Getting Started with Data Governance

Data Governance is a big topic, right up there with regulatory compliance, data-based decision-making, and being a learning organization. For leadership, it sounds like an initiative, with committees, lots of meetings, and tons of paperwork. If an organization’s leaders don’t have a strong data background, they may find it hard to understand the value of investing time and money to improve data governance. 

For staff who work with data, it sounds like more work on their plate. They’re focused on the mission of the organization, and defining data and addressing data quality issues takes them away from their core work, unless their core work IS data. For data analysts and others at a nonprofit who primarily work with data, if they are already overloaded, it seems impossible to squeeze in the work of data governance. 

Because data is everywhere, all at once (movie link) thinking about it as a whole and how to manage it seems daunting. Especially when you have data coming in at the speed of light, and from various sources.

We won’t lie, it’s not effortless, but we want you to know that data governance is happening every day in your organization. You are already governing it, but less effectively than you could be. 

Data governance  doesn’t have to be top-down, initiated at the leadership level in a command and control manner with directives from above. The idea is to make organization-wide decisions and apply those with consistency. This requires support from the top, but decisions and actions related to data governance are carried out at all levels of the organization. 

Data governance is applying formality to processes that already exist. It may also be creating new processes and creating structure and accountability around those. The goal of data governance is to use data effectively across the organization. You can work towards that goal from anywhere within the organization, and with any type of data. 

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The goal of a data governance program is to have trustworthy data, to use data effectively across the organization, and to be compliant with your internal decisions and according to external regulators. 

To do this you must have:

• Clear policies and practices on data sharing that are consistent with security and privacy standards in your organization
• Well-defined data, and data defined in the same way across organizational units
• Appropriate access to data across the organization 

An Executive Director or CIO might tackle any part of the above, but a data analyst could as well. 

Having a data governance program in place can improve your decision-making as users can find the data they need and understand its quality and usefulness more quickly. It can also reduce the risk of fines, increase member confidence and avoid compliance issues. 

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Start Where You Are

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But where do you start? Start by looking at your organization. What are the existing norms in your organization? Are you more collaborative, top-down, crisis-oriented? Be aware of your culture, as it will impact your data governance. 

What are the norms in your organization around data? Is it valuable? Worth investing time and resources in? If data is not valuable to the organization, you won’t get any movement on improving how you deal with it. If you don’t use data, it may not matter if you can trust it. 

How does your organization currently define and understand data? Who makes those decisions and how? If one person makes all the decisions about data, they have to be on board with any changes. If you have stakeholders in every department, you will have to include all of them in your data governance process, and make sure to understand the value of data and the benefit that would accrue to each of them uniquely in improving data policies and practices. 

What about reporting relationships? Not how you create reports with your data, but how your people report to higher-ups. How does the reporting hierarchy in your organization impact the management and use of data? Who people report to will influence how they are held accountable for upholding data governance policies.

What skills do staff currently have regarding data? Who knows how to create data, change data, and use data? 

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Identify Your Needs

Next, think about your organizational needs. Ask around to find out how happy people are with current data practices. And more importantly, who is happy and who is not. For example, on a scale of 1-10, how confident are different staff in the accuracy of their reports? What is the impact of that level of confidence? Ask whether the most important KPIs in the organization are being tracked and, if so, how trustworthy that data is. If no one knows how much your members engage with your programming, that means those developing programs are operating in the dark, which could result in a drop in membership or simply running the wrong programs, for example. 

Some people may have a better understanding of what’s going on culturally in the organization but not much insight into the specifics of how the data is managed. Ask people what data works for them and why, and what isn’t working for them. You will likely discover that people with different data roles and in different departments have completely different takes on what’s working and what’s not. Some people may know that they struggle or spend too much time with their data and reporting but have no idea why.  All these views will come together to form a coherent picture of where you are and where you might want to start. 

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Keys to Success

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There are some common factors we’ve seen that help organizations succeed at improving their data governance practices. You might consider reviewing each of these for your organization and ranking your organization on a scale of 1-10, then asking colleagues to do the same. 

Top-Down Sponsorship (Board, ED, etc.)

• How much support do you have from the Board, the Executive Director, and the CFO to do data governance work? Will they allocate resources, and especially staff time, to improving the trustworthiness of the data? Is it valuable to them? You will need to make sure people have the time to do the work needed to achieve results, and you may need resources to work with consultants, to improve databases, or to learn and use new data tools. People need time to evaluate their current practices,  to collaborate, and to update or create policies. Senior leadership will need to back up the creators of the policies to make sure they are used consistently. 

Clear Vision - What’s Your Why?

• Does everyone agree on why you are investing resources to improve your data governance? If some in the organization are doing it to avoid fines for non-compliance, and others are doing it to save time, people may work at cross purposes. The data might be hard to find but compliant, or well categorized but vulnerable to sharing with people who shouldn’t have it. 

Stakeholder Engagement

• Are key people (whether that’s your best data analyst or your noisiest board member) committed to improving data governance? Getting the right people on board, and not just the people at the top or the bottom, will be important. Administrators, IT staff, the person who is the only one who knows your Salesforce build, the development person who looks at the fundraising reports every week, all of these people will have important insights and play important roles in your project. Don’t include only  those who decide about data, or only the people who use it. Data governance should make sense to everyone in your organization who interacts with data. 

Training

• How will you make sure that everyone understands and implements the new policies and procedures? Creating policies and procedures is nice, but if no one knows how to implement them they won’t be helpful. Make sure people know how to define and tag data, proper data entry policies, who is responsible for which data sets, and more. Staff turnover means training plans should be in place that can be reused as staff leave or change positions. 

Evolution Not Revolution

• Do people in your organization roll their eyes, thinking this is another “transformative” project? Many organizations think they can sweep through with a grand plan to “create” a data governance program. Data governance is like cleaning houses. You need a plan, the materials, the time, and a checklist (maybe), but it’s not a one and done. The people who are doing the data governance work are also doing their jobs, so identify which room in the house is dirtiest and start there, making it a little cleaner. Data governance is an ongoing process, and the goal is to make things a little better each time you make a change. Shoot for constant improvement (kaizen), not a clean sweep.

Good Communication

• In general, how does your organization do with communication within and across departments? Communication is key. A clear vision, engagement, trained data stewards, and a shared approach to improvement rather than upending all the current practices is great. But if no one knows about it, or people are confused about any of these, it will make it difficult to get people to carry out the work. 

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What’s a Data Governance Framework?

Data governance can be confusing, because the focus area is somewhat new, and there’s not an agreed on framework for it. 

A framework is just a way to think about all the components of data governance. It helps you identify the different elements and think about where each element falls on a spectrum between “needs work” to “on top of it.” It provides a structure for making decisions, defining a focus area, and formalizing how data will be dealt with across your organization. 

Data management involves the day-to-day execution of policies. Data governance is a step up from there, and involves the process of making those policies and decisions at the organizational level, policies that get carried out on a daily basis. A framework can help you define, agree to, and enforce data policies. It can also help you visualize a plan for improving data governance (and we all love visualizing information). 

Next month we’ll lay out the components of a data governance framework, including how to think about the beginning, middle and end of a data governance process, breaking it down into people, processes and technology. After that, we’ll present you with a framework, and explain what actions you can take to shore up any areas that need improvement. How, when, and to what extent you implement policies and practices is completely up to you. 

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Learning about data governance is the first step to having more trustworthy and reliable data and reporting. Make sure to sign up for our newsletter or keep an eye on our website for upcoming posts.