In the Field with our Experts

The Metadata ROI Series: Episode 3: Report Users

By Stephen Putman, Senior Consultant

This posting is the third in a series discussing various aspects of the financial justification of a metadata management system implementation that are not obvious in many existing analyses. Today, we will discuss the time and effort saved by reporting users in business organizations.

In Part 2 of this series, we took a look at how the software development process is aided by a robust metadata system. In this installment, we will look at the support that a metadata system can give to the end-user reporting groups throughout your organization.

One of the main things that concern end-users is the definition of business terms and how these definitions are represented in the various computer systems that they use daily. This is a huge risk exposure to the enterprise because confusion on definition of terms could lead to conflicting data reported by different groups in the organization, in extreme cases causing financial restatements at potentially great cost to the organization.

A comprehensive metadata system gives reporting users a consistent base of business definitions, data representations, and linkages between the data to mitigate the risk of misstatement of organizational data. It makes report producers more efficient, and reduces service calls to the IT organization for assistance on the business meaning of data. The returns gained by a metadata system can be measured in the reduction of IT service needs and the mitigation of post-auditing of reporting results that often occurs when definitions are unclear.

Another benefit of a robust metadata system involves the integration of operational metadata to determine the “freshness” of the data in reporting systems. The activity of loading of data into reporting structures can be recorded to the data element level, which is utilized by reporting users in dating their output, ensuring the most current data in the report. This instills further confidence in the results produced by reporting users, and although it is nearly impossible to measure this in monetary terms, it increases the general goodwill of the organization.

In the final installment of this series, we will examine the usage of a metadata system by the software development program management organization.

photo by Engin Erdogan via Flickr

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Stephen Putman has over 20 years experience supporting client/server and internet-based operations from small offices to major corporations.  He has extensive experience in a variety of front-end development tools, as well as relational database design and administration, and is extremely effective in project management and leadership roles.

The Metadata ROI Series: Episode 2: Software Development

By Stephen Putman, Senior Consultant

This posting is the second in a series discussing various aspects of the financial justification of a metadata management system implementation that are not obvious in many existing analyses. Today, we will discuss the time and effort saved by software development staff in system implementation projects.

In Part 1 of this series, we examined the value of a metadata management system in regard to the gathering and documenting of business requirements. In this installment, we will take a look at the next phase of a system implementation - software design and development. A metadata management system can help you save money and time in these areas as well.

For new system development, the system designers and developers can use the data stored in the business requirements process as a basis for their designs. Properly documented requirements leave little question as to the intent of the system, and reduce (or even eliminate) the need for follow-up meetings between the engineering staff and the business analysts. Measuring this saved time by the assigned resources is your first source of return for the investment.

Two other major areas of development that benefit greatly from metadata are Extract-Transform-Load (ETL) development and report development. Both functions need to know where data is located on various systems, which is something a metadata system does well. For ETL development, the location and mapping of source data elements is also available. Developers contribute specific information related to their activities to the metadata system to demonstrate fidelity in design to requirements and design considerations introduced to the system.

The major return on investment of a metadata system in the software development area is primarily related to the time saved by staff in information discovery and application. It is important to measure both pre-metadata-system and post-metadata-system metrics on developer and analyst time to accurately determine the money saved by implementing the metadata system.

In Part 3, we will tackle the potential cost saving to end-user reporting groups in your organization.

Photo, "physical metadata," by Nadya Peek (via Flickr)

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Stephen Putman has over 20 years experience supporting client/server and internet-based operations from small offices to major corporations.  He has extensive experience in a variety of front-end development tools, as well as relational database design and administration, and is extremely effective in project management and leadership roles.

The Metadata ROI Series: Episode 1: Business Analysis

By Stephen Putman, Senior Consultant

This posting is the first in a series discussing various aspects of the financial justification of a metadata management system implementation that are not obvious in many existing analyses. Today, we will discuss the time and effort saved by Information Technology business analysts in system implementation projects.

In a database implementation project, one of the first activities performed is the gathering of business requirements. These requirements are gathered from business users mainly by interviews and document inspection. The business analysts (and data modelers) take this information and produce documentation describing these requirements, and often perform data mapping between systems when data movement is required.

A basic function of a metadata management system is to describe data elements within computer systems and record attributes of these elements, such as the resident table(s), data types, business rules, and so on. A metadata management system makes it easy for the business analyst to gather relevant information about the existing data elements involved in the data movement in the system, and aids in the design of the data store for the new system by facilitating the data mapping exercise. These two simple uses of the repository save a tremendous amount of time and effort by the analysts in these activities.

It is a simple matter to quantify the cost savings of maintaining a metadata management system for business analysis activities by determining the time spent by staff on collecting and transcribing source data element definitions, subtracting the (very small) time spent extracting the same information from the metadata management system, and multiplying the result by the salaries of the business analysts involved in the project. This result is placed in the “return” bucket of the Return on Investment calculation. This savings is also something that continues to pay dividends over time when more projects utilize the metadata repository in this way.

This example shows that metadata management systems positively affect several areas or your IT organization that are not immediately apparent. I will be detailing more of these functions over the next few months.

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Stephen Putman has over 20 years experience supporting client/server and internet-based operations from small offices to major corporations.  He has extensive experience in a variety of front-end development tools, as well as relational database design and administration, and is extremely effective in project management and leadership roles.

Who’s on first when it comes to integrating customer data into a single version of the truth…

By Steve Bebout, Senior Consultant

 

We’ve all had situations when we think, Does this company even know who I am? Why do I get contacted about products or services I have ‘opted’ out or for which I am not a viable candidate?
Additionally, when I specifically request information, why can’t they provide me with that information?  Addressing these issues is complex but at the crux of why a single version of truth is worth investing in.

I was recently involved in a project where each line of business (LOB) was positioned against the other from a revenue standpoint.  Each LOB was rewarded by creating the largest amount of gross revenue for the company which made information sharing not a top priority.  It wasn’t a situation where they didn’t see that customer data was an asset; however the value of that asset was directly tied to the LOB’s profitability.  Senior management saw this as a problem and realized the opportunity cost associated with multiple versions of the truth.

Without coming to an agreement on a single version of the truth for customer, they would never know "Who’s on First" and how to maximize "who's" lifetime value.  Why am I using "Who’s on First?" as an analogy?  Well, it’s an Abbot and Costello routine that portrays confusion around a person’s identity.  In this parody, even with the best of intentions, they are talking past each other.  Their disagreements reveal their lack of understanding of "who" really is, what he does, and what his value is…

After creating agreement on the enterprise data definitions, senior management provided us with future business goals that we used to create key business drivers for the company.  The key business drivers were:

• Create efficient data accessibility and ensure data quality across the enterprise
• Measure the effectiveness of marketing activity
• Understand behavior for more targeted cross-sell and up-sell
• Share integrated, cleansed, and enriched customer data

Alignment was key to developing support and creating a new cultural view of data sharing.  Aligning analytical processes, key functional capabilities, and subject areas supporting customer behavior to business drivers created prioritization and a road map for creating a single version of truth.  How do you support your assumptions to the client?  We created traceability examples for the key business drivers mentioned above.

By providing the company with basic examples of how bringing together the customer data from the LOBs disparate sources into a single centralized data repository can provide value opened their eyes and was a key way to get the enterprise ‘onboard’ to create a single version of the truth.

I found traceability matrices to be a valuable tool for resolving the multiple versions of the truth in identifying ‘who’, has anyone else used this approach or have other techniques that they have found been successful?

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Steve Bebout is a consultant with over 15 years of experience in information technology in the areas of application development, business requirements, data analysis, and project management.  He has experience in the Communications Media and Entertainment, Financial Services, Life Sciences, and Insurance vertical markets; spending the majority of his efforts on customer data integration initiatives. 

Process is Half the Story

By Stephen Putman, Senior Consultant

I’m catching up on some reading these days, and I’m currently reading Broken Government by John Dean. This book addresses the process of governing in America, diagnoses issues, and offers solutions. In reading this book, this passage intrigued me:

Overwhelming numbers of Americans - three out of every four - believe that their government in Washington is broken...I am not sure many of them can explain precisely how the system got broken, which parts are not working, and why. The situation is one, rather, that they sense and intuitively understand.

I find this phenomenon in the Business Intelligence world as well. Many organizations have the desire to leverage reporting and analysis to improve decision-making, or have already implemented a program but sense something is “wrong”. Both types of organizations have issues with process - one doesn’t have one, and the other has parts (or all) that are not functioning properly.

At Baseline, we specialize in diagnosing and recommending effective processes for BI programs. However, this is only half the story. Recommendations are one thing - effective action in establishing or correcting process is quite another. It takes commitment, discipline, and persistence. It is difficult simply because it requires change in your entire organization, often by people who have established interests in continuing the status quo. It is important to show that an effective BI system can free people to perform the analysis that adds real value to the organization, and is worth the effort to change their ways.

Accomplishing this change usually requires executive-level commitment and enthusiasm to drive the concepts, techniques, and, yes, processes throughout the organization. A consulting firm can provide you with the tools - it’s up to you to have the will to start the program and drive the change.

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Stephen Putman has over 20 years experience supporting client/server and internet-based operations from small offices to major corporations.  He has extensive experience in a variety of front-end development tools, as well as relational database design and administration, and is extremely effective in project management and leadership roles.

Real-Time Data Quality Through MDM

By Bob Wall, Senior Consultant

I have found that one of the biggest challenges for data migration, data integration and data warehousing projects that I’ve worked on, is the requirement for clean data. Typically, one of a plethora of data quality/cleansing tools is deployed. The tool employs sophisticated heuristic, probabilistic, deterministic, phonetic, linguistic and empirical methods and algorithms to perform data quality analysis. For example, for customer data being integrated into a data warehouse, we want the tool to reconcile Easthartford, Hartford East, Hartford and East Hartford to the same physical address. The data quality process is usually run in a batch process, first for the initial load and then continually after that.

Today, operational MDM hubs present an even bigger challenge. We have to ensure synchronization across multiple source systems and all data must consistently be correct. The data quality checks must be applied at various stages within the master data lifecycle, and must support federated sharing across and between systems, databases and applications. In a sense operational MDM requires real-time data quality.

Digressing for a moment, I have also worked on projects that employed various search engine technologies. On one in particular, a client wanted to have an automated way to categorize structured and non-structured web data (emails, documents, images, etc.); search for certain conditions and do it in an automated fashion. We investigated some technology that used what was referred to as the semantic web technology, which incorporated advanced semantic and linguistic analysis with classification schemes (using Hyper Text Markup Language (HTML), eXtensible Markup Language (XML), Resource Description Framework (RDF), and Web Ontology Language (OWL)) to render web content machine-readable and make it capable of being searched in an automated fashion.

Software tools that support inline SOA data quality services combined with advanced semantic and linguistic analysis/machine learning capabilities are beginning to evolve. Microsoft’s purchase last year of Zoomix is a testimonial to the strategic value of these types of products. The convergence of data quality and semantic web technologies may provide operational MDM projects with the ability to automate ongoing classification, matching, and standardization of master data records. I think it is definitely worth keeping an eye on to see if it leads to real-time data quality capabilities embedded in MDM tools.

photo by Blude (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.

Triple Play Package for MDM

By Bob Wall, Senior Consultant

Several months ago I decided to upgrade my home internet connection to broadband and discovered that several of the carriers offered a bundled package that allowed me to not only get an upgrade for my internet service, but also for my telephone and television services at the same time. It would offer better speeds, consolidate my bills and most importantly save me money. This bundle is often referred to as a “triple play” deal. So recently I decided to upgrade to a triple play package and I have been extremely pleased with the services and the cost savings.

Baseline offers a similar set of services that we deliver to companies to help out with with their master data management strategy. It’s called the “MDM Masterplan” and it combines a set of MDM specific tasks and skills to deliver an overall MDM roadmap. This can save companies an inordinate amount of time and money, focusing them quickly on their objective and how to reach them. The service is its own type of  “Triple Play for MDM.”  Instead of an internet, telephone and television bundle, the service bundles three core MDM activities:  Business Scoping, Architecture & Technology Review, and Roadmap Development:

Business Scoping is analogous to the internet service in the home triple play package because it allows you to discover the company’s readiness and chart a path—kind of like a Google search!

Through review of business and IT documentation and interviews of key IT executives, MDM sponsors, key business and IT stakeholders, try to understand their concerns for MDM, opportunities for further efficiencies, the organization’s business priorities and challenges, and MDM business requirements.

Architecture & Technology Review is analogous to the telephone service in the home triple play package because the strength of the telephone service is the backbone architecture design and technology network of the service provider.

Through review of the “current state” technology development and processing environment, a gap versus the “desired state” environment, and  identification of the existing methods, practices, and functional capabilities available to support the business capabilities associated with MDM, come up with a blueprint for an MDM architecture and the required technology to support it.

Roadmap Development is analogous to the television service in the home triple play package because you can tune in and plan your future viewing.

Reconcile the business and technical findings to produce a moving forward MDM implementation plan that is based on the company strategy, business priorities, and technical activities necessary to deliver an MDM initiative in an iterative, business-driven approach. 

In summary, this “Triple Play for MDM” can assist a company in preparing for an MDM implementation and ensure that MDM is not only well-planned, but well-packaged and priced for success!

photo by rick (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.

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.