A Roadmap to Build Your “MVP” Data Governance Strategy

Master Data is Key to Data Governance

You know your organization needs a data governance program. Everyone does. But the reality is, there’s limited time, funds, and resources. Building a successful program can take years, and even then, companies are still working at it.

So today, we’re going to simplify. I'll share the minimum you need to do to succeed in the short term to establish your data governance policy.

I've created a proven step-by-step approach to building an agile, practical, and successful foundation for a data governance strategy, that can scale with your enterprise in 2019 and beyond. This approach is presented in detail in my whitepaper entitled The Data Governance Minimum Viable Product (MVP). I also discuss related topics in our podcast.

Listen to the Podcast

First, where did this MVP concept come from?

This approach is based on agile software methodologies, years of research, and practical experience with hundreds of enterprises around the world. It answers this pressing question surrounding data management today: “What are the things you, as an organization, need to do right now in order to build a foundation for data management that’s reliable so you can make better business decisions and stay compliant?” In short, the MVP is about focusing on these four elements: Structure, Quality, Relationships, and Change Management.

There’s urgency to finding a more reliable way to manage data for several reasons:

1. Companies are struggling to manage data by themselves—and are tackling too much at once. They find it overwhelming to figure out how to organize all their sales, marketing, finance, supplier, partner, and third-party data and connect it together—especially and understandably so, if they aren’t a data company. It’s a steep learning curve and takes lots of time before any results can be expected.
2. Poor data management is very expensive. According to IBM, $3 trillion a year is the cost of poor-quality data in the U.S. alone. On the flip side—clean, organized, and well-managed data is a competitive differentiator and opportunity.
3. Laws are changing quickly in response to user demands for increased privacy. These vary locally, regionally, and nationally—so global organizations must keep track of laws across all the areas in which they do business.

Why is “governance” of data necessary?

Your organization needs policies and procedures in place so your users can trust the data when they need it to make decisions.

For that to happen, a team needs to be responsible for making sure that the data is trustworthy, accurate, current, and complete. This cannot happen without a data governance program.

Many companies know this and accept that Master Data and a dedicated team will help their organization. However, the more difficult question to answer is how, and when will you get ROI? How do you measure the value of data when you don’t even know how much data you have?

Enter the “Governance Paradox”

The governance paradox comes into play when the sheer volume of the data is not yet possible to quantify, making it difficult to quantify the ROI opportunity of managing that data better. This blocks the program from being approved more easily, when in reality, the completion of the program would fix the issue and prove the ROI through clean, actionable, and relevant data.

I see this day in and day out, and as a Distinguished Architect focusing on Master Data, I get to work with some of the biggest Fortune 1000 companies across the globe. I can safely say that organizations would know the value of their data If they applied governance competencies to the data upfront.

Build a basic Data Governance strategy first

When advising companies on how to start building a Master Data program, I encounter teams who feel “stuck”— especially if they are on their second, third, or even fourth iteration of attempting to make a strategy work with their master data management software. They’re exhausted. Some can’t even generate a single view of their customer yet.

That’s why trimming the scope helps organizations immediately. Start with easy steps. It makes it approachable, manageable, and allows you to take practical steps to build out a governance program.

I’ve worked with many customers who invested tens and hundreds of thousands of dollars in systems, processes, and tools around Master Data—yet they haven’t developed a single definition of their customer. Instead of trying to master all your data, all your customer records, all your supplier records, and everything at once, keep your scope focused. This will drastically improve your chances of success.

Have plans to build a Data Governance program? Start by narrowing down the scope to make it more approachable.

Tackle one category to start—let’s say, customer data. We’ll walk you through how you can:

1. Define the structure and standards.
   
2. Improve the quality of the data.
   
3. Establish ownership hierarchies of the relationships involved.
   
4. Know how to monitor that data ongoing to get dynamic updates.

The next step is to download my whitepaper: The Data Governance Minimum Viable Product (MVP).