by Julie Hunt

It’s always great to get a briefing from a very knowledgeable and flexible founder of a young company: tapping into original vision that has been tempered by the experience of customer implementations can be a rich experience. Recently the MDM Think Tank chatted with Martin Turvey, CEO of Loqate, about location intelligence and data quality. Loqate may be a young company, but in many ways, it is not a “start-up” due to the extensive expertise of founders Turvey and Paul Flew, in the areas of address quality practices and location intelligence — and the technologies that support them. Flew’s strong NLP (natural language processing) background is also an important asset for Loqate.

For most businesses, accurate address data is essential; poor address quality costs companies tons of money and lost customers. Not only is missing address information a problem, but inconsistent address data across repositories impedes data synchronization and calls into question the accuracy of all of the data. Turvey provided an interesting point: over 80% of data has a location element (source: PBBI). This means that verifying and cleansing address data, and then adding geocoding, can greatly enhance the usability of this data.

Use cases for location intelligence include: fraud detection, insurance risk assessments, improving mailing and shipping operations, real time mapping of web content and news feeds. Loqate maintains a repository of reference data comprised of address, geocodes, languages and other data covering 242 countries and territories.

Loqate is one of the few independent software vendors for address quality / location intelligence services, since most of the other vendors have been acquired by the usual suspects. Traditional data management stacks from the large infrastructure vendors are not an option for many companies, especially in emerging markets and the larger international arenas for address quality needs.

So Loqate is positioning its independence as a competitive differentiator that allows it to target solution niches not usually covered by the big infrastructure vendors.  This positioning is strengthened by Loqate solution innovation and future direction, including an upcoming Cloud / SaaS offering. Turvey commented that most MDM solutions fail at what Loqate does well for address quality and location intelligence. As to sales model, the Loqate solution is only available through Loqate partner companies that OEM or sub-license the technology.

The components of Loqate are broken down into:  Verify, Geocode, Register, and Identify. Additional technology includes the Geo-Data Quality Engine and the Global Knowledge Repository.

In Verify, where validation and clean up are performed, powerful differentiation exists in the parsing methodology. Based on lexicon and context, parsing algorithms understand what the data should be, based on context parameters. Loqate parsing capabilities analyze and remediate data in situ, and do the hard work on single strings without breaking the string into components first. In fact, the string’s structural context provides cues for Loqate’s parsing / validation. Most other data quality tools require users to do quite a bit of hands-on mapping and other tedious work as preparation for remediation. This isn’t the case for Loqate Verify. Parsing is also trans-global for processing records and strings with mixed international character and language sets. Data can also be transliterated from one character set to another character set (e.g. Roman to Katakana in Japan)

Turvey cited a use case for Fraud Detection: cheats will use fake addresses made up of components that are valid on an individual basis (real street address, real city), but in combination the components do not add up to a valid address. Most other address quality and data quality solutions will vet the individual components but not the composite, which means they may validate a fraudulent address.

Loqate provides real value by trapping errors at data entry time when remediation is at the cheapest point. It’s also essential to trap inconsistencies at data entry to prevent fraud and block bad data from infecting processes such as shipping that can greatly impact costs.

Geocoding is available for every address data element “out of the box”. The geocode assignment results from high granularity generation of a latitude-longitude coordinate for any address worldwide. From the geocode a map visualization can be created, accurate to delivery point / rooftop levels.

Register provides smart data entry to reduce errors and speed up operational processes. This is particularly useful when working with customers, whether it’s a call center employee talking to a customer or a self-service interface for eCommerce.

Identify:  The Loqate Entity Extraction module enables location, additional geographic and contact information to be identEified and extracted from web content and other unstructured information sources. LocationV extractions enable content to be localized, driving location-based services and geographically targeted advertising.

Loqate has included the ability to quantify address data quality through its Accuracy Code analysis. A verification accuracy match score portrays the similarity between input data and the closest reference data match as a percentage between 0 and 100, with 100 as best match, as well as detailing what changes have been made to each key component during processing and determining validity of those components.

Right now, user tweaking is limited and is mainly accomplished through processing rules. There is no means as yet to tweak algorithms. Loqate is taking a slow approach here, being careful not to lead users astray, since algorithm changes can end in unexpected and harmful consequences.

Next up for Loqate is an impending Cloud / SaaS offering that should be available Spring 2012. Loqate is touting their Cloud services as “developer source for anything location”. It is also a great opportunity for further innovation since the Cloud can take software vendors in some very interesting directions.

About the author: Julie Hunt is a software industry strategist and analyst, providing market and competitive insights. Her 25+ years as a software professional range from the very technical side to customer-centric work in solutions consulting, sales and marketing.  Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter at @juliebhunt   For more information, please visit Julie Hunt Consulting – Strategic Product & Market Intelligence Services. 

Not because we need to jump on the social networking bandwagon to keep MDM interesting and relevant. But because companies like Google (with Google+) and data.com (formerly Jigsaw and now SalesForce.com) have already cemented the relationship between the two.

The evolving conversation regarding MDM and social networking has two perspectives. One angle considers how to use members of a social network in the management of master data. The other addresses how to use MDM for managing data about members of a social network.

The first context for discussing MDM and social networking has been a subject of interest for some time. Crowd-sourcing is the basic social networking mechanism used to accomplish this goal. The “crowd” can be a well-defined group of employees or a coalition of like-minded members of an online service.

The second recently came to the forefront when Google chairman Eric Schmidt proclaimed that the company will only accept “real names” in Google+. According to GigaOM, Schmidt admitted in an interview “Google is taking a hard line on the real-name issue because it sees Google+ as an ‘identity service’.”

That sounds a lot like an MDM policy in the making.

Marrying MDM and Social Networking

The idea of bringing social networking and MDM together has its roots in “community data stewarding,” which some in the MDM space started touting a few years back. The idea is to leverage the collective efforts of individuals within an organization to help manage master data. More recently the notion of community data stewarding expanded to include using “the masses” for MDM.

Online data services like data.com, which is the reincarnation of Jigsaw after it was acquired by SalesForce.com in 2010, is a good example of mass data stewardship.  Jigsaw is probably the first real adaptation of social networking, specifically crowdsourcing, to managing data about people and organizations.

Even though the stated intent of Jigsaw was to share contact names, I can easily argue that Jigsaw is a social MDM application. By tapping the universe of salespeople for information about people and organizations, Jigsaw, now data.com is, in effect, the first commercially successful crowdsourced Master Data as a Service (DaaS).

Master DaaS is different than MDM SaaS, which is the delivery of MDM software capabilities in the cloud. Personally, I believe all the action is (or will be) at the intersection of Master DaaS and MDM SaaS, which is where data.com is likely heading. But that’s a conversation for another time.

One can also show that even LinkedIn is readily re-purposed as a Master DaaS, where individuals manage their own identity. Consider offerings such as “LinkedIn for Salesforce.com.” It’s not much of a leap to see how contact names in SalesForce.com are indirectly managed by the contacts themselves through their LinkedIn profiles.

While understanding how to adapt crowdsourcing dynamics to data stewardship is worthy of further consideration, this article focuses on the second context: how to use MDM to manage data about members of the crowd, i.e. a social network. This is where the conversation gets contentious, as Schmidt unwittingly demonstrates.

At first blush, all the fuss about banning pseudonyms on Google+ seemingly has nothing to do with MDM. But it does. Very much so.

Master Identity Keeper

According to GigaOM, during an interview with Andy Carven, National Public Radio’s digital editor, Google’s Schmidt stated:

“G+ was build (sic) primarily as an identity service, so fundamentally, it depends on people using their real names if they’re going to build future products that leverage that information. If you think about it, the Internet would be better if we had an accurate notion that you were a real person as opposed to a dog, or a fake person, or a spammer or what have you… So if we knew that it was a real person, then we could sort of hold them accountable, we could check them, we could give them things, we could you know bill them, you know we could have credit cards and so forth.”

Fred Wilson at Union Square Ventures further notes, Google “wants to be an identity gatekeeper,” where individual crowd members basically manage their own identities.

Schmidt and Wilson suggest what sounds like the ultimate Master DaaS for person-type parties. But it raises some interesting questions. Does a business need to definitively know the individuals that they interact and transact business with? While this may seem absurd to even ask, apparently we are at that crossroad. And from the dialogue it seems not everyone agrees on the answer.

Is MDM Evil?

To date, a business naturally assumes that a customer cooperates by exposing their identity. After all, how else can you conduct business?

That said, there are many instances of businesses that don’t know the identity of their customer. P&G, for example, cannot readily identify the consumers who purchase, say, Tide®. The “customer” represented in P&G’s business systems are retailers and wholesalers and some of their employees, but not likely the person pouring Tide® into their washing machines.

On the other hand, take a retailer like Target. Recently, they had some challenges with handling online purchases as described in this story on CNN.

“…shoppers who bought the Missoni Target line are posting on social media websites Facebook and Twitter that they won’t shop at Target again because their online orders are being delayed — or worse, canceled — by the retailer.”

Before the internet, Target did not likely know the identity of many “shoppers,” i.e. customers who made their purchases at a store, unless they had a Target credit card or exposed their identities at the cash register. And even if they did have shoppers’ identities, they would not likely have the capability to resolve the relationships among them, which is a major goal for social media sites.

In the past Target’s customers for MDM purposes were suppliers and wholesalers and not “shoppers.” Just like P&G. With online purchases, however, this is no longer the case.

Of course, Target needs to know the identity of the suppliers and wholesalers and those related contact names. The question is this. Will they ever know the identity of the supplier or wholesaler contact, who, when behaving also as a shopper, is bad mouthing Target on some social media site under a pseudonym…or is part of some anti-Target group? Meanwhile, a Target representative may just have had a seemingly pleasant lunch with the person. They’re being blindsided.

Now consider this. The blog GIZMODO states “Google’s horrible new policy on using real names in Google+ effectively means that the service is now a danger to real people.” (As opposed to fake people?) And “…the policy is evil.”

GIZMODO adds:

“You can’t use initials (even if that’s what you go by). You can’t use a pseudonym (even if that’s what you go by). And you can’t use numbers or symbols (even if they are part of your name).

Æ, e.e. cummings, Malcolm X, and T.S. Eliot would all be in violation of Google’s policy. So, too (by my reading) would be Mark Twain, George Eliot and doubly so, R.U. Sirius. I’m pretty sure nobody whose name you actually know in the band U2 can use Google+ or, by extension, Gmail.”

Play Nice

Apparently Google seeks birth certificate-quality names. Is this the same strength of policy making that MDM needs to succeed?

Traditionally, the answer is not necessarily, because any decent MDM technology will have the ability to relate multiple aliases to a person party. But as MDM moves to manage master data about your customers who are also members of business and social networks, not all aliases are willingly shared.

Everyone knows Mark Twain and Samuel Clements is the same person. And even if we did not, someone besides Twain himself would ultimately have to know his real identity. Otherwise how would he collect his royalties?

And here is the blind spot for MDM moving into the social realm. A 360-degree view will be without those structured or unstructured data relationships of a party that may only be revealed under a fantasy name…and not disclosed to you or anyone else.

Selling and marketing may get a whole lot harder as individuals increasingly armor themselves with pseudonyms and fantasy names (or personas). In response, we see the rise of strict policies enforcing identification…or don’t play on my social media site.

Unfortunately, that’s a double edged-sword, and the physics of it all has yet to get worked out. On the one hand, Facebook and Google have a threshold mass where people have to play by the rules or get booted. On the other hand, the resistive power of the masses can influence those policies. Just ask Netflix.

When a Customer Identity Is the Product

Consider Don Norman’s observation about Google+. Normanis the author of The Design of Everyday Things. He says, “Real names, they (Google) say, turn out to be the names on your driver’s license and your passport and your credit cards so that they can track you.”

He goes on to say Google’s “goal is to gather all the knowledge in the world in one place, but really their goal is to gather all of the people in the world and sell them.”

This appears very much like a goal of MDM: to gather all of the people in your business circle in one place so you can ultimately track them. All, of course, with the intent to manage a relationship with them…um sell them something.

I unequivocally say, yes, this is a goal of MDM. But there is a slight twist to the Google+ story.

Norman also submits that “Most people would say (of Google) ‘we’re the users, and the product is advertising. But in fact, the advertisers are the users and you (we) are the product.”

Typically, MDM assumes we are talking about the identities of persons and organizations like customers, suppliers, employees, partners and the like. Norman fundamentally asks, when a person’s identity is a product, do we have a right to enforce them to share that identity as a condition of use…I mean, participation in a service?

Frankly, I am not quite sure what the big deal is. Credit bureaus, like Experian and other companies like Acxiom, have sold our identities as a product for years.

Data Is Not An Asset. A Person’s Identity and Relationships Are.

According to GIZMODO, “Forget social networking, the big goldmine of the future is online identity verification.” Bingo, that’s Master DaaS.

Two questions related to MDM are at play here. (Since we are solely discussing individuals and groups of individuals …and for simplicity, I exclude master data on other entities such as products.)

1. How do you have transactions and interactions and perform analytics without, well, master data? After all, a party’s name is master data. In other words, how do you create an order or an account without header information about the party?

2. Is there an obligation for people who do business with you to correctly identify themselves? I am not sure how else business can occur. Even setting up a Swiss bank account requires identifying the account holder. Although, I cannot say for certain. I’ve never had enough money to hide from anyone!

Speaking of bank accounts, Dave Winer thinks Google “wants to effectively become a bank.” According to Weiner, knowing the relationships among persons is where the value of sites like Facebook and Google+ is. Knowing and managing the relationships among persons happens to be an important function of MDM too. We can think, then, of a MDM hub as a sort of bank of person and organization identities and the relationships among them.

If nothing else, one thing has been settled. Data is not an asset. The true identity…and corresponding relationships of a party are. It’s an asset to a person. It’s an asset to a business. Even if we mean “asset” rhetorically.

In my opinion, Google+ and other social media sites purporting to be identity services should offer an incentive like Jigsaw does. You gain points by sharing the identities of people you know. If anything, Jigsaw is the evil one. It’s a platform for everyone to “rat out” everyone else they know by disclosing their name, employer, work address, phone number and email address.

Identity and Relationship Resolution and Keeping

The concern voiced by Google resonates in MDM because a single representation of customer information and a “single version of truth” are frequently stated desired outcomes. Given the largest percentage of MDM initiatives involves resolving and managing identities and relationships, we need to reconsider what and who is a party to a transaction and interaction.

For starters, we need to rethink the notion of “customer.” It’s becoming an increasingly marginalized, if not obsolete and irrelevant concept. “Customer” seems inadequate for collectively describing the myriad roles played by all the participants in business transactions and interactions.

If abandoning “customer” altogether is too radical, we should limit it to a very narrow meaning. Take a health insurance company for example. They narrowly define a customer as the employer sponsoring a health plan. That’s it.

An employer a.k.a customer is only one of many participants in their business transactions and interactions. Other participants include subscribers, providers, members, administrators and brokers. They collectively refer to these participants as constituents, and any participant may play more than one role. A provider, for example, can also be a subscriber or member, or if the provider is an organization, such as a hospital, the provider is also an employer that sponsors a health plan for its own employees.

Additionally, we need to recognize that the collection of participants forming a crowd, group, organization, circle or whatever we call it is also an entity. Crowds, circles and groups are similar to organizations, except they usually don’t have a legal standing and tend to be virtual. Nevertheless, they are living, breathing entities that matter and require identity and relationship resolution. This is particularly the case if they are participants or potential participants in a transaction, interaction or analysis.

We can no longer easily segregate the persons and organizations we engage in a transaction or interaction into separate entities like customer, supplier, employee, partner, user, shopper, guest, donor or whatnot. It’s time to recognize these concepts and terms for what they are: role designations, not discrete entities.

The entity is the person or group. That’s why some organizations now collectively recognize all of them as a single entity and dub it a “party” or “constituent” or the like. Where the entity can behave in one or more roles as a customer, supplier, employee, partner, shopper or whatever.

Personally, I prefer “participant” to describe the individuals in a group. “Member” or “party” is probably easier on the brain, but “participant” is an action word, even if it doesn’t nicely roll off the tongue. “Constituent” works too, but sounds a little formal.

I also prefer Google+’s “Circles” to simply “group” or to, say, Facebook’s “Smart Lists” when depicting a crowd. After all, people travel in circles, not on lists! A “list” is too linear, even hierarchical sounding. “Circle” is a clean break from the chronic misrepresentation of all relationships as hierarchical. Plus, we can be participants in multiple related or unrelated circles.

“Smart group” might work too, where smart means identifiable. Then, of course, there is always “network.” A network is neither linear nor hierarchical but it’s too clinical sounding. We can always just say persons and organizations. But that’s unimaginative.

Instead of categorizing persons and organizations by their role in transactions and interactions, just designate them as participants in a circle. Some seek to distinguish social networking and business networking, but in the end, we can’t always distinguish interactions as social or business.

The following table depicts the evolving conceptual models for representing participants and circles in a system. While the goal is to move toward a Stage VI model, most organizations will have systems representing participants and circles in transactions and interactions at different stages.

Where Do We Go From Here

Deriving a panoramic view of fragmented customer data for transaction processing, business interactions and analytics involves multiple parties arranged in complex network configurations. But not all these parties traditionally and simply behave as a “customer.”

Business applications must rapidly evolve to a Stage VI model that can support different sets of relationships among persons, organizations and groups and different sets of data relationships for them. A blind spot may still exist where the identity of participants in a combined social and business circle are irreconcilable.

Until business applications can support a Stage VI model, MDM will have an interim function as keeper of participant and circle identities and relationships. However, even with MDM, separate data relationships based on participant role may not be fully supportable until business systems themselves can support complex network configurations.

Once business applications can support a Stage VI model, they still may not be suitable for managing all participant relationships for two reasons. One, if enterprise applications are not optimized for a large, complex arrangement of participant and data relationships, performance could be a significant roadblock. And two, a production transaction system may not be optimal for dedicated data stewards and curators to maintain participant identities and relationships.

For these reasons, the importance of MDM will increase as it becomes the main mechanism for managing current and historical participant and circle identities and relationships with pointers to corresponding data relationships. As cloud computing penetrates enterprises, resolving and keeping participant identities and relationships will increasingly occur as a combination of MDM SaaS and Master DaaS.

“MDM should be a business driven program” is the mantra we hear time and time again. And while that is the right prevailing wisdom, doesn’t it seem that there is far more articulation about the technical elements of MDM than about the business elements?

So often I have seen MDM publications and presentations start with the “should be business driven” perspective but then quickly shift to covering the technical elements of MDM, topics related to architecture, data models, data integration, metadata management, match logic, consolidation, synchronization, application services, and so on.

Yes, those all are important elements in the MDM equation, but this over-abundance of technical insight can be frustrating for those seeking practical knowledge and guidance for the business planning of an MDM program. After all, without a strong business presence, MDM can’t develop into a core competency throughout the company. So why, in comparison, is so little insight provided about the business side of the equation?

Actually, it’s easy to understand this situation. The plethora of technical insight is a byproduct of the influence that IT and vendors have on the MDM market. And that’s not suggesting that business organizations don’t care to promote their MDM practices, it’s just that there is much more uniqueness and latency involved with getting these business components established, and these dynamics are harder to articulate.

Let’s take a closer look at these influences and dynamics.

The call for MDM

The initial need and sponsorship for an MDM initiative often emerges from the IT and/or analytical groups in a company. These groups usually exist separately or on the periphery of the business. The IT and analytical areas responsible for activities such as system integration, data migration, information management, data warehousing, business intelligence and reporting will typically be the first to expose where poor data quality and lack of data governance is creating project delivery delays, data management problems, integration issues, distrust of the data, and reporting problems.

Therefore, it’s understandable that these groups become initial proponents of MDM solutions. And while the root cause for many of these data problems lies in front-end business practices and data entry points, the IT and analytical groups are most directly impacted and naturally tend to implement their own back-end corrective actions.

At some point these ongoing problems and workarounds become a tangled mess, and that situation becomes a catalyst for seeking an MDM solution. Current state issues, improvement opportunities, and cost/benefit projections cited in MDM proposals are usually centered on correcting these legacy issues, improving data governance and information management practices, and eliminating the workaround overhead. In other cases, MDM programs often emerge when legacy applications are being replaced with more integrated platforms such as business application suites, data hubs, and enterprise warehouses where IT planning and activity is already underway.

Product vendor and consulting influence

Because of the large market opportunity and competition among MDM product vendors and consulting firms, it is expected that they will have a significant influence on the MDM information being presented. Technology and consulting help should always be factored into an MDM assessment and implementation plan. Although the overall impact and practical use of both can often be overstated, good technology and consulting help applied in the right places can definitely advance MDM capability and reach.

But many other aspects of implementing MDM involve new and unique business practices, business context, and process management where technology and consulting help will only have limited application, if any.

MDM is as much about people and process as it is about technology, which is why product vendors are increasingly looking at improving their business consulting practices or consulting partnerships as a competitive advantage. Over time this trend should help bring a better balance of information and practical insight for the planning and implementation of MDM.

Discovery and Analysis

At the onset of an MDM initiative, a “Discovery and Analysis” phase is conducted to fully detail the issues, root causes, business and system impacts, and opportunities for improvement. This discovery and analytical phase is often led by IT or an analytical team, if not a consulting group. Business leads should be actively involved in this phase, but specifically how and where business groups will be needed to drive and support MDM plans will largely depend on what priorities and direction come out of this discovery and analysis work. And where the business engagement needs are identified, the business groups will often need time to plan, budget, and prepare for these activities.

Implementing process improvements and driving data governance activity can be new or disruptive territory for business organizations. Many MDM programs do not have sufficient budgets to cover these business area needs, therefore the implementation of these business elements can take some time.

MDM job roles

IT groups already have most of the necessary job roles and skill sets needed (e.g. analysts, architects, project managers, programmers, data miners, database administrators) to initiate and support the technical aspects of MDM. The business roles needed within a MDM program (e.g. data governance leads, data stewards, process analysts, quality managers, data access gatekeepers) often do not already exist as formal job roles. Consequently these roles either have to be assigned to existing resources that have other job responsibilities and/or created through new hires, job transfers, or contracted positions which can require budget allocation and also take time to fulfill. Therefore it’s common to see IT and analytical related activity initiated early on while the business roles and needs are being addressed.

Maturity models

In MDM and data governance maturity models, we typically see the advanced levels of maturity defined using terms such as Managed, Optimized, Proactive, Advanced, or Transformational. But in many of these models, those levels are characterized by more system and analytical orientated achievements, related to systems integration, establishing a system of record, business process automation, using SOA/SaaS, quality monitoring, delivering trusted analytics and KPIs, and so on.

The business area maturity needs and milestones — associated with data governance, data life cycle management, and quality control — are much less apparent in these maturity models.

Granted, much of the program development and maturity on the business side of a MDM program is going to be tied to unique business practices that are harder to generalize in a high-level maturity model. Therefore it often takes some digging in MDM and data governance forums or finding business case studies to gain good insight on how and where the business events and the maturity of business practices have occurred in a MDM implementation.

A developing dynamic

So even though it is critical for business to be involved and provide leadership in an MDM program, defining, articulating, and achieving that is likely to be a developing dynamic that spawns from IT and analytical underpinnings where product vendors and consulting firms are also well entrenched. As more companies launch MDM initiatives and develop their MDM core competencies across their business model, we can expect to see increasing amounts of business insight and best practice information made available that will express how and where business roles and business practices evolved in MDM programs. I look forward to that.

Mark Allen is co-author of the book “Master Data Management in Practice: Achieving True Customer MDM”. Mark has over 20 years of data management and project management experience including extensive planning and deployment experience with customer master initiatives, data governance programs, and with leading data quality management practices. Mark is a senior consultant and enterprise data governance lead at WellPoint, Inc. Prior to WellPoint, Mark was a senior program manager in customer operations groups at both Sun Microsystems and Oracle Corporation. At Sun Microsystems, Mark served as the lead data steward for the customer data domain throughout the planning and implementation of Sun’s enterprise customer data hub.

We’ve served almost 30 clients on three continents (North America, Europe and Africa), in industries such as financial services, insurance, telecommunications, software, high tech, information services, payroll, life sciences, health insurance, and medical devices.

Although we’ve had our ups and downs, we’ve managed to grow even during the toughest economic times of the past eighty years. Over the last four quarters, revenue has grown an average of 100% per quarter. It hasn’t hurt that the master data management (MDM) space has been doing well even in the teeth of the turbulent economy.

We currently have two distinct practices:

Our Consulting & Systems Integration practice focuses on developing and delivering high value MDM and data governance strategies. We focus on:

• Education
• Readiness Assessment
• Strategic Roadmap Development
• Preliminary Software Selection
• Business Case Creation
• Data Governance Formation

Our unique approach allows clients to develop their MDM strategy and create their data governance organization in parallel.

Our Thought Leadership practice develops high quality content to help MDM software vendors reach their target audiences:

• Objective, well researched white papers
• Thought provoking, high attendance webinars
• Guest articles on other organizations’ blogs
• Keynotes at conferences and dinners
• Engagement through social media
• Distributing content through our specialized network

The golden records in the hub are formed from the master data records typically describing the customers, suppliers, products and locations in the transactions made in the enterprise application stack. In the master data hub, we emphasize consolidating, and eventually also splitting, the master data (to be) from different contexts into golden records being as close to the real world as needed in the enterprise as a whole.

As in common database theory, we also need relations between the golden records and we may, staying in the metallic tune, call them golden relations.

Golden Relations in the Party Domain

In understanding our customers, suppliers and other party roles, we build hierarchies of the golden records in the golden copy. Typical hierarchies include:

• Consumers belonging to a household
• Company family trees, often derived from external reference data
• Contacts within the companies which are our customers and suppliers

My guess is that we’ll start seeing more advanced relationship tracking in this domain in the near future. An example would be social network-based tracking of contacts changing jobs between parties who are our customers, prospects and suppliers.

Golden Relations in the Product Domain

Hierarchy building in the product domain is much more diverse between industries and in a single organization than hierarchy building is in the party domain.

Therefore, flexible structures are needed within a golden copy or master data hub used for Product Information Management (PIM).

Our ability to handle more products in our databases and the trend towards globalization making more products available will only increase the demand for handling the golden relations between the golden product master records.

Golden Relations in the Place Domain

I like to name the domain of locations as the “place” domain, because then we have a “P” trinity of Parties, Products and Places.

Hierarchies come naturally with places, as they form a geographical hierarchy of the type we like to use, typically being country, state, postal code / city, street name / block, building number and unit depending on where on the earth our place is situated.

The trend of governments around the world making public sector data more open helps a lot in getting the structures of the place master data aligned with the real world.

Golden Relations in Multi-Domain MDM

A multidomain master data hub embracing the “P” trinity of parties, products and places will have some important golden relations between the golden records within each domain like:

• The exact place where a unique party such as a consumer lives. This also helps with forming the right households.
• The exact place of a certain part of a product, being a locality for example in hospitality and travel – and the exact places of the nearby attractions.
• The sales figure in a defined period for products belonging to a given category sold to parties being companies in a given line-of-business.

Most interesting business problems require more than one domain of data for their solution.

Platinum Relations

Master data may be born in the hub or may be born outside the hub and then transformed into the hub, thus becoming the golden copy.

Transforming already existing records representing parties in the prospect and customer role into the hub is still the most common direction today. Therefore that discipline is still often called Customer Data Integration (CDI).

In this process, it is highly recommended not to purge the records and relations that already exist when we merge data into golden records. You should keep the incoming records with a platinum relation to the new golden record as it sometimes happens that you have to rollback.

Mass import and transformation of data also happens in the product domain, for example at retailers. Also here it’s recommended to keep the original data and make platinum relations.

In some places, I’ve come across a case of “keeping up appearances”, called vanity addressing. Here your customer insists on using a somewhat incorrect address that “sounds better”, such as “Beverly Hills” instead of “Los Angeles”. For that reason too, it’s recommended to keep the vanity address and a platinum relation to the real world place.

This article was written by Henrik Liliendahl Sørensen, a well known blogger whom we hope will be a frequent guest author here. You can find his blog, “Liliendahl on Data Quality” at http://liliendahl.wordpress.com.

This large telecom company is getting ready to do an enterprise transformation program called PROTEA, which stands for Process Redesign, Organizational Transformation and Enterprise Architecture.

They recognized early on that master data management would be a critical part of their new enterprise architecture, so they reached out to Hub Designs last fall, when they were starting to put together their new program. We worked closely with them to help craft an engagement that would focus on developing a Strategic Roadmap and Business Case, and after being home from the Gartner MDM Summit for three days, we headed to South Africa to kick off that engagement.

Our main contact, Maurice, met us in the lobby and quickly ushered us through getting security badges and a quick tour of the facilities. Our first scheduled meeting was with Paul, the MDM program’s business sponsor, who would be an important ally. The meeting went very well, and we promised to work on some introductory slides he could use at the kickoff meeting coming up that Monday.

An hour later, we met the entire PROTEA team, including Maurice’s boss, Clark, plus the organizational change management team, led by Carol, the enterprise architect, Brian, a business analyst named Lisa, and project managers Joseph and Stephan. We were struck by the warm, welcoming feeling we got from the team, and the efficient way everyone got down to business, getting ready for the upcoming week’s workshops on MDM, data governance and the “As Is” and “To Be” states that we would be having with the business and IT community.

The next day, we spent time finalizing the presentations for those workshops, and meeting with the business sponsor again. We also started having some one-on-one meetings with people from the business, and we met with the project manager and talked about how we saw future phases of the program shaping up.

Friday was hectic, as we were putting the finishing touches on the presentations for the upcoming workshops. We would be presenting to and meeting with almost 50 people from across business and IT, and doing an “Intro. to MDM” session on Monday, for 3 hours in the morning, and then 3 hours in the afternoon. On Tuesday, we would do two 2 hour “As Is” workshop, and then on Thursday, two workshops on the desired “To Be” state. All told, we did more than 14 hours of workshops in three days.

Friday evening, the team was very gracious in inviting the Hub Designs folks out, along with the rest of the PROTEA team and a few international visitors, plus everyone’s families, to an authentic South African “brai, which involved a lot of great conversation, adult beverages and huge quantities of barbecued meats. It was a great time, and a very good way to get to know everyone on the team in a short time.

During the week, we also had some one-on-one meetings with a few key IT people who were critical to win over to the MDM initiative. They were skeptical at first, in some cases, but it seemed the meetings went well, and we reached a meeting of the minds that the PROTEA initiative, and the MDM component of it, was something they recognized the need for, and that MDM was something that “made sense” to them. So, a few more potential allies in the enterprise were identified.

The Monday “Intro. to MDM” workshops went very well. Lots of good discussion and questions, very interactive, engaged attendees from both business and IT, good evaluation forms, a big relief at the end of the day that it went so well.

Tuesday’s “As Is” sessions went well too, although it was a little harder because of the mixed audience of business and IT people. At one point, we were discussing some technical questions for a few minutes, and of the business chimed in and said that if we didn’t change the subject back to a more business-oriented track, she was going to leave. We immediately saw that she was right; we were losing the audience. So we apologized, explained that we would change back to a more business-oriented theme, and we’d take technical discussions “offline” if they came up in the future.

Wednesday was a national holiday so that South Africans could vote, but Tim Smith and myself came into the office and worked anyway, getting ready for the Thursday session and preparing for a Friday meeting with Africom’s CIO that had just been set up.

Thursday’s “To Be” sessions were very productive, leading to lots of back and forth discussions with the business users and the IT people about what the destination point for PROTEA should look like.

We used the Gartner Seven Building Blocks of MDM: A Framework for Success as a guide, with some additional Hub Designs frameworks added in as well. Basically, we focused on aligning the MDM vision with Africom’s overall business strategy, then developing an MDM strategy that supported that MDM vision, and creating some metrics (while working towards an MDM business case) that the MDM initiative can impact in a positive way.

Finally, we recognized that without a strong emphasis on governance, MDM is just “throwing technology at a problem” and is unlikely to be successful, so we planned for creating a data governance organization and corresponding processes. Only then did we envision the technology and future architecture that will facilitate the organizational transformation, process redesign and enterprise architecture that PROTEA requires.

Realizing that there are significant gaps between the “As Is” state and the “To Be” state, we dug in and spent a long working session on Friday listing those gaps. On Monday, we’ll prioritize the gaps and identify the gap closure strategies needed to remedy or close all of the gaps we identified.

We also had a great meeting with Africom’s CIO on Friday, who was very receptive and impressed me with his grasp of the implications of a business-led data governance organization on the relationship between business and IT at Africom. We spent 30 minutes talking with him and it was one of the best business conversations I’ve ever had with a C-level IT person.

Over the weekend, Tim Smith and I took a break and drove to the Pilanesberg National Park, a game reserve in the North West Province of South Africa. What a beautiful place! We saw zebra, gazelles, giraffes, Cape buffalo, hyenas, impala. Saturday night, we stayed in Sun City, which was an awesome resort about 15 minutes from the game reserve. Sunday morning, we went back and had the most amazing experience. Five or six elephants walked right in front of our car, including one giant one who stopped directly in front of us, eyeballed us for about 5 minutes, sniffing the hood of the car, even touching it with his trunk, trying to decide whether to charge us or not. Eventually though, he decided we were no threat and he wandered off to join the rest of his family.

We’ve got two more days of meetings, as we discuss the importance of data governance with Clark’s boss, meet with another critical senior IT person, have our gap closure strategies working session, and have a debriefing session at the end of the engagement on what we’ve accomplished, and what are the next steps.

We’ll be coming back in July for another two weeks to finalize the Strategic Roadmap and Business Case, and to spend some time socializing them with the business community and IT leadership that we’ve met on this trip. We’ve really enjoyed the first two weeks of this engagement and are looking forward to the next part in July.

Africom has a lot of work ahead of it as it brings PROTEA from the early stages to the execution stage. We’re looking forward to being one of their MDM and data governance partners, as they take on this massive program.

We look at it as an effort comparable to trying to lift a pyramid – you need someone at each corner and many people in between. “Many hands make light work.”

In partnership with the Africom business and IT staff, the SI firm they’ll engage to assist with PROTEA, and a local consulting firm that also specializes in data management and information quality, we think Hub Designs can continue to make a big impact on the MDM and data governance component of the PROTEA initiative.

The golden records in the hub are formed from the master data records typically describing the customers, suppliers, products and locations in the transactions made in the enterprise application stack. In the master data hub, we emphasize consolidating, and eventually also splitting, the master data (to be) from different contexts into golden records being as close to the real world as needed in the enterprise as a whole.

As in common database theory, we also need relations between the golden records and we may, staying in the metallic tune, call them golden relations.

Golden Relations in the Party Domain

In understanding our customers, suppliers and other party roles, we build hierarchies of the golden records in the golden copy. Typical hierarchies include:

• Consumers belonging to a household
• Company family trees, often derived from external reference data
• Contacts within the companies which are our customers and suppliers

My guess is that we’ll start seeing more advanced relationship tracking in this domain in the near future. An example would be social network-based tracking of contacts changing jobs between parties who are our customers, prospects and suppliers.

Golden Relations in the Product Domain

Hierarchy building in the product domain is much more diverse between industries and in a single organization than hierarchy building is in the party domain.

Therefore, flexible structures are needed within a golden copy or master data hub used for Product Information Management (PIM).

Our ability to handle more products in our databases and the trend towards globalization making more products available will only increase the demand for handling the golden relations between the golden product master records.

Golden Relations in the Place Domain

I like to name the domain of locations as the “place” domain, because then we have a “P” trinity of Parties, Products and Places.

Hierarchies come naturally with places, as they form a geographical hierarchy of the type we like to use, typically being country, state, postal code / city, street name / block, building number and unit depending on where on the earth our place is situated.

The trend of governments around the world making public sector data more open helps a lot in getting the structures of the place master data aligned with the real world.

Golden Relations in Multi-Domain MDM

A multidomain master data hub embracing the “P” trinity of parties, products and places will have some important golden relations between the golden records within each domain like:

• The exact place where a unique party such as a consumer lives. This also helps with forming the right households.
• The exact place of a certain part of a product, being a locality for example in hospitality and travel – and the exact places of the nearby attractions.
• The sales figure in a defined period for products belonging to a given category sold to parties being companies in a given line-of-business.

Most interesting business problems require more than one domain of data for their solution.

Platinum Relations

Master data may be born in the hub or may be born outside the hub and then transformed into the hub, thus becoming the golden copy.

Transforming already existing records representing parties in the prospect and customer role into the hub is still the most common direction today. Therefore that discipline is still often called Customer Data Integration (CDI).

In this process, it is highly recommended not to purge the records and relations that already exist when we merge data into golden records. You should keep the incoming records with a platinum relation to the new golden record as it sometimes happens that you have to rollback.

Mass import and transformation of data also happens in the product domain, for example at retailers. Also here it’s recommended to keep the original data and make platinum relations.

In some places, I’ve come across a case of “keeping up appearances”, called vanity addressing. Here your customer insists on using a somewhat incorrect address that “sounds better”, such as “Beverly Hills” instead of “Los Angeles”. For that reason too, it’s recommended to keep the vanity address and a platinum relation to the real world place.

This article was written by Henrik Liliendahl Sørensen, a well known blogger whom we hope will be a frequent guest author here. You can find his blog, “Liliendahl on Data Quality” at http://liliendahl.wordpress.com.

You can retweet this by cutting and pasting >> Great #MDM article on Hub Designs by Henrik Liliendahl Sørensen: “Golden Relations and Platinum Relations” at http://wp.me/p5Tdn-Bp

This week, I attended David Butler’s presentation at the Oracle Applications Users Group COLLABORATE 11 conference in Orlando, FL.  David Butler has been with Oracle for almost 14 years, and has been with the Applications side since 2001.

If you don’t fit MDM into an architectural vision, you’re just throwing “stuff” at a problem.

The data is fragmented – it’s all over the place, in CRM, in ERP, in different divisions, locations, processes, formats, and silos. And it’s in a state of flux, with potentially thousands of points of entry. Master data changes at a rate of 2% per month – across companies, individuals and products. This represents a huge cost of doing business.

But don’t just throw technologies at the problem. There’s an alphabet soup of different tools and products you can purchase, but you can wind up making things much more complex. You want to make things simpler (not more complex).

Start with the applications, the CRM, supply chain, operations, web sites, financials, distribution, ERP, product lifecycle management, etc. People have been writing code for “point to point integration” for many years – the “N squared” problem – the “hairball”. This isn’t sustainable. This is what drove the creation of Enterprise Application Integration (EAI) originally. This metadata layer, with adapters for each application, supports dozens of applications. But the data in the applications, is still inconsistent in format, and this approach still doesn’t address the quality of the data.

More recently, we’ve had the concept of orchestration across the enterprises, using web services and standards across all of these various types of applications. But again, we’re just inventing new ways to break processes. And even more recently, we’re moving things to the cloud, which in some ways, opens up Pandora’s Box, because it moves some things out of our reach into the cloud.

The data warehousing approach moves everything from the applications into an enterprise data warehouse. This has been around for a long time, and is still very powerful. But in some important ways, it doesn’t deliver the “Single View of the Customer”, because it can be a case of “Garbage In, Garbage Out”.

What you need is a Master Data Management solution, which gives you a chance to consolidate the data into the MDM hub, to cleanse it and govern it, and to move it back to the source applications. Then the business processes can use the cleaned and improved local data. You get a chance to improve your business processes. The transactional data finally gets cleaned up, and you can feed that clean data to the data warehouse, and you can do meaningful analytics in a business intelligence solution on top of the data warehouse.

Some companies started building the improved data in an MDM hub strictly for analytical purposes, and feeding it into their data warehouse for BI. But when they saw how good the data was, they started feeding that data back into their operational system too.

The data hub is the data model, plus the purpose-built applications like Oracle Customer Hub, Oracle Product Hub, Oracle Site Hub, etc. (state of the art applications, which Gartner has recognized as belonging in the leaders’ quadrant of the Gartner Magic Quadrant).

Oracle can use its own ETL tool (Oracle Data Integrator, ODI) but can also use other ETL tools as well.

Oracle has a state of the art product for hierarchy management, Data Relationship Management (DRM), which can manage complex hierarchies for many different domains of master data.

Oracle also provides BI Publisher as a business intelligence tool that runs against the MDM hub, to provide useful reporting against the master data that accumulates there.

The EAI that Oracle provides is Fusion Middleware, which provides an Enterprise Service Bus.

With the Sun acquisition, Oracle can provide an integrated hardware stack to run the MDM hub and the data warehouse on the Exadata and Real Application Clustering environment.

Oracle’s recommended Master Data Management process is (a) Consolidate, (b) Cleanse, (c) Govern, (d) Share.

This process allows you to add attributes to the underlying data model, and the data quality tools that are built into the MDM hub will operate against those extended attributes.

Oracle’s suite includes:

• Oracle Customer Hub
• Oracle Supplier Hub
• Oracle Product Hub
• Oracle Site Hub
• Oracle Hyperion Data Relationship Management

Today, the applications have their own individual user interfaces for data governance, but the roadmap eventual will move them to a common data governance user interface.

Oracle MDM high level architecture is based on an MDM framework, with the MDM applications on top, and verticalizations for key industries on top of that.

MDM and Service-Oriented Architecture: MDM without SOA will be a single version of the truth in its own silo. SOA without MDM is an enterprise-wide service without reliable data that breaks at the application boundary.

Forrester referred to MDM and SOA as the most important business case with the most return.

MDM and Business Intelligence: this gives you the quality governed dimensions, the corporate cross reference and the hierarchies needed for accurate roll-ups.

David Butler gave a great example of a consumer getting married and changing her name, two manufacturers who are both subsidiaries of the same D&B global ultimate, two suppliers who are the same but with different D&B trade style names, and two products with different descriptions that are actually the same.

So the example illustrates how a data warehouse can return wrong answers unless you “work the data” through Master Data Management and data governance.

The strategic nature of MDM is:

• Foundation for Customer Relationship Management (CRM), Enterprise Resource Planning (ERP) and Supply Chain Planning (SCP) deployments
• Foundation for Service Oriented Architecture (SOA) deployments
• Foundation for Business Intelligence (BI) deployments
• Key to corporate data governance
• Key to business process optimization (BPO)
• Operationalizes the data warehouses
• Path to IT agility

From time to time, Hub Designs highlights an MDM-related position as a courtesy to a friend of the firm. This position is being listed for Steve Minor at Microsoft, whom I’ve known for several years.

As readers of this blog may know, Microsoft is working on a very high end MDM solution (for its internal use, not as a product).

Microsoft’s internal MDM platform can support in excess of 2 billion customer records, and it’s meeting its performance goals of ~2,000 transactions per second (updates) while hitting its 400 millisecond Service Level Agreement.

The team is onboarding approximately 20 applications inside of Microsoft. The solution is fully High Availability and Microsoft is also implementing Disaster Recovery.

In fact, the Microsoft team is coming up on its 5th of 5 releases (due in September).

The exciting part is that after this 5th release, the goal is to take the “platform” to the next level and truly “platformize” it in terms of moving it to Microsoft’s Cloud, creating a “Platform as a Service” (PAAS) and broadening it to support master entities, and in fact, any entity that needs large scale storage, performance and all of the enterprise class features around instrumentality, monitoring (Availability and Quality of Service), fail-over, etc.  The team wants to do this over the next 2-3 years, all the while adding new entities.

To do this, Microsoft needs to hire a senior/principal level technical Program Manager.

Ideally, this person has been a strong developer in the past (a “dev lead” or architect type) that has worked heavily with transactional type systems (like MDM) where they understand well the design approaches and issues in solving many of the complexities that a complex MDM solution would run into.

This person must have good verbal and written communication skills, and be comfortable at writing strong functional design specifications.  Microsoft is open to bringing in a pure developer that wants to make the transition to Program Manager.

In reality, as a technical Program Manager, this person would leverage and utilize a broad set of architectural, design and to a lesser extent evangelist type skills.  To be clear, this would not normally involve any actual coding, but POC work does offer some opportunities in this area.

The candidate should be familiar with some portion of the following list of skills (the more the better):

• Single version of the truth concepts (core MDM stuff) for a central Hub design
• High scale persistency in a relational database (SQL Server, etc.)
• 2 Way synchronization with many disparate applications
  • Integration patterns (sync, async, batch)
  • Mapping of fields (semantic, metadata definitions, etc.)
  • Security concepts around windows auth, and certificates in those integrations
• Pub/Sub async notification integrations
  • Subscription concepts
  • Key mapping concepts (centralized vs. decentralized)
• Scale up and scale-out patterns
  • Multi-threading
  • Database partitions
  • Configuration management across many servers, etc.
• Performance management
  • Defining performance criteria, SLA needs
  • Managing performance sub-team
• Standardization technologies (Trillium, etc.)
  • US CAS, Canadian SERP, international
• Matching technologies
  • Deterministic, Probabilistic
• Platform concepts (re-use, housing many types of entities in a common framework, etc.)
• Integrations with EDW/BI for analytics
• Reporting in general (operational, etc.)
• Understanding integration concepts/difficulties across multiple network domains (trust, etc.)
• Understanding of privacy laws (for individual type data)—US and international (this helps with paradigms of understanding legal and audit requirements)
• Encryption/Compression

Being at Microsoft, we’re largely using MS technologies, including .Net C#, SQL Server, etc.  Having equivalent skills in Java, Oracle and others would be acceptable.

Any knowledge on Microsoft’s Cloud (Azure, etc.) or other Cloud aspects would be a plus too.

This is an awesome opportunity for someone wanting to work on a large complex n-tier DIY MDM type solution that scales to levels that no vendor COTS solution can match.

I realize that as with any opening like this, it appears we need someone that can cure cancer, and get someone on Mars. The fact is, we need a real sharp candidate that has a track record of getting the job done on a large team.  Having a few holes in experience can be overcome.

Microsoft has a strong reputation for benefits and compensation, and that it can also be a bit intense.  This is a classic 50 hour work week type job, with a few spikes here and there. It’s for someone that is quite senior and wanting the challenge.

If you’re interested, please contact steveminorjr@yahoo.com.

His first question was about AbiliTec IDs for individuals. He wondered if this was an Axciom product or an industry standard identifier.  He was looking for a way to uniquely identify customers from the web, retail point-of-sale (POS), and other marketing channels for a client who doesn’t have any useful way of identifying the same customer across channels.

I’m familiar with AbiliTec IDs (Acxiom calls them AbiliTec links). It’s a persistent identification scheme for consumers and addresses, issued and controlled by Acxiom, similar to how D&B issues and controls the D-U-N-S Number for businesses. There’s a good brochure available on Acxiom’s UK website.

To answer his specific questions, it’s definitely an Acxiom product, not an industry or open standard identifier. So one can only get AbiliTec links by working with Acxiom in some way, shape or form.

As far as uniquely identifying individuals across channels like the web, retail POS, and other marketing outlets, that’s pretty much exactly what AbiliTec is used for – think of it as a high speed matching engine that will return AbiliTec links for every consumer record you feed it.  The downside is you’ve got to pay Acxiom for the privilege. But like D&B, they’re pretty good at helping you create the business case to justify the expense.

Then my friend came back with another question: are there any competing products for the AbiliTec link?

My answer was: none that I know of that are as widely accepted. The three consumer credit bureaus (Equifax, Experian and TransUnion) all sell their own persistent consumer IDs too, but in my opinion, Acxiom’s is very good at that particular task.

Products like DataFlux, Trillium, Informatica, IBM’s QualityStage and SAP BusinessObjects can also generate a key with the same value given varying input, so that different representations of the same person, such as

• John O’Connor, 30 Palomino Lane, Westwood MA 02090
• J. J. Oconnor, 303 Palomino Lane, Westwood MI 02093
• John Joseph Connor, 30 Polo Pony Court, Westawooda RI 02021

will all generate the same key value.  So you can use that generated key to identify the person across three different channels.

Of course, it all depends how well you write and tune your business rules, too. If you write them too tight, then the three records above won’t generate the same key after all. Write them too loose, and a bunch of other records will also generate that same key value and you’ll end up with a bunch of false positives (non-Johns).

The beauty of Acxiom’s approach (and D&B’s for that matter when you’re interested in businesses) is that they’ve both got anywhere from hundreds of millions to billions of records of reference data to work with – both to refine their match engine and business rules, and to match against.

So when you’re comparing records, you’re not just comparing these three representations against one another, you’re comparing them to all of the historical addresses this person has lived at over the last 25 years, and all of the other versions of their name of file from marriages, divorces and name changes. Don’t underestimate the power of the database!

You can retweet this by cutting and pasting < New on the Hub Designs Blog: “Matching (That Is, Entity Resolution) Revisited” at http://wp.me/p5Tdn-yS >

Image courtesy of Infoglide Corporation

photo © 2008 Toshiyuki IMAI | more info (via: Wylio)

Now that 2010 is over, we can share some readership statistics with you.  Through Dec. 31, 2010, our total views since inception (in July 2007) were 101,078 (including RSS traffic).

We were excited to see that overall readership was up 14% in 2010 vs. 2009 (and 2009 was up 96% vs. 2008).

This offers some great opportunities for exposure for guest authors. Some of our most popular articles on the Hub Designs Blog have been written by guest authors such as James Parnitzke, Rob DuMoulin, Maureen Butler and Joan Lawson.

So, as we start off 2011, we’re looking for new writers – new perspectives, new talent, new ideas. We’re looking for people like you, our readers, who are (like we are) out on the front lines of master data management and data governance.

Whether you’re working through the education process with your team, or developing your strategic roadmap for MDM and governance for the next few years, or creating a business case to convince your senior management to fund your MDM initiative, or conducting a vendor evaluation, or in the middle of implementing an MDM hub – we want to hear about it!

By all means, sanitize your stories, and change the names of the guilty to protect the innocent, disguising the identities of the companies and individuals where needed. But share your lessons learned, your best practices, and your “things not to do” with the rest of the MDM Community.

If you’re interested in writing for the Hub Designs Blog, please check out the Author Guidelines first, and then get in touch using the Contact Us page on our web site.

We’re looking both for people willing to write on a regular basis, and for people looking to contribute a single or occasional guest article. Please include a brief abstract of your article in your message, and we’ll reply to everyone we hear from.

This is a “triple win” – you gain from the exposure your article will get on the Hub Designs Blog, we gain from working with new writers with interesting perspectives, and of course, our readers gain from the great content that we’ll be able to bring together for them.

So get your “thinking cap” on and start writing! Then reach out to us using our Contact Us page.

The combination of Siperian with Informatica has exceeded their expectations so far, with MDM revenue running significantly ahead of quota and Informatica landing customers in a number of new vertical industries such as retail, healthcare, aerospace/defense, agriculture, education, and hospitality. Informatica continues to penetrate EMEA and has had its first successes in Asia Pacific and Latin America as well.

There’s also a healthy sales pipeline being built for future quarters, with the top three verticals being healthcare and life sciences, financial services and insurance, and high tech and retail. Growth is being seen all over the world, with a large percentage of the bigger sales opportunities for Informatica involving MDM, regardless of the region.

Ravi highlighted how the Informatica Master Data Management (MDM) solution is solving multidomain business problems like physician spend compliance, product mastering, high volume reference data mastering, clinical trial management, customer and channel management, and Salesforce.com enablement. He also discussed how Informatica’s other products usually fit into an MDM solution.

As the Informatica MDM product has evolved, it has remained true to its roots, and continues to offer complex hierarchy management, to be business user focused, and to allow for fast time to value. What Informatica has done, building on what Siperian had created before its acquisition, is to provide for true multidomain master data management, which allows for a much wider range of problems to be solved.

Informatica continues to increase its market share beyond the pharmaceutical vertical, and shows a strong track record of expanding its footprint within existing customers as well.

Informatica MDM Data Director has been widely used as well, with every new customer since its release in March 2009 buying it along with the MDM hub.

Informatica just finished up an 18-city MDM road show in the U.S. and Canada, and featured its MDM product prominently at Informatica World in early November. It has both a horizontal and a vertical industry marketing strategy.

Ravi previewed for us the materials for their “Customer and Channel Management Solution”, which manages hierarchies and relationships between customers, channel partners, products, and resources, in order to maximize account penetration, optimize coverage, and enable business agility and speed.

Ravi also gave us a demo of the latest version of the Informatica MDM product, with built-in dashboards using Data Director measuring data quality for individual customers and organizational customers. He also demonstrated the integration of MDM with the rest of the Informatica Platform – Power Center Business Glossary and Metadata Manager, and Informatica Data Quality.

Another impressive feature is enabling business applications, such as Salesforce.com, to be MDM aware. New records can be entered in the Salesforce.com application and instantly be bounced up directly against the Informatica MDM hub, and customer hierarchies can be viewed in a Salesforce.com tab, rather than requiring the user to jump back and forth between a Salesforce window and an Informatica MDM window. And the Salesforce user can see a timeline of a record “as of” a particular date, including all the hierarchy data.

At the end of the briefing, I came away feeling (again) that Informatica had made a great move in purchasing Siperian, and that Informatica’s MDM business has clearly gained momentum since the acquisition. This is clearly one of those cases where one plus one equals three. Informatica has done a great job integrating Siperian into the company, in taking advantage of the synergies between the two companies, and in promoting the product. Opportunities exist to take it even further, but the Informatica team is to be congratulated, since almost 60% of all mergers and acquisitions fail to create shareholder value according to the Boston Consulting Group.

Gartner Research is predicting 14% growth over 2009 levels for master data management (MDM) software license revenues, to $1.5 billion.

Business drivers for adoption range from delivering revenue, service, agility and risk management improvement, cost reduction and integration simplification. John Radcliffe, a research vice president at Gartner, said ”Today, most organizations juggle multiple sets of business and data applications across corporate, regional and local systems. At the same time, customers are demanding faster and more complex responses from organizations, leading to an inconsistency that hinders the organization’s ability to measure and move within the market. With MDM, CIOs can create a unified view of existing data, leading to greater enterprise agility, simplified integration and, ultimately, improved profitability.”

Some interesting predictions were included in the Bank Systems & Technology article:

• From 2009 through 2014, MDM software markets will grow at a compound annual growth rate of 18%, from $1.3 billion to $2.9 billion.
• Gartner foresees a larger, more unified MDM software market reaching nearly $3 billion by 2014.
• By 2015, 10 percent of packaged MDM implementations will be delivered as software as a service in the public cloud (MDM today is typically implemented on-premises)
• Through 2015, 66 percent of organizations that initiate an MDM program will struggle to demonstrate the business value of MDM.

This is not because MDM can’t show sufficient business value. The Bank Systems & Technology article goes on to say “If IT departments initiate an MDM initiative, they often struggle to get the business on board and to demonstrate the business value of MDM, particularly if there are no business-process-oriented metrics and financial quantifications to define and measure success, Gartner analysts say.” (emphasis added)

At Hub Designs, like many other MDM practitioners, we’ve been saying for quite a while that the business needs to own the MDM initiative.  This isn’t always a popular stance, particularly when the people bringing you into a particular client company are the IT people.  But it’s the truth – if the business doesn’t own it, the business won’t feel ownership.

The article goes on to say “MDM needs to align with the business vision and strategy, and will require executive business sponsorship, strong involvement of business stakeholders and change management.”

“It’s not just an IT project. The business needs to take responsibility and be accountable for master data governance and stewardship,” says Radcliffe.

“Unless organizations take a holistic, business-driven approach to MDM, addressing governance and metrics requirements in particular, they risk having their MDM programs fail,” he says. “Internal politics won’t be brought under control without a governance framework, and without a metrics structure, there will be no way of objectively defining what success looks like and measuring whether or not it has been achieved.”

We couldn’t agree more. In our “Ten Best Practices” series this October, we specifically discussed that topic in Master Data Management Best Practice #10 – Use a Balanced, Holistic Approach, saying “This may be the most important best practice of all: use a balanced, holistic approach – addressing people, process, technology and information. Start with the people, politics and culture, and then move on to the data governance and stewardship processes, then the technology.”

The MDM initiatives that companies are taking on right now aren’t “too big to fail”, but they are too important to fail.

As a long-time MDM evangelist, who is used to describing MDM and data governance in such a way that people get excited about the change it can make for their companies, I think we need the types of economic and technological changes described in Penny Crosman’s article. Too many companies are lurching into the 21st century with the baggage of a late 90′s technology infrastructure holding them back. Faster, better decision-making, increased revenue and reduced costs, easier compliance and risk management, improved business and IT agility – these are things that aren’t going to come easily but they are worth it, and MDM and data governance are a big part of the answer for a lot of companies.

So hats off to Penny Crosman and her article in Bank Systems & Technology, and to John Radcliffe and Andrew White at Gartner Research for all the good work that they do.

Dan Power: Informatica MDM Tweet Jam like playing “stump Dan” – see if you can perplex, mystify and amaze me!

Dan Power: Actually, just kidding – want to have a good dialogue with everyone – would love to have a good MDM discussion.

Informatica Corp.: Right now! Join the #MDM TweetJam with @dan_power. 9am PT.

Dan Power: OK, the Tweet Jam is officially open!

Jakki Geiger: Dan, what are the most common concerns you hear about MDM?

Dan Power: IT people still seem concerned about how to involve the business and sell it to senior management.

Jakki Geiger: what advice do you give them?

Dan Power: IT seems to know that MDM is needed but sometimes can’t seem to get the business on board, and it can be hard to pitch to the C-Suite.

Dan Power: We advise building a compelling business case – getting outside help if needed – and recruiting internal business champions.

Jakki Geiger: What strategies to get the business on board have you seen work?

Dan Power: I wrote an article about that in a recent Information Management magazine and a blog article on Hub Designs Blog that accompanied it.

Jakki Geiger: We’ve seen IT successfully tie MDM to key strategic imperatives like improving cross-sell and up-sell=getting sales on board.

Ravi Shankar: One thing we have done to help IT is to quantify how much DQ issues can cut costs or increase revenue.

Dan Power: Getting the business on board means STARTING in the business – find out their pain points and recruit them to drive from Day 1.

Jakki Geiger: Others include onboarding channel partners onboard faster, which appeals to sales and channel operations.

Jakki Geiger: A huge driver has been regulatory compliance = appealing to those who gather data across the enterprise and create reports.

Ravi Shankar: I like what Charles Bloodworth of J&J said at Informatica World 2010 – “MDM is not just a project; it’s a discipline – a way of doing bus for us”.

Dan Power: Good points Jakki & Ravi – those are the pain points I’m talking about: increasing revenue / onboarding channel partners faster.

Jakki Geiger: One area I think is really going to take off is improving business processes = improve data to improve the process.

Jakki Geiger: One exec got buy in from exec team with “we need to manage our product supply chain and info supply chain equally efficiently”.

Ravi Shankar: Agreed – bus needs to be involved in MDM. Charles of J&J said bus involvement drove their MDM and data governance success.

Dan Power: That’s right – becomes a way of life – new discipline for the business – to have a golden copy of the data that they can trust.

Jakki Geiger: I agree with u. IT needs to understand what the business pains and strategic imperatives are, then evaluate “can MDM help?”

Dan Power: Product management and supply chain are just as fertile for most companies as customer data – so MDM is just getting started.

Dan Power: I’ve been talking to a lot of companies lately that have already done customer MDM and are now looking at doing product MDM.

Ravi Shankar: Product MDM: I see lot of demand for this from manufacturing companies. Just came from S. Korea – product MDM is hot.

Dan Power: Or even supplier MDM – in order to get global strategic sourcing initiatives off the ground, which can save millions of $.

Ravi Shankar: Customer MDM to product MDM – we’ve seen that with our own early customers – They leveraged the same Informatica platform.

Julie Hunt: How do you see MDM implementations evolving to take advantage of newer tech such as ‘cloud’?

Julie Hunt: And what advantages does the cloud offer to MDM solutions?

Dan Power: Good question, Julie – definitely see a movement towards the cloud – people don’t want to create tomorrow’s “legacy systems”.

Dan Power: So they increasingly are asking their vendors about cloud deployment options, even if they don’t rush to take advantage of them.

Dan Power: They want to know they’re available

Dan Power: To Julie’s Q about cloud, I think eventually we’ll see cloud deployments at lower cost than on-premise (particularly hardware).

Ravi Shankar: Let me outline 2 use cases we’ve seen @ InformaticaCorp.

Ravi Shankar: Use case 1: During peak times like holiday seasons, retailers can burst into cloud for additional capacity.

Ravi Shankar: Use case 2: Mktg mgrs can use self service tools to upload attendee list from event w/o having to bother IT.

Dan Power: The promise of cloud for me, is more flexibility as my business grows and if we have seasonal peaks and valleys of demand.

ocdqblog (Jim Harris): What do you say to companies that expected that from their data warehouse? How is MDM different from conformed dims?

Ravi Shankar: ocdqblog – welcome. Looking forward to a lively MDM discussion.

Dan Power: Good question, Jim. Most companies had unrealistic expectations from data warehouses, which ended up being expensive, read-only,

Dan Power: and updated infrequently. MDM gives them the capability to modify the data, publish to a DW, and manage complex hierarchies.

Dan Power: So to finish answering your question Jim, I think MDM offers more flexibility than the typical DW.

Dan Power: That’s why BI on top of MDM (or more likely, BI on top of a DW that draws data from an MDM) is so popular.

Ravi Shankar: MDM for DW – 90% of Informatica MDM customers use it for analytical use (in addition to operational).

ocdqblog (Jim Harris): Thanks Dan – Follow-up is do you see MDM as compliment or replacement for DW?

Dan Power: Definitely a compliment – fills void in the middle between trx systems and the DW – does things that neither can do to data.

Jakki Geiger: are you seeing this trend? Evolving beyond single customer view= visibility into 360 customer view w/products and channels, etc.

Dan Power: Yes, Jakki – people want more than a single view – they want multiple views on top of the single view.

Ravi Shankar: Siperian customers – We’re having a lively chat on MDM and data governance. Join in!

Ravi Shankar: Dan, what do you tell DW admins that DW provides their single view for enterprise?

Dan Power: I tell DW admins that most people in the enterprise aren’t completely happy with DW – that’s why there’s pain leading to MDM.

Jakki Geiger: Since the driver of MDM is the business, how are we getting master data into the hands of the business?

Dan Power: Good Q, Jakki – getting MDM data back into hands of the business should be built into the project – and the software platform.

Ravi Shankar: Compliance is driven out of DW – you need MDM for accurate compliance reports – Do you agree?

Dan Power: Yes, Ravi – Garbage in, Garbage out – you need quality data from the MDM system to feed into the data warehouse.

Julie Hunt: So we must advocate value of data governance as well as value of MDM with business, senior management?

Dan Power: I tell people to think of their initiative as a data governance project that happens to involve #MDM technology.

Dan Power: Not an #MDM technology project that requires data governance.

Dan Power: And to start the data governance piece about 6 months before the technology piece, if possible.

Julie Hunt: The importance of data quality = another layer to be advocated to the business and to management – show them the impact on outcomes.

Jakki Geiger: MDM is like a Ferrari. If you don’t use DQ with MDM, it’s like putting regular gas in Ferrari=sub optimal performance.

Dan Power: I’ve seen people try to do MDM without data quality – and it’s a disaster, like trying to run a submarine on dry land!

Dan Power: The fact is that #MDM and data quality are linked, just as #MDM and data governance are linked.

Ravi Shankar: Should data quality be integrated within #MDM?

Dan Power: Good question, Ravi – I’ve seen it both ways – a data quality engine integrated with the MDM platform or separate, both can work as long as the data quality tool is robust and the integration is solid, shouldn’t matter.

Dan Power: Most MDM platform vendors are not equally good at developing data quality tools – Informatica is one of the few that is.

Julie Hunt: How much does corporate culture impact success/failure of projects for #MDM, data governance etc.?

Dan Power: Great Q – corporate culture is a huge impact on success because data governance drives MDM and requires a lot of change mgt. So spend a lot of time on org. change in the data governance side of the #MDM initiative in order to be successful.

Ravi Shankar: Heard a customer say – “Don’t overdo data governance – do just what’s necessary” Do you agree?

Dan Power: I’d agree not to go overboard on data governance – balanced approach that’s right for your co. just enough to get the job done. Too much data governance can be worse than not enough – can be bureaucratic – the “data governance police”.

Ravi Shankar: Data governance applies to all data, but I hear that in MDM context a lot. Do you hear “master data governance” for MDM?

Jakki Geiger: Some argue shouldn’t call it data governance because the -ve connotation of “governance” thoughts?

Dan Power: I actually like that phrase – master data governance – makes it more clear and precise what we’re talking about

Dan Power: Because otherwise, data governance organization can get drawn into all kinds of weird things not related to master data

Dan Power: We need to recognized that data governance is (a) political, (b) controversial, (c) going to have an enforcement side.

Ravi Shankar: Now, do orgs do data governance first before implementing MDM or after they select an MDM product?

Dan Power: So in some ways, I actually like the term “data government” better – makes it more explicit what we’re talking about.

Dan Power: And it reminds people that we’re talking about governing the enterprise’s core master data – just like we govern other key assets.

Jakki Geiger: I think the challenge is that we’re still in the process of understanding that data is a strategic asset.

Dan Power: It’s ideal if they can start data governance before even selecting a product – so that the data governance org. can help w/ the selection process.

Ravi Shankar: Dan wrote an excellent whitepaper – “When Data Governance Turns Bureaucratic” – you can download it from http://bit.ly/ck2Gw8.

Dan Power: Truly competitive 21st century companies not only understand that data is a strategic asset, it’s how they run their business.

Dan Power: Forward looking businesses like Google, Amazon, Century 21, eBay, etc. realize that the data IS their business!

Jakki Geiger: “Data as strategic asset” is a fairly new concept. Visionaries recognize need 4 scale and intelligence=harnessing & analyzing data.

Dan Power: That was a fun white paper to write – looking forward to doing another one with the great folks at Informatica again soon!

Jakki Geiger: What I liked about Dan’s WP was the discussion around stopping the problem of data quality at the source.

Seth Grimes: Is data governance also (d) useful on balance and (e) capable of delivering ROI?

Dan Power: Yes, of course – or people wouldn’t be doing it. You can’t bring together massive amounts of data in an MDM hub and not have some type of governance framework in place. And if there was no ROI, it wouldn’t be happening.

Dan Power: I’m pretty familiar with Oracle’s data governance program, and for a huge company, it’s not real expensive.

Ravi Shankar: Welcome to #INFATJ – good data governance question.

Ravi Shankar: Successful Informatica MDM customers like J&J, Merrill, and numerous others have had strong global data governance orgs.

Ravi Shankar: Data is a key asset that many firms make a lot of money out of it – Bloomberg for e.g.

Ray Wang: RT @Ravi_Shankar_: Data is a key asset that many firms make a lot of money out of it – Bloomberg for e.g.

Dan Power: Good example with Bloomberg – welcome Ray!

Ravi Shankar: @rwang0 thx for the RT

Jakki Geiger: Can you create a career out of MDM? Many of our customers have extended MDM to address more and more issues in their orgs.

Dan Power: Good Q, Jakki – u can create a career out of it, I have for the last 6 years, but you’ve got to really have this in your blood

Ravi Shankar: Within Informatica customers, we’ve seen careers of several people take off b/c of successful #MDM data governance.

Julie Hunt: Thanks for great tweet jam!

Jakki Geiger: Thank you for participating! Looking forward to next time. Good luck to you all!

Dan Power: Thanks for joining us today – hope you enjoyed it! Check out the Hub Designs Blog at http://blog.hubdesigns.com.

Ravi Shankar: Thx for your insightful discussion and advice on #MDM data governance. Hope you all enjoyed it. Until next time!

Dan Power: This is Dan Power, signing off – have a great day everyone!

A shorter, more targeted project (vs. the “ultimate” whiz-bang project with all the technology bells and whistles) pays off better in two important ways:

1. Generally, the costs are lower, because you’re incurring them for a shorter time. That’s obviously not always strictly true (some crash projects can end up being very expensive) but a 6-9 month project usually tends to be less expensive than a 12-24 month project.
2. You’re delivering the expected benefits that much sooner. So whatever value the business is going to gain from your MDM initiative, it will get that value roughly twice as fast if you can go with the targeted 6-9 month project instead of the 12-24 month “mega project”.

If you think back to our recent article on MDM Best Practice #1 – Start with the Need, Pain or Problem (Not “The Solution”), what the business really wants is for their problem to be solved. They don’t want the most elegant solution with the latest ‘whiz bang’ technology.

They’d like to be able to recognize their customer at all touch points; to be able to add new customers easily without accidentally creating a lot of duplicates; to be able to manage customer creditworthiness and risk in an efficient manner; to roll up sales by the customers’ corporate hierarchy; to be able to efficiently identify the untapped prospects in a corporate family, geography or vertical market; to be able to tie all interactions with a customer back to a single view of that customer; and so on.

Not a lot to ask, they’d probably tell you. They’ll probably ask, why can’t we do that now? After all the investments in all the ERP and CRM systems, in all the data warehouses, data marts and business intelligence solutions, we come along with MDM platforms and (gulp) data governance.

We tell the business users that with MDM, on the one hand, we can help them with their burning problems that never seem to get solved any other way. But on the other hand, it’s going to take their direct involvement in a way they’ve probably never had to do before: data governance.

So it’s matter of “to whom much is given, much is expected”. The business will have a new capability that will solve some important business problems, but the business owners and users will have to step up in a way they may not have had to before, by taking ownership of the data, setting policies around data quality, accuracy, completeness, timeliness and consistency, and then agreeing to enforcement of those policies.

Data government is primarily a political endeavor, and as a result, MDM projects have an explicitly political side to them. Be prepared for that, and remember, faster is better.

Contact Hub Designs for advice on your MDM or data governance initiative.

I’ve tried to emulate him by being an evangelist for customer and product MDM. From 2001 to 2004, I was a consultant working with the precursor to Oracle’s Customer Data Hub platform. At D&B from 2004 to 2007, I managed its strategic alliance with Oracle while Oracle launched and refined Customer Data Hub. I left D&B to start Hub Designs in 2007 because I wanted to work more directly in developing and executing MDM strategy at corporate clients. All this time, I’ve tried to get people excited about using the evolving technology to solve business problems.

In the past nine years, in all of the different industries and companies I’ve worked with, most have quickly “gotten” MDM:

• They understand the value of the Single View of the Customer (or Product, as the case may be).
• They see the revenue increases from being able to up-sell and cross-sell customers by knowing more about them, and by knowing their own products better.
• They understand the dollar value of having a streamlined, coordinated New Product Introduction process.
• They see the short payback period and millions in savings from a strategic sourcing program that consolidates vendors and products, and renegotiates agreements.
• They understand the contribution MDM makes to credit risk management (know your customer, and whether they can pay their bills on time).
• And they see how MDM (done properly, which includes data quality improvement and a data governance program) makes it much easier and more efficient to have accurate, complete, timely and consistent information available for compliance with governance regulations.

But all of those organizations, where I’ve been the “external champion” or evangelist, have needed a corresponding “internal champion” or evangelist.

Someone to lead the charge internally, to have the hallway conversations, to fight the good fight politically, to scrap for every budget dollar, to convince the powers that be, the type of person who digs in and doesn’t let go. Someone who’s convinced that master data management and data governance is important to his or her company. That it’s so important that it’s worth going out on a bit of a career limb. Or who perhaps was brought in specifically to head up an initiative like this.

My friend Tom Carlock wrote a great article called “So You Want to be a Data Champion?”, where he discusses how to be prepared to be your organization’s “data champion”. Tom knows whereof he speaks, because he’s been in roles like that at The CIT Group and AIG, and is now a leader of product strategy at D&B. He mentions attributes like being able to have a consistent vision that you can “sell” to others, the ability to develop and maintain relationships, being able to listen, ask for input and deal with objections, and being optimistic, hopeful and patient.

To that I would add, being persistent. My father introduced me to a quote by Calvin Coolidge, the 30th U.S. President:

“Nothing in this world can take the place of persistence. Talent will not; nothing is more common than unsuccessful people with talent. Genius will not; unrewarded genius is almost a proverb. Education will not; the world is full of educated derelicts. Persistence and determination alone are omnipotent.”

If you decide to become an MDM evangelist at your company, and you’re persistent in that role, you can help your company manage master data as an enterprise-wide asset – and transform itself in the process. I think our corporations today – ten years into the twenty-first century – desperately need that type of innovation and change.

Start with the people, politics and culture, and then move on to the data governance and stewardship processes, then the technology.

The recent Gartner “Magic Quadrant for MDM of Customer Data” by John Radcliffe had a great statement: “To succeed, you should put together a balanced MDM program that creates a shared vision and strategy, addresses governance and organizational issues, leverages the appropriate technology and architecture, and creates the necessary processes and metrics.”

Another illustration of the need to balance the technology with the people and process is a quote by the inventor and entrepreneur, Dean Kamen: “The technology is the easy part. Understanding what drives people – individuals, societies, what makes cultures clash – all of those questions are way, way harder to answer than how to solve any particular technical problem.”

This Best Practices series is based on a talk that I’ve given at the Oracle Applications Users Group COLLABORATE and Oracle OpenWorld conferences a few times. The talk has evolved each time I’ve given it, but one consistent theme has been “being an MDM evangelist”. I believe in the nature of master data management and data governance to fundamentally change the IT architectures, business processes and organizational cultures (how we think of the core data that we use to run our businesses). And I think corporate America is overdue for these changes.

We’re all consumers who’ve had frustrating experiences with companies trying to do simple things like changing our addresses, stop receiving extra copies of catalogs, fixing errors on credit reports, etc. And we’ve all had the opposite experience, when a quick phone call or self service Web portal took care of everything. What a difference in the customer service experience!

And in the business-to-business world, there are a lot of companies out there that would like to make decisions more quickly, based on reliable data, that would like to reduce their supply chain spend, consolidate their enterprise applications, increase their revenue by up-selling customers, get paid more quickly by making sure invoices go to the right address every time, manage credit risk for new customers, understand customers’ corporate hierarchies, cut their new product introduction life cycle in half, and so on.

These are the types of innovations that our companies desperately need to be competitive in the next decade. The economy is improving – but slowly. As an MDM evangelist, what improvements and innovations can you bring to your company? And can you use the balanced, holistic approach to make sure that the shiny, new technology doesn’t outweigh the people, process and information sides of the picture?

You’ll succeed if you recruit the right executive sponsors; invest in creating a data governance team; design your data governance processes, and communicate how the MDM initiative is helping the company to achieve its strategic objectives. And above all, be persistent. Don’t take no for an answer. The company didn’t get into its current situation overnight, and fixing it won’t happen overnight either.

Please let us know – in the comments here or in the forums on the MDM Community – whether you’ve taken on the role of MDM evangelist in your organization, and if you need any help with it, please let us know.

This is very true in master data management (MDM) – where you’ll inevitably come under pressure to oversimplify. It’s not uncommon to have 20-30 source systems (or more) that have to be integrated with the MDM hub. And tackling other initiatives in the enterprise at the same time (like service-oriented architecture or major ERP or CRM upgrades) can increase the pressure. MDM can help with those other initiatives but doing several things at once may increase the overall degree of difficulty.

Remember, if you oversimplify or underestimate, you’ll be under pressure to cut functionality later. Satisfying important requirements will be postponed to later phases, and the business will be disappointed.

So watch out for the temptation to oversimplify. I had a client once who was setting up a customer hub with about five very complex mainframe-based source systems. They were oversimplifying by making the integration from the source systems to the hub one-way only. So new customer records would flow to the hub, but any updates or data quality improvements made in the hub would not flow back to the source systems.

I asked them what the plan was for those updates, and their answer was “manual integration” (which, of course, is no integration at all – just data stewards manually entering the changes a second time back into the source systems). We all know how that turns out – a great opportunity to synchronize updates and data quality improvements from the hub back to the source systems goes untapped.

Another thing I’ve noticed is that data governance can be disruptive to the business unless the business itself is driving the data governance program and it has been well-planned. Then, any disruption seems to be overlooked, much as you’d be willing to overlook a bit of mess from a home renovation when you were living in the house, as long as you got your dream house at the end of the process. But if someone else (IT, for example) tries to impose governance on the business, that’s a different story. Then, any disruption tends to be bitterly resented, since it’s being imposed from the outside.

Please let us know – in the comments here or in the forums on the MDM Community – what you think of this tendency to underestimate the complexity of MDM projects. And I mean it this time – let’s have your comments and “war stories”!

The next article in the series is: MDM Best Practice #10 – Use a Balanced, Holistic Approach

MDM Best Practice #8 – Resist the Urge to Customize

As the various MDM hubs mature, it’s getting easier to resist the temptation to customize. When I first started working with Customer Data Integration (CDI) hubs in 2004, they were a little “rough around the edges”, and sometimes customization was unavoidable.

But we’re six years further into this now, and the major vendors’ platforms are light years ahead of where they were in 2004. At this point, working with the vendor to improve their product in future releases is a better strategy than customization.

And most products allow you to modify the underlying data model – and the various flavors of the user interface – without touching the source code. This is a big improvement, because most of the times, the changes needed by the business are relatively minor – a few new fields here and there, some new reports of course.

One important thing to include in your evaluation of vendors’ platforms is how easy it is to “settle into” the platform – to make those minor changes and to adapt the platform to the way your organization does business. If the platform seems like it would difficult to adapt in this way, consider that a warning sign.

If you do have to customize, do it carefully; make sure your changes will survive an upgrade gracefully and are well documented.

One of the biggest risks is getting “rev locked”. The MDM vendors are still revving their products once or twice a year, so you don’t want to get stuck on an older version. I had one client that was told by their vendor that their technical problems were fixed in the latest release. Unfortunately, they were told by their internal team that the earliest they’d be able to upgrade to that release would be in about 18 months!

One way to avoid this is to build what I call “upgrade competency” into your project and your team during your initial implementation – so you already have one upgrade under your belt during your implementation life cycle. That way, the upgrade process isn’t quite so daunting.

Please let us know – in the comments here or in the forums on the MDM Community – how your organization is dealing with the issue of customizing your MDM platform.

The next article in the series is: MDM Best Practice #9 – Don’t Underestimate the Complexity

There’s not much point in doing master data management if you’re not going to govern the data.

I remember attending an MDM Summit conference a few years ago, and hearing a pharmaceutical company admitting that they had spent 6 months implementing their MDM technology before they realized that they needed to have a data governance component – an organization with the accompanying processes to manage the quality and accuracy of the company’s critical master data. They essentially had to start their project over again after putting that data governance program in place.

The ironic part was that their system integrator partner ended up sponsoring the Data Governance track at the next conference.

Make sure you convince management of the need for a data governance team as part of your MDM implementation, because trying to do master data management without data governance is like trying to fly a plane with only one wing.

Please let us know – in the comments here or in the forums on the MDM Community – how your organization is handing the intertwined nature of MDM and data governance.

The next article in the series is: MDM Best Practice #8 – Resist the Urge to Customize

Today, we’re going to resume our series on Master Data Management Best Practices. Here are the earlier articles in the series:

1. Start with the Need, Pain or Problem (Not “The Solution”)
2. Active, Involved Executive Sponsorship
3. Emphasize the Organizational Change Management Aspects
4. The Business Has To Own MDM and Data Governance
5. Use Your Best Project Managers and People

MDM Best Practice #6 is to think of MDM and data governance as long term programs, not a short term projects.

Start by understanding and describing your current state – where you’re starting from. Then define your “to be” or future state, and analyze the gaps between the current and future states, and how to close them.

Work with the business owners to break the project to close those gaps up into a series of discrete, manageable phases, much as a software company will have a series of releases of functionality in their successive versions of their software over a period of years.

Spend some quality time planning – the time you invest will be repaid many times over. I recommend spending up to 15% – 25% of the total initiative in planning. Don’t forget, you’ll be breaking down silos and coordinating across multiple lines of business, functional areas, channels, geographies, and so on – and sometimes, these areas you’ll be coordinating won’t like one another very much. So you’ll want to allow for plenty of time to plan what will probably end up being a complex, multi-year effort involving a balanced initiative composed of both data governance organization and process and MDM technology implementation.

The other thing to keep in mind is that MDM is never truly “over” – you may reach a plateau or “steady state”, but there will always be master data coming into the company that will have to be cleansed, matched, merged, synchronized, published, analyzed and utilized. And there will always be more you can do – higher levels on the MDM maturity model scale that you can help your organization achieve.

So plan for an MDM “way of life” that continues on, much like Finance or Sales continue on, not a project that “goes live” and then is over.

Please let us know – in the comments here or in the forums on the MDM Community – how your organization deals with the long term nature of MDM and data governance.

The next article in the series is: MDM Best Practice #7 – Create a Data Governance Organization and Processes

Make sure you can’t be derailed by opponents pointing to avoidable project management or organizational issues. You cannot afford to have this type of project fail, so focus on controlling scope, getting the requirements right, managing risks, and communicating effectively and often.

I’ve seen situations where clients have had simultaneous projects going on: MDM, data governance, CRM and ERP. Even though the MDM and data governance projects were the most crucial, foundational efforts, upon which both the CRM and ERP projects depended, the MDM and DG projects seemed to suffer from “brain drain” – where the stronger resources were getting reallocated to the ERP project.

This “brain drain” syndrome is a mistake – the technical complexity of MDM, breaking down the organizational silos, the cultural changes and other “soft stuff”, putting data governance processes in place across the enterprise, all of these factors argue for putting your best people on these transformational programs.

It may be “project management 101″ but don’t put your “B” and “C” players on your most important programs.

Please let us know – in the comments here or in the forums on the MDM Community – what you think of prioritizing your MDM and data governance programs and putting your best people on them.

The next article in the series is: MDM Best Practice #6 – A Long Term Program, Not a Short Term Project

One model that I’ve seen work very well is for the business to lead the data governance initiative, with senior management being involved through a Data Governance Council (which makes policy for enterprise data), with Global Process Owners handling day to day activities in their own functional areas such as marketing, sales, channels, customer support, and finance, and with tactical aspects handled by business data stewards and IT stewards, under the direction of the Global Process Owners and the IT Global Solution Owner.

This three level model (Data Governance Council, Global Process Owners, Data / IT Stewardship) allows the business to set direction at the highest level and coordinate across the enterprise, while still letting the process owners manage activities within their own functional areas. It’s important to break down the silos which are so common in most of today’s corporations, because silos breed the “islands of data” problem. Reuniting and reconciling those “islands of data” is one of the major reasons companies are doing master data management initiatives in the first place.

When MDM is driven solely by IT, the business may not understand it or buy in. In some cases, the business may not even realize MDM is there, if it’s buried too deeply in the “infrastructure”.

The hard truth is that MDM’s nature as an ongoing program means that even if the initial project is funded by IT, the business may not pick it up in Year 2 & beyond – unless the business owns it.

I’ve seen many instances of MDM programs whose first iteration (driven solely by IT) failed, until they started over, recruited sponsors in the business, transferred ownership of the program to them, and took a more business-oriented approach to the initiative.

Please let us know – in the comments here, in the forums on the MDM Community or using the #MDM hashtag on Twitter – what you think of the need for business to own the MDM and data governance initiative.

The next article in the series is: MDM Best Practice #5 – Use Your Best Project Managers and People

Outside perspective can be very helpful here. As I discussed in a recent article, “Org. Change and Data Governance”, organizational change management – as an applied discipline – is used far too rarely on MDM projects. They’re big enough to justify it, and they certainly involve enough corporate politics and cultural change to benefit from a structured approach to organizational change management. My firm, Hub Designs, applies org. change and communications strategy techniques to every project we do.

Most of what I know about organizational change management I learned from my friend, Dr. Burt Reynolds, who is now an Assistant Professor at Southern NH University. We first worked together on an Oracle ERP project at a software company in Massachusetts. One of the reasons that project was successful was the project leadership included a strong org. change component.

In MDM projects, a clear communications strategy that addresses all of the various stakeholders of the initiative, and communicates your messages to them using their preferred methods of communication, over the right time frame, will have a huge impact – particularly if you can tell those stakeholders how MDM and data governance are making a difference and helping the organization realize its strategic goals. Find every occurrence of increased revenue, reduced costs, and easier compliance and risk management, and pass those success stories on to the organization at large.

Please let us know – in the comments here, in the forums on the MDM Community or using the #MDM hashtag on Twitter – what you think of the need for organizational change management in MDM and data governance initiatives.

The next article in the series is: MDM Best Practice #4 – The Business Has To Own MDM and Data Governance

To champion a change (towards managing master data as a true corporate asset) is going to mean significant cultural disruption. In most companies, that type of change is best driven “top down”.

Don’t try to start until this is in place. Work on your elevator pitch, reach out to senior management and educate them on master data management, and work on recruiting your executive sponsors.

MDM and data governance programs are typically not very successful from the “bottom up”. They may start that way, and even show a few small wins, but you’ve got to get the “C suite” interested and engaged at some point in order to get the budget money and the political “juice” you’ll need.

Don’t forget that data governance is largely a political function. I’ve always liked Jill Dyche’s definition of data governance: “Data governance is the decision-rights and policymaking for corporate data, while data management is the tactical execution of those policies.”

When you see the word “decision rights” and “policymaking” next to the words “corporate data”, you know that you’re dealing with an area that is more political than technological. But we need to embrace that, for that is the reality of data governance (or as my friends at Evaxyx in the UK like to call it, “data government”).

And if you think that anything in the enterprise can succeed that is so strongly political without the explicit and continuing support of senior management, I’ve got a bridge in Brooklyn that I’m dying to sell you.

Please let us know – in the comments here or in the forums on the MDM Community – what you think of the political nature of data governance and the need for active, involved executive sponsorship of MDM projects.

The next article in the series is: MDM Best Practice #3 – Emphasize the Organizational Change Management Aspects

I wrote an earlier article on this in October 2007, and it’s proven to be one of the most popular articles on this blog, with more than 4,500 views to date. I’ve spoken on this topic several times at the Oracle Applications Users Group COLLABORATE conference, and at Oracle OpenWorld in 2009 and 2010.

My thoughts on MDM and data governance best practices have changed a bit over the years. At the recent Oracle OpenWorld conference, I co-presented with a couple of great people from Oracle, so I only had about 30 minutes, which forced me to focus and be more concise.

For those of you who couldn’t get to San Francisco for OpenWorld, I’m going to do a series here on this blog, looking at my recent Oracle OpenWorld presentation one best practice at a time.

MDM Best Practice #1 – Start with the Need, Pain or Problem (Not “The Solution”) – the “build it and they will come” approach really doesn’t work for MDM. I had one client where the IT group built a working customer hub, but couldn’t get the business interested in adopting it, and as a result, couldn’t get the funding to continue project beyond Year 1.

To avoid their mistake, make sure MDM solves some key business problems. Find out what your company’s overall corporate strategy is, and figure out how to tie MDM to delivering on that corporate strategy.

In particular, look at the data-related components of your planned and in-flight projects, then see how a centralized data hub can save money. I had one client where the “data components” of their ten planned and in-flight projects totaled about $10 million, and they calculated that by implementing a customer hub, they could achieve those same business goals for $6 million. After their implementation, which lasted 12 months, their actual costs were only $4 million. So they delivered savings of $6 million vs. the data-related costs embedded in the ten separate projects.

This may sound like an IT-driven initiative, but saving $6 million while still achieving the same business goals was a win-win that made the business team and the IT team look good.

Please let us know – in the comments here or in the forums on the MDM Community – what you think of business-driven rather than IT-driven MDM and data governance initiatives.

The next article in the series is: MDM Best Practice #2 – Active, Involved Executive Sponsorship

Here’s an except:

“I’ve been an MDM evangelist since 2004 and have worked with a lot of people either becoming MDM process owners or helping shape another person within their company into one. Here are some tips if you’ve had that role handed to you, are aspiring to it or want to interest someone else in your company in stepping up to it.

First, embrace the political aspects of MDM. I wrote an article in the March 2008 issue of Information Management called “The Politics of Master Data Management and Data Governance,” in which I recommended that people start by understanding the political landscape at their company when creating a plan. Who are your likely allies and opponents? How will you get your initial funding and accomplish implementation? And don’t forget to plan for data governance.”

Click here if you’d like to read the full article.

Prior to those three conferences, I went to eight in a row, and spoke at six of them. But now that the “MDM tribe” is gathered in New York, I find I’m wishing I was there.

I am totally jammed at the moment with client projects and a webinar that I’m working on.  And I just got back from speaking at Oracle OpenWorld in San Francisco.

But from reading the #MDMDG stream of Tweets on Twitter, I find I’m kicking myself for not going. It’s only a couple of days, and it’s always good to see people that I don’t get to see very often. As much as I enjoy Twitter’s real-time dynamic, it’s not the same as being there.

If you’re attending the MDM Summit in New York this week, please let us know in the comments here or on the MDM Community what you think of the conference, and whether you’d go again next time.

Let me start out by saying that Hub Designs is vendor agnostic – we partner with all of the leading MDM vendors, including Oracle, Informatica / Siperian, Initiate Systems / IBM, SAP, D&B / Purisma, and Kalido, and are having partnership discussions with others like Orchestra Networks and Stibo Systems.

But my roots in the Oracle community go back to 1995, and my knowledge investment in Oracle’s CRM, ERP and MDM products is considerable. So I feel very comfortable at OpenWorld, and have about 250 Oracle people in my address book.

So although we are vendor agnostic, it’s only natural that we’ve developed a strong relationship with some partners, and are still working on developing that level of partnership with others. It’s hard to have equally deep partnerships with ten or so different companies.

My schedule prevented me from arriving until Tuesday, and when I did get there, I didn’t feel too well. But I did get to some sessions on Wednesday, and I was particularly impressed by “MDM Customer Panel: Implementation Challenges and Best Practices with the MDM Institute, Credit Suisse, Royal Caribbean Cruise Lines, Cricket Communications, and Wind River Systems”.

The session was a very practical Q&A, with different Oracle customers from different industries talking about their experiences, difficulties, and successes over the past four years or so. Several of them had implemented Oracle’s Customer Hub (formerly Siebel Universal Customer Master or UCM), with Wind River having implemented the Customer Data Hub (CDH) product.

The session also included Aaron Zornes, a prominent thought leader and Chief Research Officer of the MDM Institute. It was great to see him and to chat briefly after the session. If you’re able to, you should definitely register for the upcoming MDM and Data Governance Summit in New York City on October 3-5. I’ve been attending these for several years and always find them helpful in order to stay in touch with the pulse of what’s going on in the MDM and data governance space.

The session that I did with Bill Miller and Vanessa Hsu from Oracle was well attended, despite being in the very last time slot of the conference (Thursday at 3:00 pm). We had 101 people in the room, and even though we went a few minutes past the top of the hour, almost everyone stayed to the end. I talked about the need for change in today’s corporations, and the power of being an MDM evangelist in bringing innovation and change back to your company, as well as about the Top Ten best practices that I’ve observed over the past nine years of working in the fields of Data Governance and Master Data Management, across both the customer and product domains.

Bill Miller talked about how Oracle has applied these concepts to its own MDM needs, and its own six year journey from data quality chaos to finely tuned governance machine. It was great to hear, because I’ve known Bill for almost that entire time, and watched him go through some incredible projects, and grow into an important role as Global Solution Owner for Data Quality Management with Oracle’s IT function. He works closely with the business people (the Global Process Owners) in marketing, sales, finance, customer service, and so on. That virtual team is Oracle’s data governance board, and is responsible for some huge improvements in Oracle’s data quality picture over the last few years. Oracle implemented Oracle Customer Hub internally, and made some great process and cultural changes.

Vanessa Hsu is a Senior Product Strategy Manager at Oracle, and is responsible for a new product called Oracle Data Governance Manager. That product is an extension to Oracle Customer Hub, and provides a centralized administration tool for data stewards, giving easy access to key MDM operations, to increase data steward productivity and highlight enterprise-wide data quality metrics at a glance. It’s an important capability that Oracle will extend to its other hub products over its next release cycle.

The “feel on the street” in the MDM track at Oracle OpenWorld this year was that it was “full speed ahead” at Oracle. Gartner recognizes Oracle as one of the leaders in its “Magic Quadrant” for MDM, and deservedly so. There are a lot of smaller vendors with great technology too, but Oracle has done a lot to advance the state of the MDM art, and it was a pleasure to be in San Francisco this week to see their customers talk about their success. It will be interesting to see what happens over the next few years as Oracle introduces Fusion MDM to the market.

Image via Wikipedia

I’m really looking forward to speaking at the upcoming Oracle OpenWorld conference. I’ve been attending OpenWorld since 2004, and my talk at it last year was a big hit.  David Butler from Oracle, who manages the MDM track at OpenWorld, said I was their “cleanup hitter” last year and that I “hit a home run with the bases loaded”.

The attendance for the session at the 2009 OpenWorld set a record for its time slot (the very last session in the conference).  This year, I’ve got the same time slot again, so if you’re planning to go to OpenWorld and are interested in Master Data Management, hang out to the very end and drop by the session.  It will be on Thursday, September 23rd, at 3:00 pm Pacific time, in the Moscone West building, Room 3003.

I’ll be co-presenting with my friends Bill Miller and Vanessa Hsu from Oracle.  The topic will be “Best Practices and Advanced Topics in Master Data Management and Data Governance”, and here’s that the Schedule Builder says about our session (Session ID S317887):

Data governance is key for healthy enterprise-wide CRM, ERP, SCM, and BI enterprise processes. Master data management provides a foundation for data governance. Thus, for many companies, it’s not “if” they will implement some form of MDM–it’s “when.” You can’t govern unmanaged data. This session will help you better understand MDM and data governance. It presents some useful MDM and data governance best practices, talks about what works and what doesn’t, covers the importance of a holistic approach, and discusses how to get the political aspects right.

So I’ll present some useful best practices for MDM and data governance, Bill Miller will give an “applied case history” of what Oracle has done internally in its implementations of MDM and data governance, and Vanessa will discuss the Data Governance Manager product that Oracle has recently introduced.

It should be a great session – I’m really looking forward to being part of it!

I’ve been involved in the Oracle Applications Users Group (OAUG) since 1995, and have been a member of the OAUG Education Committee for several years now. The Education Committee is starting to plan next April’s COLLABORATE 11 Conference, and I’m managing the “Master Data Management” track.

Together with the Special Interest Group (SIG) coordinators for the Customer Data Management SIG and the Oracle Enterprise Product Lifecycle Management SIG, we invite YOU to submit a paper for the 2011 conference’s MDM track.

Our vision for the MDM track at COLLABORATE 11 is to have:

• a good mix of beginner, intermediate and advanced topics,
• presented by a range of well known and first time presenters,
• covering master data management, data governance and data quality,
• including domains such as customer, product, supplier and site,
• discussing Oracle products such as Oracle Customer Hub, Oracle Product Hub, Oracle Supplier Hub, Oracle Site Hub, Oracle MDM Data Quality, Oracle Higher Education Constituent Hub, Hyperion Data Relationship Management, and Oracle Fusion MDM.

Here are the important facts from the OAUG Call for Papers:

You’ll have the opportunity to connect with more than 5,000 users, technology leaders, Oracle executives and solution innovators gathering for the user-driven education and networking event April 10 – 14, 2011 at the Orange County Convention Center West in Orlando, Florida. Proposals are now being accepted. The deadline is Friday, October 1, 2010 at 11:59 p.m. EDT. To submit a paper, go to http://collaborate.oaug.org/submit/.  For more information, you can go to http://collaborate.oaug.org/presenterinfo/.

Note to Oracle Employees: All Oracle employees interested in speaking at COLLABORATE 11 are to submit your papers through the Call for Papers submission form. Please contact speakerprograms@oaug.com for assistance with technical difficulties. For all other inquiries, please contact Lisa Stuart at lisa.stuart@oracle.com.

Education

• Based on our popular “Best Practices in MDM and Data Governance” speaking engagements, presented at Oracle OpenWorld and the Oracle Applications Users Group COLLABORATE conference.
• Our workshops get business & IT professionals up to speed quickly
• You get access to the best MDM experts, and can bring your business people into the process early

Roadmap

• Based on Hub Designs’ MDM framework
• Defines where you are now, where you want to be, and over what time period
• Looks at master data management, data integration, data quality, and data governance over time

Readiness Assessment

• Looks at issues relating to politics & culture
• Performs skills assessment on people who may need training
• Examines process issues, outlining where business processes need improvement or redesign
• Investigates technology issues, detailing where essential components are not present or not able to support your upcoming MDM initiative
• Performs data profiling to discover data quality issues

Business Case

• Captures business requirements
• Identifies stakeholders and select metrics
• Baselines current performance
• Negotiates expected benefits
• Converts to financial results
• Develops total cost of ownership
• Calculates hard-dollar ROI

Software Selection

• Develops selection criteria
• Creates a weighted vendor scoring model
• Includes functionality, technology, viability, costs, services and vision
• Develops demo scripts for vendors to follow and sample data sets to give them
• Manages proof of concept (POC) process
• Assists in evaluating POC performance and scoring vendors

These engagements range in length from one to twelve months, with teams varying from two to ten people, depending on the size of the company, the number of domains of master data  involved, and the complexity of the politics and legacy systems in the enterprise.

If you’re interested in discussing an MDM strategy engagement like this, please contact Hub Designs at http://www.hubdesigns.com/contact_us.html. Or if you have comments on the above approaches, please let us know by commenting here.

Expected Activities to be Performed

Technical Program Manager (PM) with strong communication & project mgmt skills. Ideally has a development background, but has already transitioned to PM role. Has experience on large transactional systems, is familiar with complex integrations using Web Services and Pub/Sub integration patterns, and is familiar with scale-up/out strategies and complexities. Someone who can outline strategy, plan and functional design, have enough project mgmt skills to drive those plans to closure, and have the experience to know what their risks are and how to navigate obstacle and politics.

Tasks:

• Author Scenarios and Uses Cases
• Author detailed Functional Specifications
• Manage one or more feature teams (cross-functional team of Dev and QA as related to implementing feature areas) with necessary communications and managing weekly feature team meetings
• Work with Dev, Test, Architects, program leadership and other PM’s to successfully design, vet, and receive approval for specified features
• Generating weekly status

Feature Areas for possible focus:

• Reporting design (defining necessary design to accomplish business/audit and operational reports from a very large ODS database, which may require defining necessary data marts and/or cubes
• Business rules for computing data quality scores on key data fields
• Disaster recovery design (extending existing DR that is already in place)
• Data retention design

Desirable Skills

Duration

Expected Start Date = August 2010, Expected End Date = TBD (likely a year out)

Principals only please (no agencies). Again, please contact Dan Power via http://www.hubdesigns.com/contact_us.html, and we’ll put you in touch with the hiring manager.