And I spoke earlier this week at the New England Oracle SOA Users Group, talking about Master Data Management as a foundation for Service-Oriented Architecture.
MDM initiatives seem to be getting linked to Service-Oriented Architecture or to advanced analytics and business intelligence programs.
I think there can be a problem (but also an opportunity) for MDM in inserting itself between two things that used to talk directly from one to the other (an ERP system to a data warehouse) or (b) asserting itself as a predecessor task to ensure a better outcome (for example, when MDM is used to consolidate and improve the quality of enterprise data before people try to use it in analytics or business intelligence).
While I think it’s true that MDM is in fact needed at most large organizations, having to coordinate with an already-underway SOA initiative, or step back from a planned BI initiative and first tackle MDM, does complicate things a bit. So that’s the “problem” part.
The “opportunity” part is that, for organizations that have the foresight or the luck to tackle MDM first, it makes implementing SOA or achieving business intelligence success that much easier. There’s already a centralized repository of information on customers or products (or whatever domains have been mastered), and that information is proactively managed so that it’s trusted to be accurate, complete, timely and consistent.
Whichever situation your organization is in (tackling MDM first or building it into something else like SOA or advanced analytics), spend the time to develop a workable MDM strategy, using a holistic approach that addresses people, process, technology and information. By all means include an MDM hub in your planning, but make sure you also plan for business process management or sophisticated integration, as well as built-in or bolted-on data quality and enrichment capabilities. And be sure to build a data governance framework around your MDM initiative.
I’ll write a trip report after next week’s DIG conference, to let you know what I thought of the conference itself and whether I got lucky at the tables!
I’ve known Haidong for several years, from my “previous life” at D&B, where I managed D&B’s alliance relationship with Oracle.
He made several great points that resonated with me:
- “MDM is the foundation for all of the other product areas and modules”
- “Poor Data Quality is the #1 Enemy of MDM”
- “Somehow, data has been left out – an afterthought – but if you don’t focus on the data, you’ll have issues”
- “Technology can actually magnify the problem if you propagate bad data across the enterprise”
- “Master data is in a constant state of flux” (what I call the ‘data decay’ problem)
- “Master data changes at a rate of 2% per month on average, so after 2 years, nearly half your data is obsolete or suspect”
Haidong talked about why data governance is needed in the enterprise, and how data quality issues can be an inhibitor to application acceptance. He talked about helping clients to avoid large fines and bad publicity, and the need to formalize a data governance framework.
He gave Toyota Financial Services and UMB Bank as two customer success stories, talking about their situation and challenges, and the Oracle solution they implemented and the positive results they experienced.
And he used the idea of a “Day in the Life of a Data Steward” to walk the audience through Oracle’s new “Data Watch & Repair” offering for MDM. It’s a closed-loop process, consisting of “Connect”, “Profile”, “Assess” and “Repair & Monitor” steps.
He also discussed Oracle’s integration with Acxiom, a consumer content provider, and with D&B, a business content provider.
He ended by describing Oracle’s MDM solution as the most complete offering on the market today. At Hub Solution Designs, we partner with all of the leading MDM hub providers. But from my previous experience with Oracle’s MDM products, and Haidong’s session today, I am very comfortable predicting continued success for Oracle in the marketplace.
Today, we’ll talk about some criteria you can use to evaluate Master Data Management vendors.
Before you go into “evaluation mode”, it’s important that, on the business side, you first have your MDM strategy chalked out.
And on the technical side, you should have mapped your organization’s data landscape, completed some in-depth data profiling and documented your data requirements. Not doing these things can significantly reduce your chances of getting the right MDM platform for your company.
Some important questions you can ask your potential vendors are:
- Do they support multiple data domains? In other words, does their solution handle just one type of data (like customer), or can it handle other important types of data, like product information, as well?
- In what vertical industries do they have a strong presence?
- Is their solution service-oriented architecture (SOA) enabled? What services are available “out-of-the-box”?
- Does their product have workflow capability or an MDM methodology built-in?
- If hierarchies are important to your organization, do they have a flexible hierarchy management tool?
- What third-party data providers do they integrate with (e.g. D&B, Axciom, Trillium, etc.)?
- Is their solution used primarily for operational or analytical MDM?
- What’s the state of resource availability in the market (or at SI firms) to implement their solution?
- Do they have an integrated data quality engine for standardization, matching and measurement purposes?
- Lastly, are they easy to work with in terms of response times, flexibility, and demonstrated alignment with your corporate objectives?
Answers to these questions may not be readily available on the vendors’ websites. But if your organization hasn’t started its software evaluation process yet, and you’d like answers to some of these questions, please feel free to contact us for our perspective.
As SOA (service oriented architecture) initiatives gain popularity, let’s look at how MDM (master data management) and data governance can dovetail with a SOA strategy.
SOA, although technically a type of IT architecture, is more of an integrated approach to building high-level services that are inherently reusable and scalable across various applications. High-level services are not consumed as end-point services themselves, but operate more at the business process level.
While composing the entity framework for a service-oriented architecture, a Data Governance Council should be an integral part of the SOA team. The role of the Data Governance Council is two-fold:
- Provide a comprehensive data map (authoritative sources, data flows and underlying data policies) to the SOA architects, and
- To plan and implement “Master Data Services” as part of the services available for consumption to applications within the scope of SOA. An example would be “Create Customer”, where sources, lookups, standards, business validations and enrichments are all built-in, and are available for applications across the enterprise to consume in a robust, auditable fashion.
So what does this do for an MDM initiative?
It provides a powerful platform to integrate the current business processes and to improve levels of data quality, to provide accurate, current and complete data within and outside the IT applications.
It also provides a central platform and process for various domains of master data (suppliers, items, etc) as they come aboard the MDM bandwagon.
Hub Solution Designs, Inc. was incorporated in September 2007. At this point in our history, I thought I’d spend a few minutes reflecting on what we’ve done so far and where we’re headed.
Clients: we’ve been lucky to get off to a strong start here and have formed some great relationships. We take confidentiality seriously, but you can get a sense for the relationships in our article A Good Client Site Visit. One client said they’ve “made huge strides toward our MDM vision, and you’ve helped us work through the areas that were broken”.
Team: another area where we’ve been very fortunate. We have a strong group of experienced MDM practitioners: Tim O’Sullivan, Gaurav Arora, Eric Gustafson, and Maureen Butler. I believe that with a great team, anything is possible – and we’re very lucky to have assembled this team in the first six months or so.
Partners: from the beginning, our vision has been to partner with all of the MDM hub software vendors. Our strongest relationships on Day 1 were with Oracle and D&B/Purisma (due to my three years working at D&B, managing its alliance with Oracle). But we’ve developed great working relationships with both Siperian and Initiate Systems as well (for example, Tim O’Sullivan just attended a week-long training class on Siperian). We’ve been very impressed with the caliber and professionalism of both Siperian’s and Initiate’s people. And we’re working hard to further develop our IBM and SAP partnerships as well.
Marketing: We’ve been getting the word out on Hub Solution Designs over the last three months. In February, we launched a completely redesigned web site, and this month has been our best month ever on our corporate blog. We’ve had 4,850+ hits to date, with 1,000+ hits so far in March ’08.
DM Review magazine has also been very supportive. My article on “The Politics of Master Data Management & Data Governance” was published as the cover story in the March ’07 issue. Tim O’Sullivan has an article that will be published as the cornerstone of an MDM supplement that will be mailed with their June issue. And I’ll be doing a monthly column for DM Review’s Online Edition starting in May.
Speaking engagements: We’re speaking at the Spring 2008 MDM Summit in San Francisco next week, and in the MDM track of the Oracle Applications Users Group COLLABORATE 08 conference in Denver in mid-April.
The MDM Summit session, which will be presented jointly by myself and our client, Shirlee Collins from ADP Dealer Services, is entitled “Real World Data Governance” (Tuesday, April 1st, 4:00-4:30 pm PDT). We’ll talk about establishing a data governance organization, improving underlying customer data quality, and creating a robust process to enrich customer data in Oracle Customer Hub with D&B information. The ADP Dealer Services story reflects a pragmatic approach, aligning Sales Operations and Finance, and balancing each group’s needs and priorities in managing customer master information.
I’m also speaking at COLLABORATE 08 in Denver, CO, which is the annual conference of the Oracle Applications Users Group (OAUG), and which will have a Master Data Management track for the first time. The session, “Best Practices in MDM and Data Governance” (Tuesday, April 15th, 9:45-10:45 am MDT) will present some useful best practices, and will also cover what works and what doesn’t, the importance of a holistic approach, how to get the political aspects right, and how to address more than just the technology elements.
So at this point in our firm’s development, I couldn’t be more excited about the overall MDM market, about our great clients and team members, and the future potential we’ve got for the remainder of this year and beyond. We’re building a great company from the ground up, working hard for our clients, and having a lot of fun in the process.
I was reading a whitepaper by Aaron Zornes today (“2007-2008 Scorecards for Data Governance in the Global 5000 Enterprise”) and came across an interesting quote:
“Although many organizations have improved end-to-end business processes through CRM implementations, the challenge of developing a unified customer or product view has not been fully addressed by the application suite vendors. For example, enterprise CRM solutions such as Siebel Systems supposedly were to integrate sales, marketing and service functions but in reality provided mostly automation of the sales force with arduous and fragile interfaces between sales, service and marketing. Concurrently, enterprise resource planning (ERP) was marketed as the integration among accounting, manufacturing and distribution. In practice, large enterprises are now turning to MDM as the service-oriented architecture means of unifying both CRM and ERP individually as well to integrate the front office (CRM) and the back office (ERP) together. “
In my experiences over the past twenty years or so, the enterprise software implementations I’ve been part of have treated data and process integration as a “necessary evil”. Almost like a difficult proof in a college math class, where the professor takes you up to a certain point, and then as the class ends, calls out that “the rest of the proof is left as an exercise for the class”.
I’ve seen projects where several systems were supposed to be integrated but never were, or where the front office and back office were integrated through “manual integration”, i.e. manual re-keying of key customer and product information between the two systems.
Little wonder, then, that ERP and CRM investments in many cases failed to deliver their expected return on investment. And now large enterprises are turning to Master Data Management (MDM). Given that successful MDM implementations requires five essential elements (data governance, a hub platform, integration, data quality and external enrichment capabilities), the temptation is there for people to de-scope important aspects of MDM.
Just as critical interfaces were de-scoped from earlier ERP and CRM projects, we’ve started to see people trying to do MDM without data quality, and even without adequate integration.
But let’s collectively resist these temptations. MDM and data governance are “hot” right now because they offer the promise of accurate, complete, timely and consistent information across the enterprise.
If we start to compromise on the essential elements of MDM, or fail to address MDM’s interconnected nature of people, processes, technology and information by focusing only on the technology, then in the not-too-distant future, MDM will not only go through Gartner’s “Trough of Disillusionment”, but it will be largely discredited. The industry will miss out on some huge future opportunities, and global enterprises will miss out on the ability to invest in their people, redesign their processes, implement new technology for MDM and service-oriented architecture, and weave in external information to supplement their internal data.
We all understand the pressure in the corporate world to deliver results in one quarter or less, but let’s make sure our short term approach doesn’t compromise the long term vision so much that the longer term return on investment becomes unachievable.
“Data governance is critical to these master data management efforts and ultimately is the tipping point as to whether the MDM program’s business outcome achieves its intended ROI and long-term sustainability.”
So resist the temptation to identify the need for Master Data Management, and then immediately run out and engage a systems integrator to help you evaluate, select and deploy some MDM technology. Remember to invest (either up front or in parallel with your MDM selection and deployment) in defining a workable data governance organization with accompanying business processes.
By paying attention to the integration between data governance (i.e. the people and processes) and the MDM techology (hub platform, integration, data quality and external enrichment), you’ll dramatically increase your chances for the successful delivery of expected functionality and ROI, on time and on budget.
When it comes to building the case for an Information Management strategy, cost reductions alone may generate enough benefits to justify your business case, or they could further enhance your economic arguments.
Here are some examples of where you may uncover potential cost reductions:
1) IT costs, such as managing redundant systems/databases, data duplication and/or reconciliation, consulting fees, and software maintenance fees
2) Delivery costs due to inaccurate data, such as product returns, shipping fines, direct marketing waste, returned employee mailings, and Day Sales Outstanding (DSO) costs from invoicing delays
3) Productivity costs due to inefficient processes creating workarounds, redundancy, or rework. Also consider costs associated with audits, time to search for customer records, and time wasted matching customer files
Start by interviewing internal business partners to determine where they have issues. If your partners identify problems and participate in the business case development, they’ll have a vested interest in supporting it. Here are some business areas to consider:
- Finance / Credit / Accounting
- Sales / Contracts
- Corporate Development / Mergers & Acquisitions
- Customer Service / Call Center
- Operations / Production
- Human Resources
- Product / Vendor Management
Ways to identify and measure costs include:
- Quantify shipping fines, returns, or other operational expenses
- Quantify mail return rate, response rate, and delivery hit rate (did the mailing actually make it to the intended person?) Check with Direct Marketing, HR, Finance/Accounting/Credit, Mailroom, or any other outbound mail services for these costs.
- Identify rework or workaround activities such as returned mail, product, and invoice corrections, product information corrections, report reconciliation, multiple databases, merge/purge and data matching errors, etc. Some partners, both leadership and end users, may accept this as ‘business as usual’, so be careful not to appear threatening or overly challenging.
- Conduct process mapping or other continuous improvement activities to identify & quantify problem areas. Always keep a broad perspective and analyze both up and down-stream processes.
- Conduct time studies on processes or transactions that appear inefficient such as customer service, warehouse, manufacturing, vendor management, payroll, reporting, data management, selling, marketing, planning, forecasting, customer maintenance, mergers and acquisition, etc.
- Conduct satisfaction surveys to measure customers’ experience with duplicate mailings, wrong customer information, delayed shipments due to bad data, credit problems, customer look-up time, etc.
- Work with UPS, USPS, FedEx and other carriers to determine how to improve shipping/postal rates
Cost improvement opportunities will exist all around the business; the trick is determining where you will get the “big wins”. It’s good to have a Finance partner participate throughout this process, so your assumptions and calculations are ‘blessed’.
To find out how to identify business growth opportunities and align business leaders, stay tuned for the next two articles in this series by Maureen Butler.
As the early adopters of Master Data Management are starting to move beyond their single data domain implementations and branching out to other domains, we’re seeing the timely arrival of MDM hubs capable of handling data from multiple domains. So, what are multi-domain and federated hubs? What are some key questions to consider? And what are companies tending to adopt for global strategies? Here’s my take on these questions.
The first key consideration is “what business problem are you trying to solve with MDM?” The answer will point you in the direction of what data is required to solve that business problem. Invariably in this “business process centric” approach to MDM data, you’ll discover that you need data from multiple domains to solve the problem.
The term “multi-domain” has emerged as a way of distinguishing MDM hubs capable of managing more than one primary domain of data. The need for the term arose to distinguish single domain hubs (such as a dedicated product information management or PIM hub) from “multiform” MDM hubs from Siperian, IBM or Oracle, all of which are capable of managing multiple domains of data such as customer, supplier, product, location, and their associated hierarchies.
The rollout strategies that companies are adopting for their MDM initiatives are to start small and then build from there. In the “business process centric” approach, as each additional business problem is tackled by an organization, additional domains of data are added to the MDM hub, using the same methodology for each successive problem.
While this approach sounds similar to a data warehousing analyst, the key to the MDM approach is that data stewards (reporting to the business function) will manage the data within a data governance framework. In other words, a business process solution which is capable of being managed by the business.
The second key consideration is “how will you achieve enterprise MDM?” That is, managing MDM data on a global basis using a centralized hub vs. a series of federated hubs. While the term “federated” has been used in association with Registry style MDM hub implementations, the term is now also used with the Persistent style hubs, but using a different architecture from Registry style hubs.
Companies have two options in addressing a global deployment of a Persistent style MDM initiative.
The first is to implement a centralized hub in a single location that will be accessed from all other locations as data is needed. This requires constant synchronization of data between global source systems and the centralized persistent hub.
The second option is for each location to maintain its own local hub and then federate across the local hubs to a single corporate hub. The federation of persistent hubs requires the infrastructure to maintain data and metadata synchronization between local hubs and a corporate hub. Data sources will be synchronized at the local level with each local persistent hub.
The deployment strategies that most global corporations are following with Persistant style MDM hubs is to use federation across local persistent hubs rather than a single centralized hub in one location that must be accessed from all other locations for MDM data.
The federated approach avoids overlapping data in local hubs and with a common set of technologies in all global locations supports a consistent data stewardship approach.
For those of you who have implemented master data management in your organization, please let us know whether you’ve chosen a centralized hub or a series of federated hubs.