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In order for analytics to deliver meaningful value to your enterprise, you need to know that you’re working with quality data, and ensuring that quality hinges on the development of a data governance framework.

Without quality data — data that’s easily accessible, consistent, trusted, and relevant to business goals — your enterprise will not only miss opportunities for advancements but could also waste time and resources addressing quality issues haphazardly.

The 2019 Global Data Transformation Survey by McKinsey & Company stated that on average, 30% of participating organizations’ time was spent on tasks involving poor data quality or availability, which ultimately did not provide business value.

As a result, data governance has recently risen to the forefront of many data strategy leaders’ minds as they push for data cultural transformations within their enterprises.

Good governance should be more than just a collection of policies. How do you design a framework that is valuable, sustainable, and scalable?

Here’s what you should keep in mind as you embark on this journey.


What do you hope to gain through your data governance framework?

You’ve determined your enterprise is in need of a governance framework to ensure the effectiveness of your data and mitigate potential risks — but what do you want that framework to achieve?

Much like your overarching data strategy, it’s crucial to connect your governance framework to a key business goal, mainly increased revenue, decreased cost or complexity, or risk reduction. Aligning your framework to one or more of these goals will allow you to assign KPIs to your program and will increase the likelihood of garnering executive buy-in.

Ask yourself, should you focus on data standardization, or is the enterprise creating a new marketing strategy that will require you to prioritize solid customer information? Perhaps, your enterprise is already facing a significant hurdle or risk related to poor data quality. Engage your key stakeholders early on to determine these needs.

Curt McAdams, Senior Manager of Operational Data Governance at Beacon Technologies, spoke on the importance of identifying your business needs when building data governance during a 2021 Enterprise Data Management Council.

“We’re trying really to get the organization to take accountability for the data they use, wherever that ends up being so that we get business value — nothing we do in data should be done without business value behind it,” Curt said. “It’s really how you fit within what the company needs, whether it’s finding opportunities or mitigating risk.”

Once you’ve identified your objectives — which will likely shift over time — you can then determine how to proceed and what form of governance framework is most appropriate for your organization.


Who will support your governance framework?

You can’t implement an effective governance framework without key pillars of internal support.

A governance council and corresponding data stewards will serve as the underpinning behind the policies you’ll set. Together the council will help set responsibilities, definitions, and guidelines around data.

Morgan Templar, the author of “Get Governed: Building World Class Data Governance Programs,” said the role of this committee is to set the overall governance strategy, hold the organization accountable, and champion the work of data stewards who will serve as the connection between the practices you set and its adoption.

The structure and sophistication of your governance council will depend on a variety of factors, including the industry, the nature of your enterprise’s data, or the required legal regulations.

You may end up selecting a top-down model, where your council works with data owners to set processes and definitions, or a bottom-up approach, or agile data governance, where users pass knowledge up to the council.

According to McKinsey & Company, a governance structure includes three components: a Data Management Office led by a CDO, a data governance council, and data stewards from each business unit.

Regardless of the structure, the council needs to represent the entire organization; members should stem from core business units such as finance, human resources, marketing, and sales.

Where do you find these council members and data stewards? Michele Koch, Senior Director of Enterprise Data Intelligence at Navient suggests that you “follow the breadcrumb trail.”

Michele helped build a governance framework at Navient and found stewards by asking members of the enterprise who they turn to when they have data-related questions. She said these individuals should not only be passionate about data but should also be strong communicators, as they’ll act as a conduit between governance and each line of business.

“If they’re not good at getting the word out or involving other people, that communication path can break down,” Michele advised.

As you move through this process, it’s helpful to set clear guidelines and expectations for each role in your governance program, and responsibilities should be easily transferable as your enterprise grows. Don’t forget to put these role definitions and all processes in writing, which Michele said is a critical step.


Where can you find data governance resources?

In this ever-evolving industry of data and analytics, it’s increasingly useful to leverage educational resources to help guide your data strategy.

There are a number of resources dedicated to data governance, including The Data Governance Institute, The Data Management Association (DAMA), and The Business Application Research Center, to name a few.

Additionally, it can be beneficial to hear lessons learned from those who have already implemented successful governance programs at their organizations. You can connect with these leaders by joining data-specific communities such as the Data Board, which frequently hosts conversations on data governance.

Interested in learning more?

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