Master Data Management: Three Paths to Creating a Successful, Low-Risk Program

(ashatuvango/Shutterstock)

The biggest danger to a nascent master data management (MDM) program is starting with the wrong objectives, even though they can often sound quite right. While well-intentioned, unclear business objectives–such as creating better data quality, enabling better decision making, achieving a single version or the truth, or even a 360-degree view of the customer–may seem like a logical goal. But the reality is they can derail the entire MDM effort before it even begins.

While all the above objectives are essentially solid architectural concepts, none represent the actual and final goal of the business. To get to the root of the objective, organizations need to go beyond the “how” to understand the “what” and the “why” of what you really want the initiative to achieve.

As a result, it is no surprise that according to Gartner, the number one reason that an MDM program fails is the lack of a structured framework to qualify and quantify the value that data management creates for the organization. After leading or collaborating on many iterations of Gartner’s Magic Quadrant report over the past eight years and working with thousands of clients to initiate and manage their MDM programs, I’ve seen first-hand why these implementations never make it past the piloting or evaluation phases or fail outright during implementation.

To avoid MDM failure and reduce program risk, organizations should follow three important steps:

1.      Start with the Right Objectives and Engage Both Business and IT

The best practice here is to start with discrete and measurable business outcomes. A key test in this scenario is the ability to describe the outcomes of MDM in non-technical terms that the business can understand and champion. After all, if you can’t state your busin

Step one of your MDM journey is to bring together stakeholders from IT and business (iluistrator/Shutterstock)

ess objective in non-technical terms, then you probably have the wrong objective.

A technique I’ve found to be particularly helpful for organizations aspiring to implement MDM is to ask them to state their objectives without using the word “data.” Instead, start with business objectives that you want the MDM initiative to address such as:

• Increasing the customer on-boarding rate by XX% while reducing error rate to X%
• Reducing slack in new product introduction cycle by XX%
• Improving asset up-time by XX%

If the organization can’t do this, it’s a huge red flag, and time to stop and take stock to get to this level of detail. After all, this is the time to work through the real reason for the effort so they can truly justify the program. In my experience, this is where most enterprises stumble, but it’s a great method to get IT teams to see the challenges they’ll face maintaining momentum over the life of the MDM program. It is also helpful to consider business outcomes in distinct categories; those that make money vs. those that save money, and current but sub-optimal vs. net new business processes.

While most IT teams can save the company money by fixing current sub-optimal processes and use cases on their own, true digital transformation resides in an organization’s ability to make money with net new processes, and this requires full participation from the business in identifying, describing, and quantifying these outcomes. To further reduce risk, it’s best to address the questions and issues that the business will eventually ask, particularly when the stakeholders grow impatient waiting for what they perceive are the MDM deliverables. The key is to do this before any time, resources, and funding are spent in pursuit of managing data elements that provide no significant business value.

Step two of your MDM process is to identify teh business problems you want to solve (izvector/Shutterstock)

2. Find the “Why” Behind the Master Data Management Efforts

As with many business planning exercises, it’s often valuable to start with “why” — that is, the core reason pushing the organization to act. Perhaps it is to increase market share, improve terms with vendors, or improve cross- or up-selling opportunities. In any case, there should be a fundamental business reason behind an MDM, digital transformation or any data-related project.

Before embarking on the initiative, write down the business challenges and connect them to the “what” and “how” of the project. Failure to do so can make everyone overwhelmed and cause them to lose sight of the core purpose of the project. To avoid this, it’s critical for organizations to really demonstrate the value of an MDM program and get into the justification for it, i.e., can we drive new sources of revenue from the trusted data foundation created by our MDM program? Can we fix a broken process, that when repaired, eliminates redundancies that were costing X millions of dollars that go right back to our bottom line? It’s important to identify specific quick wins that prioritize business outcomes to show the value of the MDM program.

3. Align Objectives with a Comprehensive Roadmap

Beyond a typical “ROI study,” organizations need a comprehensive roadmap that begins with identifying your core business problem and includes a detailed plan on how to get there — including stakeholder engagement and gaining commitment along the way.

Defining business objectives on a comprehensive roadmap is the final step (Khvost/Shutterstock)

An effective Business Impact Roadmaps (BIR) helps identify specific quick wins that prioritize business outcomes to show the value of the MDM program. It also creates the data foundation that can drive many numbers of projects and opportunities to increase revenue and decrease costs. When designing the BIR, be sure to start with a compelling business case that:

• Clearly describes the business opportunity
• Helps prioritize initiatives and resources​
• Identifies key performance indicators
• Quantifies a projected return on investment​​​​

Completing this exercise empowers the business to think big but start small. By thoughtfully conducting a comprehensive business case, you and your stakeholders will understand the scale of the current business problem, what it will take to solve it as well as the total cost of ownership (TCO) and return on investment (ROI) expected from the implementation.

Master Data Management is a Journey, Not a One-Off Project

Tying the MDM implementation to real-world business problems is key to getting stakeholder engagement for the project, as it helps them understand that data management is a program, not a one-time, one-off project. Beyond the planning phase, working with a comprehensive roadmap can also help inform stakeholders what can be done within the program to create small, easy-to-achieve, quick wins. It also helps them see the value that an MDM program brings, so that you can focus on the next project in the program.

For example, many of the real-world problems listed above are inherently multi-domain issues in that they involve the relationships among customer, product and other data. So, if the business starts the effort by mastering their customer domain to better understand cross- and up-selling opportunities, celebrate that quick win. Then emphasize the new insights the business gleaned from this clean, trusted data before moving onto the product or other domains.

When embarking on an MDM journey, keep these tips in mind to avoid undue risk and ensure that all stakeholders are in synch. With the right objectives, the business can accurately convey the real and attainable benefits of the MDM program and prepare for what can come from it next.

About the author: Bill O’Kane is vice president and MDM strategist at Profisee, a pioneer in master data management (MDM) solutions. To learn more, visit the company’s website at www.profisee.com or follow the company on Twitter at @ProfiseeMDM.

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