Alliance with AMB New Generation Data Empowerment
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BOSTON, 14-NOVEMBER-2008: Hub Solution Designs, a consulting firm that specializes in Master Data Management and Data Governance, announced that it has been accepted as a Services and Reseller Partner by AMB, the leader in In-Stream profiling and the source for SOA-based data governance and CDI/MDM Discovery solutions.
Steve Meister, president of AMB, stated, “It is satisfying that organizations such as Hub Solution Designs recognize AMB’s technological leadership in MDM discovery and management technology. Our SOA-based approach to delivering In-Stream profiling and Visual Match/Merge capabilities provide a unique differentiator for architecting, planning and implementing Master Data Management implementations”.
AMB’s solution’s quick installation and ease of use makes consulting firms and professional services companies gravitate to its use on large and small engagements for CDI/MDM, Data Warehouse, ERP, CRM and other Data Management projects.
Dan Power, founder & president of Hub Solution Designs, noted “Our clients are looking for robust data quality and profiling solutions with a short learning curve and a fast time-to-value. AMB provides that and allows us to quickly teach our clients how to profile and improve their data quality, as part of their Master Data Management and Data Governance initiatives.”
About Hub Solution Designs, Inc.
Hub Solution Designs, Inc. is a management & technology consulting firm which specializes in developing and executing high impact Master Data Management and Data Governance strategies. For more information, please visit www.hubdesigns.com or blog.hubdesigns.com.
About AMB-PDM New Generation Data Empowerment™
AMB Predictive Data Management™ provides organizations a complete suite of tools to identify and remediate data anomalies. Through the delivery of the core PDM™ engine, SOA-enabled through the InfoExpose client toolkit, AMB allows technical and non-technical personnel to compare profiling results to a baseline, identify changes against the baseline to identify anomalies, drill to source data to quickly identify and plan source remediation opportunities, and report through Excel and other desktop tools organizations are already familiar with, sourcing data from its open repository. Unique to the industry is AMB’s ability to find anomalies in both textual and numeric data, thereby being the only complete suite in the marketplace to address the data quality opportunities organizations must address. For more information, visit www.predictivedatamanagement.com, e-mail info@predictivedatamanagement.com or call 1-800-928-0365.
###
Contact(s):
Dan Power
Hub Solution Designs, Inc.
+1 (781) 749-8910
powerd (at) hubdesigns (dot) com
Good News from Initiate Systems
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Initiate Systems sent out a press release yesterday, highlighting their performance in Q3 of 2008:
- achieved profitability
- positive cash flow
- year-over-year revenue growth of more than 50 percent
Also, Initiate signed up 10 new accounts in Q3, and now has a total of 177 customers.
It’s always nice to hear some good news, particularly in tough economic times.
Click here for the full press release from Initiate Systems.
Keynote at Oracle BI SIG Conference
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The Oracle Business Intelligence Special Interest Group, which is part of the Oracle Applications User Group, is hosting Desktop Conference 2008, its annual online conference, in mid-November.
Here’s a brief description:
“Join the Oracle Business Intelligence community in the only global, online business intelligence conference that addresses business intelligence and data warehousing topics related to the Oracle technology stack.”
The SIG president, Faun deHenry of FMT Systems, asked me to do one of the keynote sessions.
It’s titled “Master Data Management 101″ and will be covering:
- what is Master Data Management (MDM)?
- some useful MDM and Data Governance best practices
- what works and what doesn’t
- importance of a holistic approach to MDM
- how to get the political aspects right
- the relationship between MDM and Business Intelligence
The session will be held online on Wed. November 12th at 2:45 pm Eastern, 11:45 am Pacific. Click here to see the agenda and here to register.
MDM in Tough Economic Times
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It’s too early to tell exactly what effect the current economic downturn will have on the Master Data Management (MDM) space.
Software vendors are probably going to see at least a short term slowdown in orders, and consulting firms may already be feeling the effects in terms of canceled or delayed projects.
But unless you’re at one of the financial giants whose troubles are front page headlines, stay the course.
Master Data Management projects are typically so compelling that canceling them is like “burning the furniture”.
A good MDM strategy typically includes a strong business case, with “quick win” elements like increased revenue due to capturing currently missed cross-sell and up-sell opportunities, support for improved analytical marketing, and cost reductions through increased productivity and consolidation of systems and applications not needed after implementing the MDM hub.
I came across a great quote by John Radcliffe at Gartner:
“But there are many other pieces of MDM — like compliance, risk management, cost reduction — that aren’t nice to have, but are essential even if the economic climate is poor. We should see growth in these areas of MDM. They still need to get done and they actually help people during an economic slowdown.”
Perhaps I’m whistling past the graveyard a bit here, but although I’m sure MDM will be affected by global economic conditions, I’m hoping the effects will be less severe and of a shorter duration than other, more hard hit areas of the economy.
I’m planning to attend the Gartner MDM Summit on Nov. 17-19 in Chicago, and I spoke at the SourceMedia / MDM Institute event last week.
Those two events should give me a pretty good “pulse check” on how much impact current economic conditions are having on the MDM space. I’ll report back to you here on what I find, and please comment here to let us know your views and opinions on this question.
Importance of Metrics in Data Governance
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A critical component of any Data Governance program is the tracking of data quality metrics over the life cycle of the data. When a new record enters a Master Data Management system, it does not stay static; it undergoes updates until the last transaction (and beyond).
After the last transaction, at some point, it should be purged to maintain the freshness of the data. At all these stages, the information’s quality, security and compliance can be prone to compromise. A good data governance program should address measurement at these various stages of the data life cycle. Efforts must be made to build suitable metrics, as the organization progresses through the maturity levels of its data governance program.
Here’s an example. As part of the Data Governance program, a company identified one key metric as the “number of validated Ship To addresses”. Why? Because for a significant number of deliveries, FedEx would return the package and charge the company for giving an undeliverable address. And FedEx, as part of its business process, would not let the company know what was wrong with the address or where the correction was needed.
If a company does a large volume of shipments, even a small percentage of returns amounts to a substantial cost. When a data governance program was instituted, the company ensured that for all new customers’ Ship To addresses, the Customer Hub validated the new addresses via FedEx’s web services. FedEx has an elaborate address validation and other shipment-related web services available on its web site.
The company also ensured that any other projects that touched the customer master were aware of this integration. This was published as an official data governance policy. If any other program or user attempted to update the validated address, an approval workflow was initiated. Periodic system refreshes were also developed that would end-date the validated address and create a new validated Ship To address, using U.S. Postal Service’s National Change of Address service.
For historical customer addresses, the company started doing validations of the “defective” FedEx addresses first and after that set was processed, the remaining addresses were cleansed and validated.
The most important thing to remember is that unless visibility is provided thru a data governance metric, it’s easy for management to lose sight of your accomplishments. Therefore, it’s critical to build the data governance metrics first, even before embarking on an MDM project.
October Column in DM Review
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Here’s a brief excerpt from my latest “MDM Insights” column in DM Review.
A recent article in the Boston Globe titled “Tougher Consumer Data Rule Adopted: Businesses Must Improve Safeguards,” described how “state regulators released new rules … ordering businesses to better safeguard consumers’ personal information.” This got me thinking about the often-overlooked relationship between master data management (MDM), data governance and data security.
Companies that don’t have MDM capabilities yet usually don’t have a data governance organization either. But it’s a critical best practice to implement MDM technology in concert with developing a data governance organization (if not already in place).
Click on “Data Security in Master Data Management” to continue reading.
And please let us know your thoughts by commenting here …
Business Process Execution Language and MDM
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Most IT organizations have to support a wide variety of enterprise software. The legacy applications have proven their reliability over time, in spite of some performance or support issues. The new breed of Java or .Net applications can be complex to code, mostly because their business rules are not well-documented.
The end result is that to support a single business process like “Order to Cash”, multiple applications spread across multiple operating systems and databases are a reality for most IT organizations.
These applications can talk to each other either through point-to-point (tightly coupled) integration or through an Application-to-Application (A2A) (loosely coupled) integration. The latter is emerging as a new trend and is gaining ground among many leading IT shops.
Business Process Engineering Language (BPEL) enables an IT organization to build a single business process, spanning multiple applications thru A2A integration and maintaining the state of each business process instance. This is accompanied by a tool called Business Activity Monitoring (BAM), where one can monitor each activity for a given business process.
To connect BPEL to multiple applications, several approaches can be used. One is to use web services, another is simple file transfer, and a third approach is to use message queues to exchange XML messages. For connectivity to popular CRM and ERP systems, the leading BPEL vendors have come out with “adapters” that can connect their BPEL server to some popular platforms (like SAP, Oracle E-Business Suite, Siebel CRM, JD Edwards, etc.).
In any case, these servers provide tools to convert a native message into an XML message as well as perform transformations on XML messages.
The logic related to the business process resides in the BPEL server. If the business requires frequent changes to the logic, some BPEL vendors provide integration to a separate rules engine. The idea is that the business user must be able to change these rules in the rules engine using a simple interface. The changes then take effect directly in the BPEL engine. For working with external organizations, BPEL vendors are continually providing support for EDI, HIPAA and other standard formats.
The availability of Business Process Execution Language technology and its aggressive pricing has a huge implication for MDM adoption. It dramatically reduces the cost to integrate a new MDM hub with existing source systems.
Complex logic based on the source systems can now reside in the BPEL server and an entire business process (such as creating a new customer across multiple applications) can now be visible to the Data Stewardship organization. This is an exciting event! Please comment here about what other implications BPEL might have on MDM and its adoption.
Trip Report on Fall 2008 MDM Summit
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The Fall 2008 MDM Summit conference ended a couple of days ago. Here’s a quick trip report summarizing it.
I’ve attended the last six MDM Summit events in the U.S. and have spoken at five of them. I always enjoy them, because of the great job that SourceMedia and The MDM Institute do, because I enjoy seeing everyone I’ve come to know in the MDM world, and because of the new people I meet and the new ideas I pick up.
This year, I arrived via the Acela Express train from Boston, went straight to the Hilton New York, and attended Evan Levy’s pre-conference workshop on “Best Practices for MDM Delivery: Lessons from the Trenches”.
Most people who attended one of the pre-conference workshop came to the Experts and Analysts Panel, with Jill Dyché, Aaron Zornes and myself, moderated by Jim Ericson, Editorial Director of DM Review. The panel was a lot of fun. I’ve known Aaron for several years and continue to appreciate the quality and depth of his analysis. Jill’s insights were right on the money as usual, and Jim did a great job moderating and guiding the discussion.
After the opening night reception in the exhibit hall, I ran into a friend and fellow consultant, Mani Kumar Manda from Rhapsody Technologies. We went to dinner with Christopher Dwight, Director MDM Field Strategy from Oracle’s Master Data Management team. We had a great time, and talked about Oracle’s Hyperion Data Relationship Management solution and the upcoming Oracle Applications Users Group COLLABORATE 09 conference. Mani and I are involved in planning the MDM track of that conference.
The next morning, I attended Aaron Zornes’ keynote “Milestones on the MDM Road for 2008-2009″, which I particularly like as a way to stay current on developments in MDM over the past six months.
Tony Fisher from DataFlux gave a great talk on “Stop Kicking the Tires and Start Your Master Data Engine”. I first met Tony at the Fall 2006 event, and I chatted briefly with him afterwards about Hub Solution Designs’ interest in becoming a DataFlux partner.
Next was Pascal Laik, VP of MDM Product Strategy at Oracle. I’ve known Pascal for several years, since he took over for Ronda Krier in that position. Pascal laid out Oracle’s strengths in the manufacturing, telecommunications, retail and financial services industries, and included an interesting but apocryphal story about the “Battle of Ulm”, where the Russian army showed up 12 days late for the battle due to the difference between the Gregorian and Julian calendars.
Bence Gazdag also spoke about Oracle’s internal MDM efforts, and I later bumped into my friend Bill Miller, Oracle’s Director & Global Solution Owner for Data Quality Management, who was supposed to deliver that part of the presentation.
The last keynote before lunch was by Chris Lucas from D&B and Kim Fahey, Senior Director of Information Architecture at R.R. Donnelley. Kim did a great job describing Donnelley’s MDM journey and the growing value they’ve gotten from their implementation of Purisma.
I had a quick lunch, then headed off to a session on “Best Practices in DG, DQ & Identity Resolution” by Alex Bentley from Initiate Systems and Scott Drummond from Grange Insurance. This one I really enjoyed – down-to-earth delivery by Scott, and lots of good “lessons learned”.
I spent a fair amount of time Monday in the exhibit hall, talking to the different vendors, gathering more information, and seeing old friends working for various companies. I went to the end-of-day reception again, then headed out to a great dinner at the Blue Water Grill with Initiate Systems.
Tuesday was a bit of a blur. I had a couple of meetings in the morning, then went to lunch with Siperian at a great Venetian restaurant named Remi near the Hilton.
In the afternoon, I caught the “Global B2B Hierarchy Management in the High-Tech Industry” session by Jesse Weissman from EMC. Jesse did a great job describing the challenges and corresponding benefits of managing complex corporate hierarchies in EMC’s MDM environment.
The last session I caught was Eric Hansen from Nationwide Insurance, talking about “Data Governance and MDM – The Nationwide Experience”. This one was very well done too, with lots of good insights into the process of developing a vision for data governance in a large-scale Financial MDM project.
Aaron Zornes would want me to remind you about the virtual MDM Summit, which starts on Nov. 11th.
I don’t know the dates yet for next spring’s MDM Summit, but it’s usually in San Francisco and it’s one of my favorite events of the year.
If I met you, spoke to you, had lunch or dinner with you, or learned new things from you – thank you for making the Fall 2008 MDM Summit such a great experience!
Evan Levy’s Workshop at MDM Summit
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I really enjoyed Evan Levy’s session at the MDM Summit on “Best Practices for MDM Delivery: Lessons from the Trenches”.
I heard some great quotes today:
- “Measure data quality levels and continually publish them”
- “Knowing that data is bad is very different from knowing how to correct it”
- “MDM is all about comparing a source system record to the hub’s golden record and asking ‘is it better?’”
- “Do a few things and do them fast.”
- “We’re probably 2-3 years aways from the hubs being really mature and supporting applications smoothly. There’s usually a big impact on how the company has deployed service-oriented architecture.”
- “Do batch first, but don’t forget to design for real-time transactional use too. Get the data problems out of the way first.”
- “A lot of shops profile data during the design phase and never look at it again. Continue to profile during development, and profile the data after it’s loaded. Even profile your data as a production activity.”
Evan’s session was interesting, with a wealth of examples from his years of real-world MDM experience.
Highly recommended!
MDM Summit
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In a few days, I’ll be heading to the Fall 2008 MDM Summit in New York (Sunday, 10/19/08 through Tuesday, 10/21/08). It will be the 6th MDM Summit I’ve attended and the 5th one where I’ve spoken.
I’ll be on an “Experts and Analysts Panel” with Jill Dyché, Partner & Co-Founder of Baseline Consulting and Aaron Zornes, Chief Research Officer of The MDM Institute. The panel is on the first day of the conference (Sun. 10/19) from 5:15 – 6:00 pm. For more information, go to www.mdm-summit.com/MDM/agenda.html.
If you’re interested in meeting, just drop me a note at www.hubdesigns.com/contact_us.html.
It’s always fun to meet the great people who read this blog!
Share Your Knowledge at OAUG COLLABORATE 09
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Hub Solution Designs is a member of the Oracle Applications Users Group (OAUG), and I’m the OAUG Education Committee’s track manager for Master Data Management.
We’ve started planning next May’s conference, and we’re looking for strong papers on Oracle Customer Hub, Oracle Product Hub, and Hyperion Data Relationship Management.
Here’s the latest reminder from OAUG on the Call for Papers, which ends October 31st.
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Share Your Knowledge at COLLABORATE 09!
The Independent Oracle Users Group (IOUG), Oracle Applications Users Group (OAUG) and Quest International Users Group (Quest) invite you to share your Oracle knowledge at the premier annual conference for Oracle customers — COLLABORATE 09: Technology and Applications Forum for the Oracle Community, taking place May 3-7, 2009, Orange County Convention Center West, Orlando, Florida.
Submit a presentation proposal by Friday, October 31 to be considered to speak at this leading user-driven event and have the chance to:
- Share best practices and tested solutions for Oracle technologies and applications.
- Enhance your own Oracle knowledge through the peer networking and exchange.
- Learn from Oracle experts and leaders through other education sessions.
If you are an Oracle Applications professional with an interest in Oracle E-Business Suite, Hyperion, Agile, PeopleSoft, Siebel, Oracle Retail, Communications Billing and Revenue Management and MetaSolv Software, as well as applications technology, we invite your proposals for the COLLABORATE 09 — OAUG Forum.
For more specific information about COLLABORATE 09 — OAUG Forum, including tracks, specific industry- or product-related areas of emphasis, presenter requirements and the presentation submission process, please refer to the call for presentations on the COLLABORATE 09 OAUG conference Web site.
Attention Team Oracle! All Oracle employees interested in speaking at COLLABORATE 09 are to contact Michael Neuendorff at michael.neuendorff@oracle.com. Do not submit papers through the official COLLABORATE 09 call for papers!
We look forward to seeing you in Orlando!
Important Paper Submission Dates and Deadlines
- October 31, 2008, 11:59 p.m. EDT: Presentation abstracts due.
- January 12, 2009: Accepted presenters notified by the OAUG.
- January 23, 2009: Acceptance of the compliance agreement due.
- March 8, 2009: All presentation materials including white paper and presentations are due.
What’s in a Name?
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As part of implementing Master Data Management (MDM) for customer information, one needs to define the “customer data model” that will be deployed in the hub.
To do this, quite often, a company will conduct workshops to get agreement on the common definition of “the customer”. The participants are all the groups or departments that touch and use customer data. These may include Marketing, Sales, Finance, Customer Service (and sometimes Legal).
The objective of these workshops is to list out the entities that are in scope for the MDM project, identify the attributes which define an entity, the possible sources of data for that entity, the business purpose of the entity and the consumers of the entity. As a secondary objective, the next step is to define the relationships among the entities and if there is any need for hierarchical representation of these relationships in the hub. But all this is definitely not an easy task to accomplish.
As an example, take the “company name” attribute for a corporation. The Sales function defines the “company name” as the name on the customer’s business card. Legal, however, needs the legal entity’s name and any alternative names, DBAs or tradestyles. Finance may want to identify the corporation with its D&B-provided name (since credit reports may use that). Tax folks may need the previous names under which this customer has transacted. Customer Service gets the “customer name” from the installed base and Marketing gets it from an external list vendor.
So there you go. These are several different potential views just for “company name”. And you thought, agreeing on the “name” definition would be easy!
Similar issues surface when defining the address-related attributes.
By now, you may be asking yourself, “So, does this end up like spaghetti, with no easy way out?”
A better approach is to gather the customer data from various systems and profile that data before the workshops. Observe the variances in “company name” from various systems and build rules based on those variances. Typos can be weeded out. Standards can be designed and proposed to eliminate the “name duplicates”. Use examples proactively. Then based on these findings and the proposed standards, conducting these workshops will be a much smoother task.
Even after this, if there is no agreement, your data model may need multiple “company name” fields to represent the “name” attribute. The objective is to minimize the number of such occurrences.
Experts and Analysts Panel Discussion at MDM Summit
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I’m going to be attending the upcoming MDM Summit in New York on Sunday, 10/19/08 through Tuesday, 10/21/08.
I’ll be on an “Experts and Analysts Panel”, moderated by Jim Ericson, Editorial Director of DM Review, along with Jill Dyché, Partner & Co-Founder of Baseline Consulting and Aaron Zornes, Chief Research Officer of The MDM Institute.
The session will be on the first day of the conference (Sun. 10/19) from 5:15 – 6:00 pm, followed by the opening night reception in the exhibit hall.
I’m looking forward to it – Jim is really sharp, and I always enjoy hearing Jill’s and Aaron’s perspectives on the MDM space.
For more information, go to www.mdm-summit.com/MDM/agenda.html.
Customer Data Quality
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Quite often, an enterprise faces an event where it needs to load massive customer files into its enterprise information systems.
Examples include integrating a new subsidiary’s customer master with the parent’s CRM or ERP system, migrating to a brand new ERP, consolidating customers from various silos within the enterprise, importing partner files and their customers, etc.
Sometimes, attempts are made to programmatically improve data quality within a customer record, but because of tight deadlines, data quality across the file is usually not given serious attention.
IT’s thinking is usually that “We received 50,000 customer records; we uploaded 50,000 records – job well done!” But wait a minute, is that really true?
It is highly likely that duplicates exist within the file and the same customer is being loaded more than once. There’s also a possibility that the same customer already exists in your target system.
Multiple instances of a single customer can lead to end-user confusion, serious reporting errors and even to reduced efficiency and impacts to customer service.
A good approach is to be proactive about data quality and to plan for spending extra cycles correcting these types of problems in the customer files before doing the migration.
A simple tactic is to extract the existing customer records from the target system and run this file along with the legacy / source system data through an address validation and matching process. A number of vendors can do this task for you at a reasonable cost, ranging from 15 cents to 55 cents per record.
The next step is to separate the non-duplicates and load only these records in the target system. The duplicates are either managed outside the target system (by building cross-references in your data warehouse, for example) or, if your target system has a way to maintain cross-references, by uploading the cross-references only into the target system (typically an MDM hub or ERP application).
A major benefit of this approach is that the new records are genuinely new and have validated addresses for deliverability. This significantly enhances corporate data quality. Then, IT can say “We received 50,000 customer records; we uploaded only 40,000 records, the other 10,000 were duplicates – job well done!”
September Column in DM Review
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Here’s an excerpt from my latest “MDM Insights” column in DM Review.
After watching both the Democratic and Republican National Conventions I saw a pattern playing out that (believe it or not) applies to master data management (MDM) projects and ongoing data governance initiatives.
Just as a strong business case is usually important in getting initial funding, communicating your successes is critical to retaining it. But, it’s usually better to let someone else tell your story.
Click on “Taking Credit for Your MDM Success” to continue reading.
And please let us know your thoughts by commenting here …
Announcing an Intensive, Two-Day On-Site Seminar
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Attaining High Quality, Integrated Information
High quality, integrated master data is all that matters in your business/IT landscape. Sure, people, processes and technology are important. After all, they get the brunt of everyone’s attention. But in the end, superior business intelligence, smooth transactions and harmonious customer interactions all depend on the quality and usability of your master data.
Why This Seminar Program?
Hub Designs and Perera have teamed up to create this important, two-day on-site seminar program for organizations struggling with low quality, fragmented enterprise data. With over 40 years of combined experience, you can expect a new level of practical insight that is unavailable in any other forum.
Our goal is to bring unparalleled Master Data Management expertise to your front door. A blend of education and hands-on guidance, your organization will gain the knowledge to confidently undertake and succeed with your MDM initiative… and transform your enterprise master data into an appreciating corporate asset.
Agenda For Mastering Your Data
Together, we will explore the issues, challenges and opportunities associated with creating and maintaining high quality, integrated enterprise master data:
- Creating a business case for managing customer, product, supplier, financial and employee master data
- Analyzing the types, nature and severity of enterprise data quality problems
- Determining quality and integration requirements for enterprise master data
- Creating enterprise master data architecture and models
- Formulating a plan to correct and transform your existing enterprise master data
- Developing and embracing master data content and format standards
- Integrating and synchronizing master reference data within and across enterprise systems
- Identifying, evaluating and selecting MDM software and third-party data sources
- Designing data quality processes for continuous master data management
- Determining metrics for assessing, monitoring and certifying the quality of master data
- Organizing and managing a data governance and stewardship program
This program is geared to business, project management and IT personnel who are actively involved in Master Data Management (MDM), Customer Data Integration (CDI) and data quality initiatives. The ideal session brings together up to 15 participants from your organization to discuss the production, distribution, consumption and maintenance of enterprise data.
By conducting this program at your site, stakeholders have the flexibility to join program segments that are appropriate to their functional areas. We charge a fixed program fee so you can tailor attendance to your needs.
Schedule TODAY!
For more information or to schedule this two-day program at your location, please call us at 781-749-8910 or visit our web site.
Getting to the Single View
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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.
But if your MDM hub is missing, and you don’t have the data governance organization or processes, all of the above is going to be much more difficult, if not impossible.
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.
Structured vs. Ad Hoc Data Governance
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I was struck recently by the difference between companies that have a formal, structured approach to data governance, versus an informal, unstructured or “ad hoc” approach.
In many cases, companies with an ad hoc approach already have the right people, in the right places, doing the right things.
But it’s not formally part of their job description. They just do it because they know it’s the right thing to do, or that the company really needs it.
So they act as unsung heroes of data stewardship, cleaning up data manually, writing scripts to make data corrections in bulk, even working together in teams to do data governance tasks, without ever formalizing it into a data governance program.
I wrote yesterday about whether data governance should be located in the business (with support from IT) or in IT (with support from the business). It’s a natural tendency of business people to think that data management, since it involves computers, should be part of IT. And it’s a natural tendency of the IT people to think that only the business knows the subject matter well enough to manage it.
But wherever you stand on this question, I think it’s better to have a structured approach to data governance. Set up a data governance committee or team, define its mission and processes, and give them the technology tools they’ll need to achieve the mission.
Relying on an ad hoc or informal approach is risky. People take new jobs, go on vacation, or get burned out. So you can’t rely forever on the unsung heroes of data stewardship.
I’ve said many times that if companies treated their physical assets (like inventory or cash) the same way they treated their information assets (particularly customer data, for some reason), then people would be going to jail.
Start thinking about how your organization can improve its data governance maturity, or start a data governance function, if you don’t already have one. You’ll find that “when the student is ready, the teacher will appear”. In other words, once you start, if you remain diligent and patient, the rest of the organization will ultimately see the value of adding data governance to “how we do things here”.
Here are some good resources for further reading:
- “So You Want to be a Data Champion?” by Tom Carlock
- Wikipedia article on Data Governance
- The Data Governance Institute’s Data Governance Framework
- The Master Data Management Institute
- Data Governance Blog
Please let us know via a comment if you have any other resources on data governance you’d like to suggest.
Where Data Governance Belongs
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Both IT people and business people usually realize when data management issues are having an impact on the company. And senior executives are usually at least aware of the issues with important master data domains like customer, supplier and product, because they live with the end results of data quality issues every day.
But sometimes the business is reluctant to hire anyone to work on data quality or data governance. So here’s my question: is it better for the IT team to take that on, if the business doesn’t step up to the plate?
I usually recommend that Master Data Management (MDM) and data governance programs be driven by the business, and in a perfect world, that probably is the best route.
But even if the business is driving, they usually need a lot of IT support. And if the business doesn’t want to take on the issue at all, perhaps it’s better to have IT doing it than have no one doing it.
Please share your thoughts via a quick comment here.
More Info. on Microsoft’s External MDM Strategy
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In November ’07, Microsoft released a “technology preview” of its Master Data Management (MDM) solution (codenamed “Bulldog”) to selected customers and partners for testing and evaluation.
Microsoft’s public MDM road map is available, as is their overview of MDM. There’s also an MDM forum on the Microsoft Developer Network.
A couple of Microsoft people (Kirk Haselden, Group Program Manager for MDM and Roger Wolter, now with Microsoft’s internal MDM project) are blogging at http://blogs.msdn.com/knight_reign/ and http://blogs.msdn.com/rogerwolterblog/.
My opinion is that Microsoft’s entering the market is a validation of MDM and probably does signal the transition from “early adopters” to “mainstream”. I continue to be interested in learning more about the Microsoft solution, and how it will impact small & medium-sized businesses, as well as larger enterprises.
Microsoft’s Internal MDM Project (MIO)
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I came across this blog posting from 08/18/08 by Nick MacKechnie at Microsoft.
It briefly discusses Master Data Management at Microsoft – the “Microsoft Individual and Organization” (MIO) project.
This is a massive MDM project that Microsoft is doing for its own internal use. I’m familiar with it from my time at D&B.
There’s a Microsoft TechNet webcast (by Matt Stitz, with whom I worked closely prior to his move from Oracle to Microsoft), and an 8-page technical case study. There’s a corresponding PowerPoint, which I wasn’t able to download for some reason.
In addition to the Microsoft technology used on the project, MIO is based, in part, on Initiate Systems’ Identity Hub.
Microsoft estimates it will help it realize over $200 million in increased revenue and cost savings. Interesting reading!
Lessons on MDM from My Summer Vacation
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Hub Solution Designs Blog - Summer Vacation Route
Since I returned from my annual two-week sailing vacation, I’ve been thinking about how to tie some lessons learned on the trip to managing successful MDM initiatives.
Don’t Be Too Ambitious
Last year, we tried to cover too much ground.
This year, we deliberately sailed less and stayed in port longer. We covered about 200 nautical miles (instead of 250), but we were more rested and relaxed when we got back, and we enjoyed the trip more.
The lesson for your MDM initiatives: don’t start off with a pan-galactic, enterprise-wide vision. Start with a small but significant win that will give you a good master data foundation that you can build on, so that later, you can go after more domains of data and parts of the enterprise.
Stay On Course but Be Flexible
The weather was a bit challenging on this trip – just about every day had afternoon showers and thunderstorms. But we figured out that when an entire day of rain was forecast, that was a good day to stay in port and postpone leaving for the next harbor. It required a little flexibility in our itinerary, but it was much safer and more comfortable.
So make sure your MDM initiative can roll with the punches. You’re going to run into political battles, funding issues, delays, technical problems, you name it. But it’s “all in the attitude”. If you, as project leader or key team member, can stay positive and flexible, while remaining focused on the destination, your project is more likely to stay on track and you’ll enjoy it more.
Sail When You Can, Power When You Must
This year, I was more accepting than usual of using the engine when the wind wasn’t cooperating. There were several days when the wind was too light, or from the wrong direction. Normally, that would really bug me, but this year, I found it was no big deal.
In an MDM initiative, like most things in life, there are going to be parts you really enjoy, and parts you endure so you can get to the parts you enjoy. But try to learn from everything, and don’t begrudge the hard parts too much.
Building an MDM hub, integrating it with major source systems in your company, improving data quality, incorporating third party information, and creating a data governance function – these are all significant achievements, and you’ll look back later on the total journey (not just the fun parts) with pride.
August Column in DM Review
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Here’s a quick excerpt from my latest “MDM Insights” column in DM Review.
I recently attended a three-day training class on one of the leading data quality products. It got me thinking about the symbiotic relationship between master data management (MDM) and data quality.
MDM without a robust approach to data quality can be dangerous. We’ve all heard the IT cliché “garbage in, garbage out.” But that is very true of building an MDM hub solution. You’re literally at the mercy of the worst data entry person in the company as you gather information from any number of source systems to feed into your new hub. If you don’t have a strong filter for what goes into the hub, both during the initial load and during day-to-day operation, you’ll quickly be fielding complaints from businesspeople around the company on the quality of the information coming out of your hub.
Click on “The Relationship Between Master Data Management and Data Quality” to continue reading.
And please let us know your thoughts by commenting here …
Governing Unstructured Data
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I had a very interesting briefing the other day by Johnnie Konstantas, the VP of Marketing at Varonis.
Varonis is a software company that focuses on governing unstructured data. Johnnie’s perspective was pretty illuminating:
- A 2007 IDC study found unstructured data accounts for over 80% of all business data
- In 2008, a study by the Ponemon Institute found that 84% of organizations believe their unstructured data is accessible by people with no clear business need and 32% have experienced an unstructured data breach
- The IDC study also found that data grows at a rate of 57% per year
There have been high profile stories lately about unauthorized people snooping in presidential candidates’ passport files, the theft of 94 million credit cards from TJX, and the exposure by an investment firm of data on 2,000 clients, including Supreme Court Justice Stephen Breyer.
And in June, The Identity Theft Resource Center reported that nearly 16 percent of breaches this year came from insiders, up from 6 percent in 2007.
Given that many of the people I talk to or work with are building Master Data Management solutions for their companies, or putting together a Data Governance program, I had to stop and ask myself “maybe we’re all missing the forest for the trees here”.
Granted, the picture on the structured data side of things needs improvement too. Companies still struggle to pull together the “Single View of the Customer”. Islands of data still exist, and artificial silos still cost companies money and hurt productivity.
But I think we ignore the unstructured data problem at our peril. I believe savvy business owners will eventually expect an integrated approach to governing both structured and unstructured data. Even though the technology tools might be quite different, a common organization and policies addressing both types of data will be necessary.
It’s not enough to lock up the structured data, when over 80% of the information in the company is unstructured and is not adequately protected or managed.
I haven’t had a chance to thoroughly research Varonis and its products yet, but it looks like a unique way to govern the unstructured data on file systems, and I’m impressed by the company’s approach.
One Year Anniversary of This Blog
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We’ve been writing this blog for a year now, with a total of 83 posts so far.
It’s been a very positive experience. We’ve had clients tell us “the reason we hired your firm was because of your blog”. And we’ve gotten lots of great feedback from our partners (Oracle, IBM, SAP, Initiate Systems and Siperian).
What we’ve tried to do is to write for people who are new to Master Data Management (MDM) and looking for basic information (like “Useful Definitions for MDM”,“Five Essential Elements of MDM” and “Ten Best Practices for Master Data Management”).
But we’ve also tried to cover more advanced topics too (such as “Master Data Management and the Art of Politics”, “The Key Requirement in Choosing a Product MDM Hub”, and “Data Governance Critical to MDM Success”).
We thought that by presenting a mix of basic and advanced topics, and highlighting key milestones in the development of the firm, we could keep your interest, and hopefully keep you coming back.
The numbers tell a good story. We’ve had a total of 8,100 hits in the past year, with an average of 32 hits per day (over the last 30 days), 200 hits per week and 835 per month (over the last 6 months).
Our “Top 10″ posts have been:
- Ten Best Practices for Master Data Management
- Our MDM Partnership Strategy
- How Master Data Management is Similar to ERP
- Different Styles of MDM Hub
- Metadata and Master Data Management
- Five Essential Elements of MDM
- Critical Data Quality Questions
- The Key Requirement in Choosing a Product MDM Hub
- Master Data Management and the Art of Politics
- MDM Business Case Creation & ROI Analysis
We get most of our traffic from our web site at www.hubdesigns.com (there’s a prominent “Blog” link there), and from the “Master Data Management” and “Customer Data Integration” tags at WordPress.com. We also get a fair amount from Google Reader, My Yahoo, and my LinkedIn profile.
Our Top 10 search terms that people are using to get to the blog are: “Hub Solution Designs”, “Dan Power”, “Gaurav Arora”, “data quality questions”, “MDM vendors”, “Master Data Management best practices”, “critical to quality”, “Oracle MDM”, “ERP and MDM” and “Master Data best practices”.
We’ve tried to keep the blog vendor-neutral, and have resisted the temptation (so far at least) to accept any form of advertising.
In the coming year, we’re looking forward to more in-depth coverage of the leading MDM and data quality platforms, more insights gleaned from working with our clients, more pointers to other places where our writing appears (like my monthly column in the online edition of DM Review), and continuing to try to break new ground and be thought leaders on MDM.
If there’s anything in particular you’d like to see us cover here, please let us know via a comment. It’s been an honor to write for you over the past year, and we’ll work hard to make this a useful resource for you in the coming year.
Building Integration using SOA
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Many companies are still deploying Enterprise Application Integration (EAI), with proprietary adapters and integration servers. However, for a Master Data Management (MDM) solution, we recommend a Service-Oriented Architecture (SOA) approach for integration between the hub and source systems using web services.
A typical web server provides Hypertext Transfer Protocol (HTTP), so Web browsers can receive pages from a web site.
Application servers provide the Simple Object Access Protocol (SOAP) interface and host the web services. The web services also provide object components, which provide the business service layer above the applications.
The development time for SOA-based MDM integration will depend on the number of business entities to be exchanged, the availability of a vendor-supplied Software Development Kit for the Web Services Definition Language (WSDL), the complexity of the applications to be integrated and the number of Web services to ultimately be deployed.
Some guidelines for developing an SOA integration for an MDM hub are:
- Use XML (eXtensible Markup Language) for all data exchange (XML is a language that provides a standard way of representing data and information).
- Use UDDI (Universal Description, Discovery, and Integration) for listing and locating applications. UDDI is a directory standard that is provided by some application tools as a built-in service to use during integration.
- The WSDL (Web Services Description Language) file should be obtained from the source system to which data needs to be sent or retrieved. WSDL is a “descriptor standard” that an application uses to describe its interface and interaction rules to other applications. WSDL is a document written in XML which describes a Web service. It specifies the location of the service and the operations (or methods) the service provides.
- WSDL should be leveraged with the help of proprietary tools provided for each application to generate the XML message required to meet that data structure.
Currently, some of the Master Data Management platforms (such as Siperian, Initiate Systems, Oracle and IBM) provide excellent SOA libraries of web services.
With some work by the end customer, these products can provide a standard set of data services at the application level. We believe this approach ultimately will give you more flexibility and adaptability than EAI-based integration.
Building a Data Governance Organization
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I’m often asked how many data stewards a company needs.
A rule of thumb I’ve used for quite a while is “one data steward per $1 billion in annual revenue”, but of course that can’t be a hard and fast rule.
Depending on the company, the degree of automation, what data quality tools are available, and the major processes around the enterprise, that number is going to vary.
Here are some thoughts to keep in mind as you build your data governance organization:
- Build the business case and secure your funding. Don’t forget this is a multi-year effort. Several times, I’ve seen data governance teams and MDM initiatives that never thought beyond their first year’s funding, and who were surprised when funding for Year 2 and beyond wasn’t forthcoming.
- You’ll probably need a multi-layer, cross-functional approach. Start with a high level group that sets data policy, usually called a Data Governance Steering Committee or Data Governance Council (DGC). Your executive sponsor(s) should be involved with the DGC. Then you’ll probably have a small group of data stewards which handle day-to-day data management, which reports to the Data Governance Council.
- Focus on your data governance processes, including relevant metrics that show the impact to the business, and on communicating those metrics and their impact to the rest of the enterprise. Create a communications and education strategy to get the word out.
- Look for IT people who “speak business” and business people who “speak IT”. These liaison-type people are going to be crucial to your data governance organization. Although I believe that data governance should be driven by the business, there’s no question that you’re going to need a lot of support from IT. So look for the “bi-lingual” folks in your company – they’re out there and they can be incredibly valuable in understanding the business impact of data issues, and in providing the technology support that the data stewards will need.
- Don’t forget about metadata. In your travels as a data governance organization, you’re going to run into a lot of metadata (information about information). Develop a disciplined approach to cataloging and maintaining the metadata you come across. In many ways, that will probably be one of the most useful outputs of your data governance initiative.
We’ll have more to say on data governance in this blog in the future, but let me leave you with one idea. Instead of describing your MDM initiative as (hopefully) including data governance, think of it as a data governance initiative that has an MDM component.
You’ll be doing data governance in your enterprise long after your current MDM hub implementation is over.
If you don’t agree, or you have a perspective on data governance you’d like to share, please comment here on this blog.
Consolidation of Data Quality and Data Integration
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In a recent article, we covered the importance of data integration to Master Data Management (MDM).
This article elaborates on that in the context of today’s software market, and talks about how the visionary data integration vendors are scrambling to acquire and offer data quality as part of their integration suites.
Historically, data quality initiatives have been rolled out only on a project-by-project basis, while integration initiatives have been point-to-point application integration projects.
But more recently, as MDM programs have started gaining momentum, there is a need being felt in the marketplace for a single platform that can integrate data from multiple sources across the enterprise (web, data warehouse, ERP, CRM, legacy systems and systems from acquired companies) as well as run sophisticated data quality processes on these sources.
This requirement allows for a single administration console and metadata repository, as well as common transformations, user interface and a unified developer workbench, all on a single, combined integration and data quality platform.
This vision is consistent with moving towards a Service-Oriented Architecture as well, and is very conducive to providing a single environment for “data as a service” that is trusted and consistent across sources.
The customer tends to love it, since an integrated platform like this generally implies lower Total Cost of Ownership and smaller IT costs than standalone integration and data quality investments, and more rapid software development cycles.
The MDM vendor, if not providing such a platform itself, loves it since it can focus on what it does best, i.e. matching, merging and building data hierarchy.
Recognizing the above need, California-based Informatica Corporation acquired identity resolution vendor Identity Systems, while Massachusetts-based Trillium Software acquired address cleansing vendor Global Address. These are just two examples of recent data integration and data quality market convergence.
And the acquisition of Group 1 Software by Pitney Bowes provides more evidence of this shift. In the process, niche data quality players are finding it more difficult to compete in such a dynamic marketplace.
If you’re considering acquiring a data quality tool for a corporate initiative, consider the above dynamics. And we’d love to hear your thoughts via comments on this article.
Importance of Integration to MDM
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We’ve discussed many other topics on this blog, such as data quality, best practices for Master Data Management, the five essential elements of MDM, and Master Data Management and the art of politics.
But one topic I don’t think we’ve given enough “airtime” to is integration. There are many different types of integration technology available today, and a veritable alphabet soup of acronyms to go with them.
There’s Extract-Transform-Load (ETL), Enterprise Application Integration (EAI), Enteprise Information Integration (EII) and Business Process Management (BPM).
In an upcoming piece in the online edition of DM Review magazine which I wrote last week, I go into more detail on the different types of integration and why I think Business Process Management offers some real advantages, due to the close fit with Service Oriented Architecture (SOA) and its flexibility and ability to model complex business processes that span multiple application silos.
But as I said, that’s a topic for another piece, and we’ll post a link to that here when it becomes available later this month.
In today’s piece, I want to urge MDM project team leaders, program managers, and “data champions” to think about the importance of integration itself, and the existence of certain typical requirements.
While integration doesn’t always have to be real-time, if you find yourself thinking solely in a batch-oriented mode, take a step back and ask yourself, “what will we be giving up by not providing for any real-time capabilities?”
And while straightforward, point-to-point XML data exchange may be all you need, ask yourself if you’ll be giving up anything important by not being able to model, deploy and manage business processes.
And try not to limit yourself by planning only for one-way integration into the hub. As hard as it is to convince the business owners to subscribe to the data quality improvements and external content that you typically do in an MDM hub project, you’ll make it much harder to achieve your expected ROI for the MDM initiative if the source system business owners don’t receive any of those improvements.
What are some of the integration “sticking points” you’ve run into on your MDM projects?
OAUG Collaborate 08 Presentation
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TechTarget recently had an article that quoted heavily from my presentation at the recent Oracle Applications Users Group (OAUG) conference, COLLABORATE 08.
The article discusses the Master Data Management program at Tektronix, Inc. and segues into an overview of MDM based on my presentation at the conference.
Here’s the full link:
http://searchoracle.techtarget.com/news/article/0,289142,sid41_gci1312492,00.html
Please let us know what you think of the article by commenting.
Favorite MDM-Related Web Sites (Part 1)
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I’ve been building up a Favorites folder of web sites relating to Master Data Management for several years now, so I thought I’d share some of them with you today.
First, I should mention our own site, www.hubdesigns.com. It has some great MDM resources, and we’re updating the Publications page to include our MDM Summit, OAUG Collaborate 08 and DIG 2008 conference presentations.
Another site I find very helpful is www.dmreview.com. And my monthly column, “MDM Insights”, started in their Online Edition last month, discussing Master Data Management and Service-Oriented Architecture.
I’ve always found Aaron Zornes’ analysis of the MDM market and its players very insightful, and I still visit The MDM Institute and the MDM Summit sites pretty often, particularly their MDM product reviews.
On the topic of Data Governance, an area close to my heart, there’s a good blog called the Data Governance Blog, which includes a couple of useful definitions of Data Governance.
A blog I read regularly is Jill Dyché’s Blog. It’s written in a very engaging first person style, but still contains some great nuggets of wisdom about Customer Data Integration, Business Intelligence and Master Data Management.
Another blog that I like is by Steve Sarsfield at Trillium. It has some good content on Data Governance and Data Quality. You can find it at Data Quality Insider.
One of my favorite blog’s is written by Andy Hayler, an industry expert and the founder of Kalido, who has written quite a few good pieces on MDM at Andy on Enterprise Software.
I’ll continue this in “My Favorite MDM-Related Web Sites (Part 2)”.
Tracking and Managing Corporate Hierarchies
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Here’s a great video that illustrates the difficulties in tracking and managing corporate hierarchies:
As the video shows, in today’s acquisition-heavy environment, it’s pretty tough to keep track of all the M&A activity in your customer base. As they say at the ballpark, “you can’t tell the players without a scorecard”.
Having worked for D&B in my previous life, I know they do a good job in maintaining the most important corporate hierarchies, with over 8.7 million company records linked to the appropriate family tree. D&B’s not perfect, but they do try pretty hard. If corporate hierarchies are important to your MDM initiative, think about including D&B early in your planning process.
And thanks to my friends Jack Dally from Transitions [2], and Mani Kumar Manda from Rhapsody Technologies for pointing me to this video.
Next Week’s DIG Conference
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I’m really looking forward to speaking at next week’s Decisions, Information and Governance conference in Las Vegas, sponsored by The Palladium Group.
And I spoke earlier this week at the New England Oracle SOA Users Group, talking about Master Data Management as a foundation for Service-Oriented Architecture.
MDM initiatives seem to be getting linked to Service-Oriented Architecture or to advanced analytics and business intelligence programs.
I think there can be a problem (but also an opportunity) for MDM in inserting itself between two things that used to talk directly from one to the other (an ERP system to a data warehouse) or (b) asserting itself as a predecessor task to ensure a better outcome (for example, when MDM is used to consolidate and improve the quality of enterprise data before people try to use it in analytics or business intelligence).
While I think it’s true that MDM is in fact needed at most large organizations, having to coordinate with an already-underway SOA initiative, or step back from a planned BI initiative and first tackle MDM, does complicate things a bit. So that’s the “problem” part.
The “opportunity” part is that, for organizations that have the foresight or the luck to tackle MDM first, it makes implementing SOA or achieving business intelligence success that much easier. There’s already a centralized repository of information on customers or products (or whatever domains have been mastered), and that information is proactively managed so that it’s trusted to be accurate, complete, timely and consistent.
Whichever situation your organization is in (tackling MDM first or building it into something else like SOA or advanced analytics), spend the time to develop a workable MDM strategy, using a holistic approach that addresses people, process, technology and information. By all means include an MDM hub in your planning, but make sure you also plan for business process management or sophisticated integration, as well as built-in or bolted-on data quality and enrichment capabilities. And be sure to build a data governance framework around your MDM initiative.
I’ll write a trip report after next week’s DIG conference, to let you know what I thought of the conference itself and whether I got lucky at the tables!
