Council has done a good job in creating the data steward organization with clearly laid out policies & procedures, it has to lay down a framework for measuring data quality and other KPIs and then deliver steady and consistent results. These measurements and results should be published and made visible across the enterprise to keep the data revolution going …
Today’s guest author is a colleague from Hub Solution Designs, Gaurav Arora. The above article is a great take on the subtle (and not-so-subtle) diferences between Master Data Management (MDM) and Enterprise Resource Planning (ERP). Best regards — Dan