by Will Bryant

Today’s Environment

Master data management (MDM) is at the heart of business intelligence, big data and information governance. Effective MDM provides an integrated, 360-degree view of the business by combining processes and tools to create an authoritative “master” source of core business information that can be shared across an organization as a strategic asset.

Most organizations have launched one or more MDM initiatives. But research by The Data Warehousing Institute shows that 44 percent of those surveyed approach MDM in silos. This defeats the main purpose of MDM: to break out of a siloed view by integrating and sharing data across the business. And according to Jane Thomson, executive director of EOH, 75 percent of enterprises lack an effective MDM strategy. For these and other reasons, many MDM efforts fail to provide the integrated view so key to business intelligence.

The good news is that the untapped potential of MDM is well within reach.

Point B’s Perspective

When an MDM effort falters, it takes a clear-eyed investigation to discover what’s impeding success. Point B has worked with clients across a wide range of industries to assess the issues and implement effective remediation plans. We often find two related issues:

  1. Who owns MDM? MDM often becomes the responsibility of IT by default, and vendors are eager to sell a software solution as the answer. Avoiding the perception of MDM as merely a technology solution is a key factor, but business ownership is essential.
  2. What it takes to succeed. Conventional wisdom holds that MDM tools and techniques are mature, and that any company can apply them successfully. However, gathering the tools is the easy part; building effective processes and creating a common understanding is 80 to 90 percent of the effort.

Know Your MDM Status.

Determining where an MDM effort has stalled is the first step in moving forward. Was it during the development of the strategy, business case or roadmap? Was it further on, during process or organizational design? Or did things look good until the actual implementation?

A U.S. retailer’s third attempt to launch an MDM initiative was mired in debate about which data to include, how to coordinate process and system changes—even how to make decisions. In this case, the technology had gotten ahead of the business processes and organization needed to support it.

At a $25 billion global financial company, where several false starts had generated little but PowerPoint proposals and consulting fees, the internal champions still couldn’t get funding for an MDM initiative that all agreed was “the right thing to do.” No compelling business case had been built to justify the effort.

Name the Problem.

Once it’s clear where an MDM effort has stalled, you can take a close look at what’s gone wrong. In our experience, some of the most common problems manifest as:

  • Declining IT delivery performance or stalled initiatives
  • Inconsistent execution and workarounds
  • Ineffective governance
  • Declining data quality
  • Falling back into old habits

For example, after rolling out two MDM for Customer and Location, a Fortune 100 retailer found it had stagnant or declining data quality performance metrics in both domains.

Find the Root Cause.

What’s causing the problem? We often lead internal cross-functional client teams of business, IT, data management and governance stakeholders to “peel back the layers” and identify the root cause. Some of the most common causes include:

  • Lack of a clear MDM strategy and roadmap
  • An inadequate or nonexistent business case
  • Differing definitions of core concepts and key terms
  • Imbalance between IT and business ownership
  • Misalignment of incentives and goals
  • Insufficient time or resources
  • Wrong skills or personalities
  • Excessive complexity or bureaucracy
  • Too gradual of a change

In the case of the retailer who had treated MDM as an IT initiative found that it needed to involve business stakeholders in decision making. Its early efforts had no standard for evaluating existing data or common understanding of how to define core master data. Even the decision-making process and timeline were poorly defined.

Remediate to Get Results.

Root cause analysis should provide the insight to create and execute an MDM remediation plan that works. Most successful MDM plans:

  • Promote business ownership
  • Run shorter projects to get value and learn quickly
  • Balance objectives with the resources available
  • Devote time to the foundation: definitions and analysis
  • Establish clear responsibilities and metrics
  • Ensure that repetition and reinforcement form habits
  • Prioritize an effective change process

The global financial company with the weak MDM proposal decided to focus initially on a tactical solution that would enhance the benefits of other high-priority initiatives. The increased benefits produced a strong ROI and business case for launching an MDM initiative. Once underway, other opportunities were identified and MDM became a fundamental part of how the business operates.

The Bottom Line

Master data management is the foundation for new insight and opportunities through big data, advanced analytics and information governance. But it takes more than technology to succeed. Just as most MDM problems are about people and processes, so are most MDM solutions.