Gaining better control over data quality and ensuring consistent data definitions: a goal shared by many organizations. But it’s also a challenge. After all, master data management is a large-scale, costly, and complex undertaking. How can your organization tackle this step by step? Martijn Muilwijk explains more.
Virtually every organization has been grappling with this for some time: the need for high data quality and data consistency. “You often see that companies therefore started out with a business intelligence solution as a first technical step, usually initiated by the ERP or Finance departments. They built on that foundation, taking shortcuts when it came to organization-wide definitions and managing them. It’s now clear that this is no longer enough,” says Martijn. “Especially now that organizations are dealing with enormous, growing volumes of data and better understand the benefits of data-driven operations, the urgency to be agile and future-proof is increasing. To achieve that, your foundation must first be solid. And that, just like AI, needs to be a topic discussed in the boardroom.”
To build that solid foundation, an approach and investment in master data management emerge as a solution—naturally, in conjunction with master data governance. However, the challenge lies in the scope and complexity of truly implementing MDM effectively and the time it takes to do so. There is often uncertainty about the structure and how to successfully bring MDM to fruition, as well as fears of significant costs.
“Organizations often see major obstacles ahead, causing them to either half-heartedly pursue MDM or not pursue it at all. But the cost of doing nothing— —is truly too high,” says Martijn. “If you do nothing, the quality and reliability of all data analyses and insights will quickly deteriorate. Consider, for example, a fundamental decision for a B2B organization: focusing on the right customers. Are you actually investing your scarce resources in the right customer set? Furthermore, everyone is currently trying to assess the value of ChatGPTs. But without reliable data, the likelihood that such an AI model will produce inaccurate results is much higher. Do you really want to base your decisions on that?”
According to Martijn, the key is to start small with a clear end goal in mind. “First, decide where you’re going to implement MDM. What you often see is that master data management quickly feels like a technical project. One pitfall is that it turns into an IT-only initiative. It’s a strategic topic that affects the entire organization,” Martijn explains. He advises placing functional ownership at least at the C-level, starting with a business unit. “For example, in the sales department or the logistics department. It depends on your company, its size, and your objectives. Not every organization is large enough to have its own Chief Data Officer as the mandate holder. IT must then play a supporting and facilitating role.”
Once ownership is clear, you can start in an area where rapid progress is possible. Martijn emphasizes the importance of communicating with C-level executives to identify and quantify acute pain points within the organization. “Quantify the impact, for example, on the cost side. Identify business and value cases that provide motivation to continue working with MDM. For instance, should the organization’s product information system be the primary source of data? Is the sales organization currently spending a lot of time and effort building a 360-degree customer view—the ‘golden record’? Then start there. It’s a matter of picking the low-hanging fruit to create momentum.”
Martijn recommends setting aside a timebox of a few weeks to take this first step. “Integrate this into your daily workflow and evaluate its value after two months. You’ll see that working data-driven has taken a step in the right direction.” As far as technology goes, he reassures us that you don’t even need to make a major investment right away. “You might be able to temporarily use an existing application as a foundation. But be aware that at some point during the journey, you’ll need to switch to a robust MDM solution, and that this transition will also cost money. In short: by thinking big and starting small, it’s perfectly possible to build a business case that demonstrates when each investment is justified.”
The key to success in the initial phase and beyond is agility. Martijn encourages organizations to invest in scalable technology and to understand that master data management is a long-term journey consisting of small steps. “What if the first step turns out to be more complicated than you thought, or you’re barely seeing any results? That’s sometimes part of the process—it’s no big deal. Master data management is a journey. Once you’ve started, it requires rhythm and steady progress toward the ultimate goal: a single, consistent, and reliable version of the definitions.”
Once you’re on your way, it’s crucial not to lose sight of the end user. “MDM must become an integral part of daily operations. You achieve this through integration with business users’ applications, with the benefits for the end user taking center stage. For example, if your marketer’s tools aren’t integrated with the MDM platform, you can be sure they’ll keep working the way they always have. So always involve the end user on the front lines,” says Martijn. “After all, the workplace is where you can turn data into real value.”
Does your organization also want to get started with Master Data Management to take your data quality to the next level? We understand that it can feel like a big undertaking, and we’d be happy to help you get started. That’s why we invite you to our “Master Data Management in a Day” workshop. In this workshop, we’ll show you what’s possible within your organization in the area of master data management and guide you in developing a solid business case for your MDM initiative. Together, we’ll define a team structure and roadmap that will enable your organization to take the next steps toward data maturity.