Click to learn more about author Bruck Assefa.

Throughout my years in this industry, I’ve had the pleasure of educating organizations about the in’s and out’s of Master Data Management (MDM) solutions. In my discussions about the industry, use cases and technologies, a few things stood out to me as regular misconceptions and potential pitfalls. Most decision-makers aren’t fully aware of what MDM is and isn’t, which prompted me to share this two-part article on the top 10 myths about MDM with the goal to educate decision-makers in their next steps of exploring MDM solutions.

Myth 1. MDM is an IT problem

Fact: Master Data Management fundamentally is a business problem and needs to be implemented with a clear business objective in mind. Most organizations see all the symptoms of poor Master Data in their critical business processes whether it’s in the form of delayed product launches, high supply chain costs, frequent customer complaints or hefty regulatory penalties. It often takes peeling multiple layers of the onion to realize that a lack of reliable Master Data is usually at the core of the problem.

It is this problem that an MDM solution ultimately aims to address by enforcing the discipline of aggregating, cleansing, enriching, validating and syndicating Master Data with the goal to improve critical business processes. This means the success of an MDM initiative needs to be measured by tangible improvements in business process outcomes. Depending on the drivers of the MDM implementation, this could mean reduction in product launch cycle time, increased sales, lower procurement spend or more accurate financial forecasts.

This does not mean IT does not have a role in an MDM initiative. In fact, it’s the opposite. The IT organization needs to play a critical role as a key enabler of a Master Data initiative through the deployment, upgrade and support of technologies that deliver business value in accordance with the goals of the organization.

Myth 2. MDM is a large enterprise problem

Fact: I recently presented on the theme of democratizing MDM to a group of executives at the Mid-Market CIO Conference in Savannah, GA – all representing organizations under $2 billion in annual turnover. What was clear was that most of the typical business process challenges related to Master Data were in fact present in small to mid-sized companies. They also have significant issues with Master Data lurking in siloed systems and inefficient manual processes causing significant data quality issues in their organizations.

Furthermore, industry standards and regulatory requirements, such as the FDA’s Unique Device Identifier (UDI) in healthcare, place the same demands on them to share reliable data to regulatory agencies and trading partners. The question to small and mid-sized companies is not necessarily that they have an MDM problem but whether the problem is significant enough to warrant an MDM initiative at a cost justifiable to them.

Myth 3. MDM is costly

Fact: This myth often goes hand in hand with the one that says it’s an enterprise only problem. There has been a long-standing idea that organizations must have deep pockets to afford MDM initiatives and those with deep pockets are large organizations. The reality is MDM software and related implementation costs are nowhere close to what they used to be five or ten years ago.  There are several factors for this.  One factor is as the MDM category matures, competition between vendors has driven down the selling price.

The second factor is that hosted deployment models whether private or public have turned MDM software into an operating expense as opposed to a capital expense and have eliminated the need for organizations to pay separately for hardware, support and maintenance. Another key factor is that there are new players in the MDM market with a focus to democratize the adoption of MDM applications by reducing the cost of sale, deployment, configuration, support and upgrade with the objective of transferring cost savings to their customers.  This ultimately means MDM solutions are increasingly becoming accessible to organizations including small and mid-sized companies at a lower cost than before.

Myth 4. We don’t need MDM because we only have one ERP

Fact: Admittedly the need of an MDM solution is much clearer when organizations have multiple ERP applications where Master Data is scattered and needs to be consolidated into a single system. However, looking at MDM solutions only through the perspective of addressing a data fragmentation problem is a narrow view that hampers an organization’s ability to maximize business value from an MDM application.

The reality is most ERP systems do not have the required capabilities to support best-practice Master Data Management processes. They often lack the flexibility to easily add attributes to support enterprise level requirements without involving the IT organization. They also lack Data Governance capabilities including Data Security, robust business rule validations and audit trail. Data maintenance is also a challenge due to lack of configurable workflows to facilitate cross-division collaboration on data enrichment, review and approval.

All of these issues can be addressed by an MDM solution. Extensibility of attributes, business rule validations, data security, flexible workflows and audit trail are just a subset of MDM capabilities that can tremendously improve the quality of Master Data – even in a single ERP application. With a solid MDM foundation, organizations can also better scale from a single ERP application leveraging clean Master Data to multiple business applications throughout the enterprise.

Myth 5. We don’t need MDM because we just cleaned our data for ERP migration

Fact: It is not uncommon for organizations to perform a one-time clean-up of their Master Data driven by an ERP migration or consolidation project. While cleaning up the data is itself an important activity, the mistake organizations often make is not putting in place the Master Data Management processes and on-going governance to keep the data clean. Master Data Management ensures that there is accountability in the ownership of Master Data and provides the Data Quality and Data Governance capabilities to ensure Master Data is validated, standardized and de-duplicated as part of the day-to-day maintenance activity.

A data clean-up exercise that is done as part of ERP migration forces organizations to have the hard conversations about profiling the quality of their data and getting cross-divisional alignment to establish the level of ‘clean’ data required to run their business processes. An MDM solution is where that alignment on ‘clean’ data is continuously enforced through streamlined Data Management, Data Quality, Data Governance and Data Stewardship processes. Without it, another costly data clean-up exercise is bound to happen shortly after the last one.

Stay tuned for Part II.