In the May 30th, 2011 edition of Hub Designs Magazine, you may recall the article The System of Record in MDM by Dalton Cervo (who is also the co-author of our new book Master Data Management in Practice: Achieving True Customer MDM).

In the article, Dalton aptly pointed out the underlying importance and challenges associated with defining a system of record (SOR) approach needed to enable a single version of the truth in a master data hub environment.

Expanding from that SOR aspect, MDM as a whole is an ongoing set of processes and disciplines aimed at achieving and maintaining a single version of the truth within one or more master data domains. Companies will typically begin their MDM focus in one master data domain area and expand to more domains with implementation of a multi-domain program model.

In some cases there may be a multi-domain plan from the start, but usually a single domain like Customer or Product will still be the starting point and set the program tone for subsequent domains. When taking this multi-domain leap, it is critical to determine what aspects of MDM planning and execution can be repeatable and scalable across the domains, as well as what are the domain specific elements. With that in mind, here are some perspectives and questions that are important to consider when pursing a multi-domain model.

Defining domains in a multi-domain model

There are a number of commonly identified MDM domains that are often referenced in MDM literature and business case examples such as Customer, Product, Locations, Materials, Employee, Supplier, and a few others that represent master data areas common to most business practices.

Depending on the business model, industry orientation, and application platforms involved, the actual master domains or domain names that a company defines may deviate somewhat from those common domain types. In fact, it would not be unusual in a multi-domain implementation to see a mix of domain types where the leading domains are some of the common MDM domains, followed by other data domains that may not necessarily fit a true MDM definition — such as a more transactionally oriented data set — but where MDM type disciplines can still be applied to achieve a desired level of improvement, consistency, and value with that data.

In such cases, this may appear to be an unconventional approach, but in practice it is reasonable to expect that regardless of the original intent and context, good data management practices and disciplines such as MDM will usually find their way into more general usage over time. A multi-domain model can often become a vehicle where good MDM practices become more generally applied across a company’s data sets. This is actually goodness, so keep in mind that the multi-domain makeup does not always have to be limited to just the master data context.

Prioritizing in a multi-domain model

As is often the case, starting an MDM initiative with a focus on the Customer or Product domain certainly makes sense since the viability and sustainability of most companies rests on customer and product dynamics. Most all sales, marketing, financial, service, and analytical functions in a company are tied to these customer and product dynamics, so this can be a natural starting point for MDM before venturing further.

Once the most critical domains area addressed, it will usually be easier for other data domain programs to get started and aligned within the overall MDM plan. However, there can be many strategic, operational, and technical reasons that can influence domain implementation order.

The MDM business case and investment decisions should be driving the overall MDM roadmap based on priorities that are typically associated with risk mitigation, revenue growth, cost reduction, or business efficiency. The MDM priorities are also going to be influenced by things like executive sponsorship, available resources, business process impacts, new technology, BI needs, and budget forecasts.

When planning a multi-domain program, sufficient time is needed to work out the right implementation approach, examine business impacts, determine critical path dependencies, and to define the ongoing program management model. Not fully addressing these items will likely lead to various program impacts and priority adjustments.

It is the business functions and transactional areas who are the primary creators and consumers of the master data, and since most transactional areas will interact with master data from multiple domains, the domain implementation plan and order can have significant impact on business operations. So be sure to plan and prioritize wisely.

Distinguishing the Program Management Office role from the data domain role

Implementing MDM across multiple domains naturally creates the need to examine how to best coordinate and prioritize multi-domain activity and focus, particularly in regards to technology needs, quality improvement priorities, and demand for budget and IT resources.

A multi-domain MDM plan needs to start by creating a distinct enterprise level Program Management Office (PMO) charter and core team to establish the program foundation needed to move forward.  In some cases, this charter may be assigned to an enterprise data governance group. However established, this is the program office that will need to provide the cross-domain program leadership, policies, standards, services, and core resources to help facilitate and support the multi-domain model. Each domain should still have its own domain specific program scope, responsibilities, and resources, but this should be in alignment with the multi-domain model and policies that the PMO puts forth.

Depending on an organization’s model and approach, the role and responsibility mix between the PMO and domain charters can vary, but generally there should be a clear separation of duties conducive to a collaborative and supportive relationship. Because many aspects of quality management, governance, and stewardship focus are unique within each domain, this should not be impeded by excessive PMO control.

If the PMO charter is too broad, overly controlling, and attempts to create too much of a homogeneous multi-domain model, it can start overshooting its value if it takes away authority and empowerment from the domain specific teams.

A multi-domain MDM program should not be a cookie-cutter process or a follow the bouncing ball type of affair. Rather, it is very much the orchestration of unique programs that have common threads and are on a common enterprise MDM mission but with different domain specific objectives and priorities. A well-conceived PMO should always be cognizant of how to continually coordinate and enable the various domain programs and avoid over-managing where control and conformance is not necessary, otherwise this can become a path toward a stifling model that is not conducive to overall MDM growth and maturity.

A PMO needs to cultivate an environment where a maturing MDM domain team can lead by example with developing best practices which other domain teams can leverage to accelerate their maturity. The leading domain implementation needs extra attention so that the business foundation it creates for data governance, stewardship, quality management, and technology usage, can create repeatable models to help prime the start up of the other domain implementations. This is critical for driving sustainability across the overall MDM model. Leveraging the knowledge, practices, and experience from a leading MDM practice should be a key strategy in a multi-domain plan.

There are also many IT-oriented services needed in MDM such as metadata management, data analysis, data integration, data cleanup, or development of metrics and reports where competing demand is likely to occur across multiple MDM programs. The PMO needs to ensure that these services are as extensible and scalable as possible in order to manage the demand as economically and efficiently as possible.

Launching too many MDM initiatives side by side and each with common dependencies and demand on IT can quickly lead to overload and bottleneck scenarios, causing deliverables to be delayed which can negatively impact the progress and expected deliverables across all the MDM initiatives.

Also, when planning your multi-domain program be careful not to create too many critical path dependencies on new technology because, as we all painfully know, these implementations will often be subject to delays and functionality issues. There are many business project areas of MDM programs (e.g. data governance, data steward setup, business analysis, process improvement, and many program management tasks) that don’t depend on technology, so be sure these type project areas and tasks are sufficiently identified in the program plan and can still move forward while other technology issues are being addressed.

Additional things to consider

Beyond what I have already covered about planning and implementing a multi-domain model, here are some other important questions and perspectives that should be considered:

• Can your IT models and practices sufficiently adjust to provide more flexibility and collaborative support across business-driven MDM programs?
• How much capacity will business and IT organizations have to support requirements and demands from a multi-domain plan?
• Will new technology actually help enable more MDM efficiency and accelerate ROI?
• Will any anticipated organizational change be a disruptive factor, enough to preclude a multi-domain MDM initiative from succeeding?

Simply stated, when planning and implementing a multi-domain model, expect a lot of variables and do the math. Complete necessary business analysis to fully identify what MDM and data governance oriented needs, benefits, and impacts can be expected; what will apply across the domains; and what will be associated to a specific domain. Gear your PMO office to help successfully facilitate the common and unique elements while also driving the domain programs to stay in scope of the overall enterprise MDM model and objectives.

A multi-domain plan can easily be a 3-5 year journey, but if persistently and successfully pursued, this should result in highly consistent and unified data management practices across the enterprise that can greatly benefit a company’s operational and analytical foundation.

I truly believe that MDM has the ability to drive more operational efficiency through continued application and maturity of its core disciplines in a multi-domain model. And while MDM oriented technology continues to be introduced that can greatly assist multi-domain implementations, fundamentally it is the due diligence done in the MDM planning stages and the ability to implement a flexible MDM program foundation that enables the efficient and cost effective application of the technology.

Mark Allen 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 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.

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.

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.

The latest issue of Information Management magazine is out, and my column in this edition is titled “Data Governance: A Chicken and Egg Problem”.

Here’s a brief introduction to the article:

Data governance suffers from a bit from the “chicken or the egg” syndrome. People at your company aren’t going to understand what data governance is and what it can do for them until they actually see the results. However, getting the initiative funded and launched will only happen if you can convince your company of the tangible benefits of data governance. That can be difficult when there’s no actual program in place.

You can read the rest of the article at: http://digital.info-mgmt.com/info-mgmt/20101112#pg33.

Please let us know what you think of the article by using the “Leave a Comment” link here.

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!

Is my organization ready for Master Data Management (MDM)?

Assuming you’re confident that you can answer the question “What is MDM?” and can successfully debate “what MDM is not” with an unseasoned Data Architect, the title question is next in your readiness assessment progression.

While the question itself seems simplistic, the answer requires examination of many aspects of business operations as well as data management and IT maturity.

MDM projects focused on creating “IT solutions” to “IT problems” fail to provide true end-to-end life-cycle management, which is the key to maximizing business value. Below are questions to consider when evaluating your business readiness for MDM success. Consider the Core Subject Item to be the business object that you are considering mastering, such as Product, Customer, Raw Materials, Party, etc.

• MDM success relies on understanding the current and desired state of business operations. Identifying and involving business champions and business sponsors is the only credible method of defining information and process gaps which lead to a true business case.  Are your business sponsors fully engaged?
• Is there a Data Governance strategy in place already that can be used to manage business information or do we need to define this from scratch?
• Is the business case defined and does it directly tie to the project success criteria?
• What is the Core Subject Item of your MDM? Have you validated that business owners, Finance, Customers, Marketing, Legal, and IT all have the same perspectives, including the same granularity and the same definitions? If not, how will you resolve the differences?
• What are the target volumetrics for the Core Subject Item based on current and anticipated business needs?
• Is there a single Taxonomy for your Core Subject Item where all objects map to one and only one leaf node?
• Have you created an as-is information model?
• Have you created a to-be information model that business and IT sponsors agree on?
• Would you be able to define a conceptual data model to describe the various high-level information types targeted for the MDM system?
• In the case of product MDM, can business users define the difference between a version and a revision, if there is one? How do they manage each?
• Is there unstructured data you need to include?
• How are object related to each other? Are some products cross-sellable, up-sellable, substitutions, or versions of others? Do some contacts household with others?
• What rules and restrictions do you have to enforce in the MDM system?
• What additional information must be collected to allow other downstream information consumers to apply their business rules and restrictions?
• What is the current lifecycle process used by the business to manage its Core Subject Items? What is the proposed new process to do lifecycle management?
• What are the technical constraints your organization will be facing?

These are just a few of the points to consider when evaluating how well your business is prepared to undertake a successful MDM project. While you do not necessarily need to answer all of them before you start your project, consider making them a milestone before full budget is allocated because it makes planning much more accurate.

Lastly, keep in mind that knowledge and experience go a long way. Those who have gone through these projects before can attest to importance of laying down a solid foundation to build upon.

This free virtual seminar is focused on best practices for maximizing SAP performance. The day long virtual event features expert presentations, live panels and expert networking opportunities to help you make the most of your SAP environment, and will cover the hottest topics in SAP right now – including business intelligence, virtualization, master data management and mobile technologies. You’ll learn tips that you can put into practice immediately and you’ll get unbiased advice for long-term strategy development. At this unique online event, go beyond the hype and get insight into the latest technologies and best practices you can use to improve operational efficiency in SAP environments.

Dan Power’s session will be at 1:30 pm EDT, and will cover topics such as:

• Definitions of master data management, data governance and data quality
• The five essential elements of MDM
• Why companies are doing MDM and what this means to you
• Getting started on an MDM roadmap
• Is your organization ready?
• Creating the MDM business case
• MDM software selection
• Some important best practices

For more information, please visit http://searchsap.techtarget.com/feature/Getting-the-most-out-of-your-SAP-environment,  and to register, please click here.

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.

You’d be amazed how often that simple statement confounds people though. They want to enter master data in their ERP or CRM system, and then synchronize it over to the MDM hub. Or they’d like to somehow do without an organization to manage their master data for the enterprise. Or they’re willing to concede the need for a data governance group, but don’t think that group will need any formal processes or technology to help orchestrate their work or facilitate it and improve their productivity.

Even though the link between data quality tools and master data management is well established, I sometimes still see people try to do MDM projects without using data quality technology. And even though synchronizing the high quality master data available in the hub should be a high priority, people (typically for cost reasons) still try to skimp on integration technology and try to get by with only the most basic ETL tools.

One of the most popular articles we’ve had here on the Hub Designs Blog was the Five Essential Elements of MDM, in which I laid out what I thought were the most important related areas of technology. In it, I included the MDM hub itself, of course, and also data quality, data integration, middleware, third party content and data governance (which of course, is not really technology, but needs to be included because it too is so often forgotten).

So getting back to the focus of this article, my philosophy of MDM is to have all of the essential elements, to have a sound vision and strategy for MDM, a strong business case based on metrics, to create a governance framework and organization to carry it out, to design governance processes, and then (last but not least) to implement technology to facilitate the governance needed to support the enterprise’s master data requirements.

So often today, we see organizations taking a technology-driven approach, or leaving out important parts of the above approach.  Have you thought your MDM initiative all the way through?

Since I’m a consultant, I have the chance to meet with a wide variety of people at different companies in various industries. About a month ago, I talked with someone I worked with a number of years ago who wanted to know more about Master Data Management. Since he’s worked more as a “functional” person for most of his career (as opposed to a “technical” one), he asked me exactly what an MDM solution would provide his company.

MDM, I told him, is not simply a software application that you ‘buy’ from a software vendor like you might with a CRM or ERP solution. You can’t just decide one day that you want to buy a “customer hub” or a “product information manager” because you heard from your IT Director (or even CIO) that it will save your company millions and cure world hunger. It’s vital to understand why your company might need an MDM solution.

You need to look at your company and do some good old-fashioned detective work. Before you take that journey, take the time to understand how your company works and more importantly, why it isn’t as efficient as it could be. Perhaps management wants to know more about your customers, but can’t do it because customer data is stored in three different applications, and even then it takes two or three months to get an out-of-date report. Maybe your company is paying too much in commissions with multiple reps getting paid for the same deal. Has your company grown so fast that you have multiple purchasing and inventory management systems and hundreds of Excel spreadsheets that have all the answers – if only you could piece them together?

Perhaps you have a more urgent need to understand your customers. If you’re a pharmaceutical company, you need to follow strict spend management guidelines related to marketing to your customers. If you’re a financial services provider, you need to comply with capital management standards like Basel II and to understand your clients as mandated by federal Anti-Money Laundering legislation. Perhaps you’re a publicly held company and need to ensure that you comply with Sarbanes-Oxley. In any case, failure to comply with such legislation can lead to fines, damaged reputations or even imprisonment of top executives.

These all are commonly found reasons for pursuing an MDM solution. Take a moment – what reasons do you have for exploring MDM? If your company is like most that I talk to, you’ve got the problems that master data management can help solve.

Editor’s Note: This is Part 2 of a two-part series written by Jim Walker from Initiate Systems. You can find Part 1 here.

Here are the rest of the six proven business strategies fueled by real-time, accurate and complete customer data in a master data management (MDM) system:

Use customer service to retain customers and cut costs: Acquiring customers is expensive, and losing them is even more costly. Better customer service will improve customer satisfaction and retention and reduce your costs. Empowering your touch points with a complete and accurate view of each of your customers and their relationships provides a clear picture to both your customer and your representatives. Automated collection and presentation of complete customer information to service professionals reduces search times and has a positive effect on call waiting times, increasing productivity and reducing costs. It allows you to never ask a customer to repeat themselves. Accurate composite customer data enables web self-service applications with a single view of multiple accounts to empower your visitors to help themselves. 

Be bold, change the playing field; buy a competitor: A downturn will have an indelible effect on many industries as valuations decrease and otherwise impossible consolidations becomes plausible. Historically, the most successful mergers are made in downturns. According to Harvard Business Review, “downturn mergers generate about 15% more value, as measured by total shareholder return, than boom-time mergers.” However, capital is sparse and careful due diligence of a potential target is imperative, as their problems will become yours if the merger is completed. Merger analysis should include careful consideration of customers and any potential risks. This knowledge will help you make sense of a bold move during a tenuous time. 

Regulations never go away: An economic downturn does not delay compliance with government regulations. In fact as a slide continues, governments look to increase regulation to prevent future issues. Compliance in a recession is imperative so that you avoid costly fines that may have a devastating effect on your financial picture.

Obtaining and delivering accurate, comprehensive customer data is at the foundation of all six of these strategies. Your level of success will depend on the quality of the data that feeds each of these business improvements. An accurate data foundation allows you to deliver on fixing short-term pains, while setting up long-term gains. A new breed of data management technology has evolved to meet these challenges.

Master data management enables delivery of these valuable strategies and objectives. It provides complete, accurate customer views and valuable hierarchy management to your customer data. Reliability and effectiveness of this data is determined by its accuracy and ability to reflect real world conditions in any situation where that data is used.

Jim Walker is a Senior Manager, Field Marketing for Initiate Systems, a leading provider of master data management (MDM) solutions. Jim specializes in researching and writing on the effects of MDM on the enterprise. He has held numerous marketing positions at enterprise software companies, focusing on data management and security. He has also designed and implemented large scale enterprise systems as a technology consultant. Jim holds a MBA in e-commerce from Carnegie Mellon University and a BS in Computer Engineering form the University of Illinois at Chicago. He can be reached at jwalker@initiate.com.

Click here for Part 1 of this series.

Editor’s Note: This is Part 1 of a two-part series written by Jim Walker from Initiate Systems. You can find Part 2 here.

As uncertainty accelerates, some companies not only survive, they prepare themselves to thrive during the subsequent recovery. Even in the best economic conditions, organizations look to do more with less, and in a downturn, they are forced to manage things even more tightly. Added market pressures force tough decisions. Less money results in contraction and consolidation of vital resources. Many companies turn to their most valuable asset, their customer data, to forecast and define their future.

A downturn opens rare opportunities to outmaneuver rivals by reducing costs and increasing efficiencies. Reliable and accurate customer data can provide valuable insight into changing market dynamics. Organizations that analyze their data to identify and avoid fraudulent and high-risk accounts can also reduce operating costs. Many use customer data to build and strengthen relationships and identify revenue opportunities. High quality, reliable customer data allows them to spot opportunities across lines of business or properly align a sales force with an up-to-date and accurate customer hierarchy. They can find pricing discount opportunities for customers or identify commissions over-payments.

The potential gain is substantial; however, the effectiveness of these initiatives is only as good as the underlying data that drives the results. Here are six proven business strategies that are fueled by real-time, accurate and complete customer data that master data management (MDM) can provide your organization.

Incent customers through improved pricing: Purchasing behavior changes dramatically in a recession. Consumers increasingly opt for lower-priced alternatives to their usual purchases. Customer upgrades and extensions not only improve your top line, they also increase customer retention and can be completed with much less cost. Knowing your customer will present pricing discounts or up-sale opportunities. However, complex business relationships, such a subsidiary and parent structure, keep you from obtaining a clear picture. Overlaying a trusted hierarchical structure on your customer data will provide an accurate view of rolled-up sales and introduce appropriate pricing discounts to garner new business in difficult times.

Never double pay a commission: Geographies or strategic sales territories sometimes overlap for sales executives. Managing this overlap for hundreds of sales resources across complex business relationships is difficult at best, and the potential overpayment of commissions is high. Identifying and removing the overlap requires you to have a clear picture of the customer and their organizational hierarchy. For instance, if two sales resources are selling into two subsidiaries of the same company, you may have missed an opportunity to roll up the sales and pay a single commission. Identifying and eliminating redundant commissions reduces operating costs.

Spend the right time on the right customers: Organizations are concerned for their own well-being as well as their customers’ and prospects’. Identifying and mitigating customer risk requires complete insight into accurate customer information, license positions and relationships. Overlaying a trusted hierarchical structure on customer data will allow you to roll up risk calculations so that you can analyze and identify a master account and apply appropriate risk strategies. This will help you understand your best customers and make strategic plans to maximize revenues associated to them. It will help you spend the right amount of time with the right customers.

Jim Walker is a Senior Manager, Field Marketing for Initiate Systems, a leading provider of master data management (MDM) solutions. Jim specializes in researching and writing on the effects of MDM on the enterprise. He has held numerous marketing positions at enterprise software companies, focusing on data management and security. He has also designed and implemented large scale enterprise systems as a technology consultant. Jim holds a MBA in e-commerce from Carnegie Mellon University and a BS in Computer Engineering form the University of Illinois at Chicago. He can be reached at jwalker@initiate.com.

Click here for Part 2 of this series.

In November, I attended Gartner’s second MDM Summit conference in Chicago.

One of the topics people were talking about at that conference was how well the Master Data Management market would fare in an economic downturn.  

Certainly, companies that were just “testing the waters” on MDM may cancel or slow down their initiatives, and anyone making the front pages or the nightly news (and not in a good way) is probably going to see some disruption to their Master Data Management efforts. 

But I’ve been pleasantly surprised by how much interest and activity we’ve seen, particularly since 2009 started. 

Friends in the MDM space report getting a slew of new opportunities recently, especially in the healthcare and pharmaceutical industries. Industries like that are doing relatively well, and even in affected industries like retail, some companies are “swimming against the tide” and investing into the downturn, looking to take market share and revenue from their competition who are cutting investments and going into hibernation mode. 

Barney Beal on SearchDataManagement.com described the picture at BJ’s Wholesale Club:

[John Polizzi, senior vice president and CIO] “Our plan was not an investment in a master data management (MDM) system, or an ERP implementation, or a point of sale (POS), but rather all of them — and more.  BJ’s is embarking on a five-year transformation of its IT infrastructure and systems.”

Philip Lay, managing director of TCG Advisors, who spoke at the Gartner conference, said “now is the time to buck conventional wisdom and ‘think like a contrarian’ when it comes to MDM.”  Lay advised the attendees “the key to making a successful business case for MDM is to tie MDM to specific, broken business processes” and quantify that impact. 

I wrote an article for DM Review on “Easing into Master Data Management” which describes how to get started by building a data governance program first, with existing resources and applications, and tackling data quality and data integration as predecessor steps to MDM.

Certainly, one of the classic drivers for MDM has always been reducing costs – and that’s even more important in a recession (look for a guest post on this topic in a few days from Ravi Shankar at Siperian). 

But even more important is to grow the “top line” – to increase revenue and pull customers away from your competitors, through better information, better customer service, better products, better pricing, you name it.

In 2009, I predict the MDM market will be affected somewhat by the recession, but it will still be one of the fastest-growing software segments, as Gartner has been predicting too.

But let’s tap into YOUR collective intelligence – what do you think? Please comment here or on the MDM Community.

I thought I’d recap our “Top 10 blog posts for 2008″ for anyone who might have missed some of them. 

1. Ten Best Practices for Master Data Management – by far our most popular post (with thanks to MDMSource.com for featuring it)
    
2. Our MDM Partnership Strategy — discusses our vendor-neutral strategy for partnering with the MDM hub vendors
    
3. Different Styles of MDM Hub — outlines differences between Registry, Transaction and Hybrid style hubs
    
4. MDM Business Case Creation & ROI Analysis — links to a “one-pager” on our Business Case Creation & ROI Analysis service
    
5. How Master Data Management is Similar to ERP – talks about the similarities in organizational disciplines and processes between ERP and MDM
    
6. Metadata and Master Data Management — discusses what metadata is and different approaches to managing it in the context of MDM
    
7. Critical Data Quality Questions – outlines four “hard questions” relating to data quality and MDM and suggests ways to answer them
    
8. Building a Data Governance Organization – five points to keep in mind as you build your data governance organization
    
9. Five Essential Elements of MDM — technology (hub, integration, data quality, external content) and organization/process (data governance) required to succeed with MDM
    
10. Importance of Integration to MDM — piece urging MDM project champions to think about the role and importance of data integration

These have all been read 100-800 times in 2008.  If you’re interested in my articles in DM Review and speaking engagements, they’re outlined on the Publications page of our web site. If you use Twitter, you can follow me here.

Thank you all for reading this blog!

I saw an interesting post by Thomas Wailgum the other day called “MDM: Buzz-Worthy Since 2000, But Still a Back-Breaker”.

While I don’t agree that “there’s ongoing uncertainty as to when to take [MDM] seriously”, he does make some good points.  The software vendors who’ve flocked to MDM and put the MDM label on everything under the sun have certainly confused the market.  

Even so, the MDM software market grew 24% from 2007 to 2008.  In spite of the tough economic times we’re currently in, that rapid growth rate should continue for the next several years. 

One area I don’t agree with is the statement “it’s just plain hard to do … and even harder to do well”.

Don’t get me wrong, I’m not saying Master Data Management is easy.  But I think it’s eminently “doable” if you:

• get yourself and your team educated on what MDM is all about and what it can do for your company
• develop a compelling MDM strategy that aligns well with your organization’s long term strategy
• get folks from the business and management on board through education, communication and evangelization
• create a strong business case and use it to manage expectations throughout the lifecycle of the project
• thoughtfully select the essential components (hub, integration, data quality, external content) and plan for data governance
• after starting your data governance program and selecting the technology components, follow some best practices for MDM implementation

Of course, there are going to be some failures along the way.  But I come from the Enterprise Resource Planning (ERP) world, where a typical project was 1-2 years in length and cost in the tens of millions of dollars.  To me, MDM doesn’t seem like a back-breaker.  It seems like a great way of breaking down the walls of the typical corporate silos, complying more easily with ever-growing government regulations, increasing revenue by becoming more customer-centric (which in a recession, can make a big difference), and saving money through more efficient processes and consolidating out-dated systems.  

What do you think? Please let us know via a comment here.

First, I want to encourage everyone who reads this blog to join the free MDM Community at http://mdmcommunity.ning.com.

I’m in Chicago attending Gartner’s second Master Data Management Summit. 

I didn’t make it to last year’s event in Hollywood, Florida, but I’m attending this one to investigate exhibiting at next year’s event, and to keep my finger on how the MDM market is doing in the current economic climate. 

The first keynote session, by John Radcliffe and Andrew White, was on “Where is MDM Going Over the Next Five Years”.  Their lead-in was that MDM is more relevant than ever in today’s econonic meltdown. 

Projects will need to offer incremental value, without being too tactical. Developing a data stewardship culture doesn’t hit the capital expense budget. They recommended people focus on the “hard benefits”, efficiencies and compliance requirements, while preparing for the (eventual) upturn. And they strongly suggested developing the metrics to quantify and communicate the value of your MDM program. 

They presented the “MDM Hype Report Card”, saying that the hype cycle is at or near its peak. The links between MDM, business process management, service-oriented architecture and business intelligence remain unclear to many users.  And external service providers (in their opinion) are finally starting to add some value to MDM programs.  And they predicted that by 2012, 70% of SOA projects will fail to yield expected results unless they include Master Data Management. 

Andrew and John covered Gartner’s “Seven Building Blocks”: vision, strategy, metrics, governance, organization, process and technology, and recommended a business-driven, holistic approach to MDM, which I’ve been recommending for a couple of years now. 

I also really enjoyed “Building the Business Case for MDM” by Michael Smith.  It was an engaging but thorough review of Gartner’s recommended steps for creating a thorough business case for your MDM initiative. 

After covering the process for developing an effective business case, Michael Smith discussed how metrics can be used to quantify the benefits, and how to use the business case to manage the initiative through the entire lifecycle. 

The main argument for taking the time to create a detailed business case is the fact that without one, IT projects in general seem to have only a 50% success rate, but when the time to create a robust business case is invested, the success rate goes up to as high as 75%.  If your total project budget is high enough, that higher success rate can translate into some serious savings. 

I attended the IBM session highlighting Nationwide’s “Transformation to a Customer-Centric Organization”, and I really enjoyed the remarks by Tara Paider, their Lead Architect for Customer Information Management. 

The attendees and exhibitors I spoke to in the Solution Showcase all commented on the power of Gartner’s brand and that the 1st day of the conference was well-attended and full of good content. 

I’m a big fan of Aaron Zornes at The MDM Institute and the MDM Summit conference he puts on twice a year in the U.S. with SourceMedia. I’ve attended all six events they’ve done together in the last three years, and have spoken at five of them. 

But I see the appeal of the Gartner MDM event as well. At this stage in the development of Master Data Management, competition is a good thing – between software vendors, services firms, and conferences. It makes us all better to have another entry in the market to measure ourselves against and to strive to outdo. 

If you’re attending as well, I’d love to hear your comments here.

We’ve been writing this blog for a year now, with a total of 83 posts so far.

It’s been a very positive experience.  We’ve had clients tell us “the reason we hired your firm was because of your blog”. And we’ve gotten lots of great feedback from our partners (Oracle, IBM, SAP, Initiate Systems and Siperian).

What we’ve tried to do is to write for people who are new to Master Data Management (MDM) and looking for basic information (like “Useful Definitions for MDM”,“Five Essential Elements of MDM” and “Ten Best Practices for Master Data Management”).

But we’ve also tried to cover more advanced topics too (such as “Master Data Management and the Art of Politics”, “The Key Requirement in Choosing a Product MDM Hub”, and “Data Governance Critical to MDM Success”).

We thought that by presenting a mix of basic and advanced topics, and highlighting key milestones in the development of the firm, we could keep your interest, and hopefully keep you coming back.

The numbers tell a good story.  We’ve had a total of 8,100 hits in the past year, with an average of 32 hits per day (over the last 30 days), 200 hits per week and 835 per month (over the last 6 months).

Our “Top 10″ posts have been:

1. Ten Best Practices for Master Data Management
2. Our MDM Partnership Strategy
3. How Master Data Management is Similar to ERP
4. Different Styles of MDM Hub
5. Metadata and Master Data Management
6. Five Essential Elements of MDM
7. Critical Data Quality Questions
8. The Key Requirement in Choosing a Product MDM Hub
9. Master Data Management and the Art of Politics
10. MDM Business Case Creation & ROI Analysis

We get most of our traffic from our web site at www.hubdesigns.com (there’s a prominent “Blog” link there), and from the “Master Data Management” and “Customer Data Integration” tags at WordPress.com.  We also get a fair amount from Google Reader, My Yahoo, and my LinkedIn profile.

Our Top 10 search terms that people are using to get to the blog are: “Hub Solution Designs”, “Dan Power”, “Gaurav Arora”, “data quality questions”, “MDM vendors”, “Master Data Management best practices”, “critical to quality”, “Oracle MDM”, “ERP and MDM” and “Master Data best practices”.

We’ve tried to keep the blog vendor-neutral, and have resisted the temptation (so far at least) to accept any form of advertising.

In the coming year, we’re looking forward to more in-depth coverage of the leading MDM and data quality platforms, more insights gleaned from working with our clients, more pointers to other places where our writing appears (like my monthly column in the online edition of DM Review), and continuing to try to break new ground and be thought leaders on MDM.

If there’s anything in particular you’d like to see us cover here, please let us know via a comment. It’s been an honor to write for you over the past year, and we’ll work hard to make this a useful resource for you in the coming year.

Here’s a quick excerpt from my latest “MDM Insights” column in DM Review.

It’s a long journey from the first efforts of “customer cleanup” to a full-fledged data governance program. But that’s where many companies start. They gradually accept that there are issues with their customer data such as:

• A lack of consistently applied standards and controls,
• Problems arising from conversion of customer data from acquired companies,
• Lack of ownership of customer data,
• Invalid addresses leading to undelivered and returned mail or
• Customer service problems caused by large numbers of duplicate and inaccurate records.

So they form a committee, hire a consulting firm, and involve their internal IT folks. That’s a great start, but it’s important to realize that this is not a once-and-done project.

Click on “From Customer Cleanup to Data Governance” to continue reading.

And please let us know your thoughts by commenting here …

I’m often asked how many data stewards a company needs.

A rule of thumb I’ve used for quite a while is “one data steward per $1 billion in annual revenue”, but of course that can’t be a hard and fast rule.

Depending on the company, the degree of automation, what data quality tools are available, and the major processes around the enterprise, that number is going to vary.

Here are some thoughts to keep in mind as you build your data governance organization:

1. Build the business case and secure your funding.  Don’t forget this is a multi-year effort.  Several times, I’ve seen data governance teams and MDM initiatives that never thought beyond their first year’s funding, and who were surprised when funding for Year 2 and beyond wasn’t forthcoming.
2. You’ll probably need a multi-layer, cross-functional approach.  Start with a high level group that sets data policy, usually called a Data Governance Steering Committee or Data Governance Council (DGC).  Your executive sponsor(s) should be involved with the DGC. Then you’ll probably have a small group of data stewards which handle day-to-day data management, which reports to the Data Governance Council.
3. Focus on your data governance processes, including relevant metrics that show the impact to the business, and on communicating those metrics and their impact to the rest of the enterprise. Create a communications and education strategy to get the word out.
4. Look for IT people who “speak business” and business people who “speak IT”.  These liaison-type people are going to be crucial to your data governance organization.  Although I believe that data governance should be driven by the business, there’s no question that you’re going to need a lot of support from IT. So look for the “bi-lingual” folks in your company – they’re out there and they can be incredibly valuable in understanding the business impact of data issues, and in providing the technology support that the data stewards will need.
5. Don’t forget about metadata.  In your travels as a data governance organization, you’re going to run into a lot of metadata (information about information).  Develop a disciplined approach to cataloging and maintaining the metadata you come across.  In many ways, that will probably be one of the most useful outputs of your data governance initiative.

We’ll have more to say on data governance in this blog in the future, but let me leave you with one idea.  Instead of describing your MDM initiative as (hopefully) including data governance, think of it as a data governance initiative that has an MDM component.

You’ll be doing data governance in your enterprise long after your current MDM hub implementation is over.

If you don’t agree, or you have a perspective on data governance you’d like to share, please comment here on this blog.

In the previous installments of this series, we covered three key drivers for building your business case: Risk Management, Cost Reduction, and Revenue Growth.

Now, we’ll review the importance of and the process for gaining organizational alignment with your strategy.

When you’re building support for your business case, it’s critical to gain alignment at all levels of the organization throughout the whole process. Making the case for an information management strategy cannot rest with only one executive. And it can’t be the brainchild of IT only, or lack executive sponsorship altogether.

You need as many areas aligned as possible. More than likely, a comprehensive information management strategy needs to consider all of the data streams across the enterprise (at some point), and will therefore be fairly time and resource intensive.

If you take a three-pronged approach to gaining alignment, then you’re well on your way to obtaining approval to implement your strategy:

(1) Get front-line employees and customers to identify the problems with the data. You should have been gathering their feedback and facts as you built your case. So when you can readily articulate that customers are frustrated with your company, or that your employees are performing workarounds, rework, or aren’t as effective as they could be, then you’ve got your “first-level buy in”.

(2) You need their individual management teams to agree that these issues exist. They need to agree that they’d be more effective in achieving their goals if they had a solution to their information problems. And most importantly, if you can get them to agree that an information management strategy should be a priority and they support the contents of the business case (which shouldn’t be too difficult if you had their support during the development of the business case), then these folks become your best allies.

(3) Have those management teams bring this message forward to their leadership. When the leaders hear, directly from their own people, that they should understand and support the business case, then your business case has achieved a level of credibility you wouldn’t have gained on your own. And your role then becomes one of subject matter expert, business case developer, and valued business partner.

I do recommend getting several executives aligned to the strategy. Because of the size of the undertaking, you’ll need several leaders to prioritize and support the effort. Providing headcount, funding and the time to deliver on the plan will be crucial from these leaders.

Once again, the more compelling your business case (whether it’s to comply with regulations, reduce costs or improve revenues), the more chance you’ll have in gaining attention and alignment.

Which brings us to the final point: set up your program so that small wins are achieved throughout.

Whether you need to set up prototypes, pilots, or small projects while you are driving the entire strategy over time (probably several years), you need to prove results. Otherwise, no matter how great your plan, the organization will lose interest along the way.

So, if you set expectations appropriately, have a good measurement plan in place, and keep communicating constantly with all levels of the organization, then you’ve got a great chance of succeeding!

But in today’s article, we want to suggest an approach that’s more likely to succeed in the long run – tying the MDM project to solving an important business problem, and then getting the business to not only sponsor the initiative, but to “own” it.

Depending on your industry, there are key business drivers frequently seen in that industry. For example, in manufacturing, the key drivers are usually margin analysis, supply chain analysis, product profitability and customer satisfaction. In the software industry, license revenue analysis, maintenance contract revenue (new and renewals), support margins and customer satisfaction are the key drivers.

When you talk about how MDM may improve results in these areas, the business owners perk up and listen. So invest some time in understanding the corporation’s strategic priorities for the next few fiscal years, and then choose a small number of these strategic priorities as the key drivers to be tied to MDM.

At a leading software company, Marketing had recently undergone a radical overhaul. The new head of Marketing was swamped by the number of “mini-databases” that had sprung up, both within the department itself and within IT. For their launch of their new software product, he needed to know who his customers were – on a particular version, at a particular support level, and in a particular geography.

It took the Marketing department weeks to get that final list. As a result, the CIO stepped up and linked the MDM initiative’s success to specific metrics used by Marketing.

Marketing was then totally engaged in the MDM project, and that momentum carried right through the product launch. And Marketing even hired a data steward for ongoing data management.

Had it only been the Technology group carrying the burden of doing the MDM project, I’d bet the project would have fallen by the wayside and there would not be any surviving MDM program there.

The key takeaway is to link your Data Quality and MDM initiatives to your enterprise’s key business drivers and your executives’ priorities. Only then you will get the business to put their money where their mouth is. And only then will you be assured of a successful ongoing MDM program.

Last week’s MDM Summit conference was great, as usual.  Attendance may have been down slightly due to the well-publicized economic situation.  But there were still a lot of “end user companies” in attendance, either speaking or attending to learn more about this fast-growing field.

One theme we picked up on was the idea of “Master Data Management solving business problems”, rather than being a pure technology “silver bullet”.  While having a central hub, married up to powerful data quality software, and integrated with the rest of the enterprise via the latest Service-Oriented Architecture integration tools is very definitely sexy, what’s even more compelling is looking for and solving the most difficult recurring problems that today’s large companies are facing.

Whether it’s driving increased revenue through better, more effective marketing and selling, or reducing costs by improving process efficiency and sunsetting redundant application infrastructure, or enabling smoother, more rational regulatory compliance, the promises of MDM are being realized in the leading companies who are implementing it.

This is not hype, people.  While there may well be a “trough of disillusionment” in MDM’s future (or going on right now), the business and IT benefits are real, large and realizable.  This is not a repeat of the wave of ERP adoption prior to Y2K, or the rush to implement a “me too” CRM strategy.

Any time you can help the business make more money, spend less money, and have a markedly easier time getting the bureaucratic monkey off its back, people in the business are going to notice and reward you for it.

I hate to say “the future’s so bright we have to wear shades”, but from our perspective, MDM is just hitting its stride, and does indeed have a bright future.

If you disagree, we’d love to hear from you via a comment.

Business Growth is really the heart of your business case. If you can identify how an Information Management strategy will enable your company’s growth, then your chances of success go way up!

This topic may be a little more difficult to document, but most executives will not argue with you if you can validate your premises.

Start by looking at existing strategic initiatives, then meet with the business areas responsible for those results and see if issues with the current corporate data could prevent them from achieving their goals.

Let’s look at the types of growth enablers you might consider:

  • Mergers & Acquisitions
  • Customer Service / Experience
  • Customer Targeting
  • Customer Coverage
  • Forecasting / Planning / Modeling / Reporting
  • Product / Service Offering
  • Channel Strategies
  • International Strategies

Questions you might ask your internal partners are: “Could you be more effective at getting your marketing materials to the right person?” “Could you improve targeting or forecasting through improved reporting, modeling or planning efforts?” “Could you improve the customer coverage model if we could more effectively identify and target customers?” “Are we failing the customer because processes are operating with bad data?” “Are there channel conflicts due to multiple or uncontrolled data sources?” “If you had better business intelligence, would you have a better chance of bringing the right product or service to market?”

If you get “yes” answers, then determine the benefits and the order of magnitude if you had a solution. Types of solutions could be through solving problems with data quality, hierarchy management, data integration, and resolving data source conflicts (through a Single Source of Truth), etc.

By helping business leaders frame their problems in terms of how an Information Management strategy could help them, then you’ve got the beginnings of a strong business case.

Your next step is to define the business requirements in more detail, and have your internal business partner(s) help you quantify the impact of solving their problems.

Stay tuned for Part 4, where Maureen Butler covers how to get organizational alignment for your business plan.