Telecommunication companies do many things well. For instance, they’re great at bundling products and services, such as mobile devices, internet offerings, and so on.

But maybe you can empathize with me when I also say that one of my worst nightmares is having to call to fix an issue. It takes 30 minutes on the phone to change my address. Why is that? Because none of their systems talk to each other. So, each one has a different version of who Rob Evans is.

From a data perspective, they lack one version of the truth.

The result is the cardinal sin of business: poor customer service.

Most of us can’t get through the day without hearing about digital transformation and the massive disruption it’s causing. Much of that discussion centers around the critical need to become faster and more nimble in the ways our organizations orchestrate data, which is the new currency of business.

As companies try to keep pace with change, they understandably are thinking about data movement and integration. But the problem with a focus solely on that strategy is that it misses a key ingredient: the discovery, cataloging, and cleansing of the data they’re integrating.

That’s the essence of master data management (MDM).

And trusted master data must be at the heart of any digital transformation project.

We’ve been integrating systems for as long as there have been computers. With the explosion of data, technologies have emerged – including the integration platform as a service (iPaaS) category – to create seamless data connections throughout a digital ecosystem. Getting data from Point A to Point B is crucial. But it also doesn’t address the governance challenges involving the data itself. Without an emphasis on managing data quality, you’ll never be able to create the user-friendly integrated experiences that your customers expect today.

As organizations evolve, it’s unavoidable that data silos will occur. Sometimes, it’s due to mergers and acquisitions. Other times, it’s rapid, organic growth. Either way, businesses might not even be aware of all the rich data they possess because that information is dark data — neither accessible nor known.

Here’s one example I heard recently. A corporation had absorbed numerous companies through acquisitions. So, a customer might order a product that happened to be sitting in a nearby warehouse. Instead, the same item could be shipped from Asia if the customer used an old product number from one of the acquired companies. That resulted in wasted time, added cost, and, worst of all, a poor customer experience.

Here’s one more relatable, personal story. I receive multiple pieces of literature from my college alma mater that misspell my name. Some parts of the school get it right. Others don’t. Well, that doesn’t exactly make me feel like a valued part of the university community – or make me excited to donate to the school.

How do organizations think through these kinds of data challenges to create frictionless experiences that put smiles on customers’ faces?

I believe there’s a three-step framework that leads to creating a golden record of data. Only then will everyone be on the same page, and the business can become more efficient.

People

Perhaps nothing highlights the growing role of data more than the relatively new category of people who have “data” in their titles. Chief data officers. Data scientists. Data analytics managers. Data engineers.

These are the data stewards. They’re in charge of figuring out what is the master data, and who owns it. It’s not just a part-time job anymore. It’s a crucial role. The companies leading the digital charge today understand the importance of data. And they put people in a position to make sure it’s managed correctly.

Process

So much of what IT does for a business takes the form of “projects.” There’s a challenge. They find a solution. They implement the change. Then, it’s on to the next problem that needs fixing.

Master data management doesn’t work that way. It’s a journey, not a destination. You may reach a particular goal, but there’s always more road to travel. In a way, it’s similar to quality control. A corporation has to commit to the idea that data governance is an ongoing improvement process. You need a system for collecting, aggregating, consolidating, and distributing master data flexible enough to meet evolving needs and circumstances.

Of course, that’s easier said than done.

A well-known analyst firm has long noted that organizations tend to fail in their first attempts to master their data. That’s primarily due to a lack of clarity in the processes or lax enforcement of the guidelines. But the toll is high for businesses that don’t get it right. Poor data quality costs organizations an average of $12.9M per year, according to Gartner’s 2020 Data Quality Solution Magic Quadrant Survey. And that number is likely to rise as business environments become increasingly digitized and complex.

If you’re not consistent in your processes, you will merely revert to the same problems of siloed, inaccessible, and unsynchronized data.

Technology

The third leg of this stool is technology – like iPaaS. It enables organizations to bring together the people and processes to deliver better results for the business and solutions for their customers.

But as you think through your challenges to creating a single version of the truth, it’s essential to identify the technology that best supports the entire business. Ideally, an integration platform will do more than connect systems and synchronize data. It will serve as a bridge between IT and business users.

Data should never be “owned” solely by IT. Data management projects that succeed also have the involvement of subject matter experts in the business. That greater collaboration throughout the organization will result in more data-driven decision-making.

In today’s world, customers expect to be connected to what they want instantly. Integrating systems throughout the enterprise helps make that happen. But don’t overlook the need to ensure that everyone in the business is speaking the same language. How do we describe our products? What is a customer? What is the process for delivering on our promises?

That’s a single source of truth.

And that is the real value of master data management.

https://resources.boomi.com/resources/blog-posts/the-importance-of-master-data-management