In the Field with our Experts

Welcome to the MDM Show, “What’s My Role?”

By Bob Wall, Senior Consultant

Years ago, I regularly watched a television show called “What’s My Line”, moderated by John Charles Daly. The show featured a panel of four celebrities (e.g. Bennet Cerf, Steve Allen, Dorothy Kilgallen and Arlene Francis) who questioned the contestants and tried to discern their occupation. The panelist would begin asking the contestant yes-or-no questions. If they received a “yes” answer they continued, but if they received a “no” questioning passed to the next panelist and $5 was added to the prize tallied on cards Daly would flip over. A contestant won by receiving ten "no" answers (as Daly occasionally noted, "10 flips and they are a flop!") or if time ran out.

If you’ve worked on a Master Data Management (MDM) project, specifically a Customer Data Integration (CDI) effort,  you may think you’re in a remake of “What’s My Line”, but now it is called “What’s My Role.” Because we are trying to integrate customer data from possibly dozens of systems, we need to understand what role the customer played in that system.

For instance, we may designate Jane Doe as a customer. For argument’s sake, a customer defined as a person or organization who has purchased one of our products, but in the shipping system she shows up as ship-to-customer, in the accounts payable system as a bill-to-customer, and in the HR system as an employee.

One way to get around this is to use a generic Party data model (with subtypes of Person or Organization) and to use 2 types of roles for that Party; Declarative and Contextual. For a Party, we might define a “role” for the party, and declare that role as “customer,” the part that an organization or person plays within the enterprise. We then might look at the associative relationship between a source application system and Party and define a contextual role, how a party is or was involved within the context of another entity. Here the roles might be ship-to, billed-to, or employee, but we always establish one instance of the specific party, in this case Jane Doe. A good discussion of using roles can be found in Len Silverston’s “The Data Model Resource Book, Volume 3, Universal Patterns for Data Modeling.”

Using a generic approach to roles for your MDM/CDI project may help you to integrate these roles and not wind up like panelists on “What’s My Role,” where you could face 10 flips and you’re out!

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Bob Wall is a senior consultant with Baseline Consulting. He is an information technology specialist with 30 years experience in all areas of data warehouse administration, data architecture, data resource management, training, and applications systems development, as well as in corporate management.

Ready, Shoot, Aim: Gaining Control of Your Data

By Carol Newcomb, Senior Consultant

You’re already familiar with the common symptoms: rapid heart rate, shallow breathing, sweaty palms and jumpy behavior.  When you are asked to identify the strategy for information management in your organization, your mind draws a blank.  “So, I’m not the CIO.  Go ask him!”  When asked about the most reliable source for master data on customers or contracts or sales force, you mumble, “Try the ERP system.  That’s where I found it last time.”  Or if an outside contractor were to ask about your 5-year plan for information management and BI strategy, you shrug, puzzled.  “What good is a 5-year plan when I don’t even have a 1-year plan?  Leave me alone.”  Treading water is the mode of survival.

The single most common problem organizations face these days is too much data.  It comes from all directions for all sorts of purposes.  It comes from dozens of applications designed to fulfill specific functions.  It has grown over the years until reluctantly, one of the organization’s leaders says “Enough already!”   Data is now costing more to manage than it is contributing to informed decisions.  Data is not an asset, it’s a liability!  How did this happen?  It’s like a teenager’s fantasy: wanting and having, wanting and having, bright shiny objects, more and more, until the sobering realization sinks in that the dream is no longer just a dream—it’s a full-fledged nightmare! 

Information management is all about control.  Stop.  Step back.  Get some perspective.  Assess the true situation. Itemize what’s good and what’s subpar.  Think about what the organization needs to achieve.  Think about how the data supports those objectives, not how the organization manages despite its data.  Data management is a deliberate, stepwise set of practices designed to ensure that value can be extracted from the data, and that the overhead associated with poor quality, inconsistent definitions, unaligned source systems and discontinuous data management practices are orchestrated to work as a whole.  The objective is to deliver information value.

So how do you go about changing from ‘Ready, Shoot, Aim’ to ‘Ready, Aim Shoot’?  First, get ready.  Admit that survival is not a strategy.  Survival is survival, and it is getting more difficult to maintain your organization’s survival, much less its competitive edge.  Next, invest the time and resources in drawing that big ugly spaghetti diagram, an inventory of ALL the source applications, software systems, ETL points, staging systems, landing points and delivery channels.  Then, take a true inventory of the end-users.  This is critical, because this is where data begins to result in business value.  Take time to really research who does what with certain pieces of data.  Do they further augment it with external data?  Do they merge it with other internal or external data?  Do they modify it to match other data sources?  How much time do they spend cleaning, standardizing or massaging data?  Start to build your ROI equation.  Data Sources X Time X People = Business Information Cost.  How much is this really costing?  Where is the value?

As you learn more about how the business uses data, start to lay out a business value matrix (the other side of the ROI equation).  This will help prioritize your data management roadmap.  Estimate the amount of effort required to integrate each source against the perceived business value, and chart a business value/implementation effort matrix.  Consider drafting more than one, as this reflects perceptions more than actual fixed units.  Share this information with end users to validate it and socialize a plan.  Then start to lay out a tactical roadmap.  Aim!

Now you’re getting somewhere!  Having faced the ugly reality (Ready) and incorporated real-life facts from business end-users (Aim), you can start to craft your strategy to streamline and rationalize the multiple data lifecycles supported by your organization.   Shoot!  Prioritize the data sources and systems to begin with, and estimate the expected value.  Launch your governance, metadata, quality and delivery resources, and engage your business users each step of the way.  Deliver value and repeat.  Evaluate the process, refine, and keep going.  It’s a deliberate, engaged, transparent and proactive approach, and it’s the only way you will ever conquer those adolescent nightmares!

photo by Erik Charlton (via Flickr)

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Carol Newcomb is a Senior Consultant with Baseline Consulting. She specializes in developing BI and data governance programs to drive competitive advantage and fact-based decision making. Carol has consulted for a variety of health care organizations, including Rush Health Associates, Kaiser Permanente, OSF Healthcare, the Blue Cross Blue Shield Association and more. While working at the Joint Commission and Northwestern Memorial Hospital, she designed and conducted scientific research projects and contributed to statistical analyses.

Get on Board the MDM Express

By Bob Wall, Senior Consultant

Imagine if you will you're the CIO of a mid-market pharmaceutical company and you've just been to a TDWI conference that had a session (“Introduction to MDM for BI Professionals”) that provides an overview of master data management. You’re heading back to your corporate headquarters by train. You feel convinced that like this train, MDM is speeding along gathering momentum, and you don’t want to be left at the platform and miss the opportunity to get your company on the MDM Express!

You may have heard that MDM offers a single version of the truth, enterprise-wide, about customers, products, and other information types. As CIO, if you look around at your company’s issues you realize right off the bat that customer data integration is a real issue. You think to yourself that it would be nice to be able to take an MDM strategy and implement it to consolidate, integrate and synchronize all of the customer data so that it would be more accurate and it would enable your sales and marketing teams to better leverage the market value of your customer relationships. However, you're faced with the daunting fact that MDM is a very complex concept—and potentially an expensive one. Moreover, many MDM vendors price their products such that they’re out of reach for the small to medium size company.

How do you get started?  Here are four proven starting-points for MDM:

1. Find the business sponsor. I know it’s trite and overused, but since you’re the CIO it’s likely you know where the pain is among your C-level colleagues. Enlist the CFO whose numbers don’t reconcile across billing and invoicing systems, or the CMO who struggles with a growing number of customer lists.
2. Engage a readiness assessment. You can do this with internal or external resources, but do it. Gauging readiness has little to do with whether people know what MDM is and more to do with your incumbent skills, data management practices, toolsets, and needs.
3. Define a Small, Controlled Project. Work with the sponsor and cut a slice out of the overall problem that you can use to not only demonstrate the value of MDM, but establish the technology foundation.
4. Build the team. You can’t just “assign” MDM to your BI or CRM team. You need to construct a new team of data-savvy practitioners who will own enterprise master data for the long-term.

Sure, there are other deliberate steps. Maybe you want to do an educational workshop to get everyone on the same page, or talk to some incumbent vendors about their offerings. But these tactics and others could backfire if they are ill-timed. Better to think globally but act locally, and reap the rewards.

photo by jurvetson (via Flickr)

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Bob Wall is a senior consultant with Baseline Consulting. He is an information technology specialist with 30 years experience in all areas of data warehouse administration, data architecture, data resource management, training, and applications systems development, as well as in corporate management.

Public Sector takes SaaS for a Spin

By Rob Paller, Consultant

There has been a lot of talk about the growth and potential impact of Software as a Service (SaaS) in the realms of business intelligence, MDM, and to some extent data warehousing on Twitter and numerous industry blogs.  The premise behind SaaS is to move the hardware and software from your data center into the cloud. By doing so you reduce the costs associated with deployment and maintenance of the hardware and software. Much like Google has done with your email, documents, and photo libraries.

Google is turns out to be a great example because of their partnership with Panorama Software. Panorama Software is helping lead the charge by providing one of the first OLAP services in the cloud. Using Google Docs and Panorama’s SaaS solutions allow you to create pivot tables or take your cubes from SQL Server and move them into the cloud for collaborative analysis.  However, that has nothing to do with what is going on in the public sector and is best saved for another discussion.

Recently, one of our clients in the public sector has taken the concept of SaaS and applied it across the agencies and departments for many of the same reasons a small or medium sized business would consider looking to the cloud. Our client has established a group within its IT department whose purpose is to share services at an enterprise level to help drive down costs by reducing multiple contracts with the same vendors and standardize on the solutions offered. The solutions offered by this group range from data cleansing, data integration, business intelligence and data warehousing.  Going forward, this group is also working toward establishing a master data management solution as they begin to address the requirements to provide electronic medical records. A substantial benefit in applying the SaaS concept across the departments and agencies is found in the reduced cost in training staff that transfer from one department or agency to another and reduce time to delivery of new solutions. 

While the traditional SaaS concept may work great for the small and medium sized business the fact of the matter is that large corporations and even the public sector is less likely to make the jump into SaaS right now.  Do you think the spin being applied to SaaS concept at this client could work for large companies or other areas of the public sector? Let me know in the comments below or on Twitter.

photo by David Accampo (via Flickr)

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Rob Paller is an expert at business analytics and database administration. Since joining Baseline, Rob has been responsible for developing a case analysis system to streamline the oversight of food assistance benefits, implementing a common citizen data model, and assisting in the rollout of a new public assistance data model integrating data from over 10 years of legacy with a new benefit eligibility determination system.