If you check out HubSpot's News and Trends blog, you'll notice a ton of interesting reports published by the HubSpot Research team. They have breakdowns, projections, detailed charts and graphs -- pretty much everything you're looking for in terms of customer data. And, with the number of customers HubSpot works with, it's impressive to see how they're able to consistently collect and analyze such large amounts of information.
But, have you ever wondered how they're able to do this?
One way they accomplish this is with data governance strategies. Data governance helps businesses manage their customer data and protect it from being lost or stolen. It also helps companies organize incoming information and distribute it to employees who could use it most.
In this post, let's go over what data governance is, and how you can develop a management framework to use with your own business.
What Is Data Governance?
Data governance is the steps an organization takes to secure, analyze, and manage its customer data. Companies use this management tactic as a way to safeguard their data collection process from inconsistency or inaccurate information. By following this framework, businesses obtain high-quality data at every point in the customer's journey.
Data governance outlines where you'll collect data, how you'll secure it, and who can distribute it. There are many ways to collect customer data and creating consistency in your process will make your data more reliable. You'll know that it's coming from trusted sources and is being shared with employees who can use that information most.
Why Businesses Need Data Governance
Businesses use data governance to get the most from their customer data. They can quickly review information and make informed decisions based on real-time metrics. This minimizes risk and helps your company capitalize on timely upselling and cross-selling opportunities.
Another crucial benefit of data governance is security. 92% of customers believe it's extremely important for a business to safeguard their information. By implementing a data governance framework, you can ensure your customer's data is safe from potential harm.
Now that you're familiar with data governance, the next step is to develop an effective management strategy. In the next section, we'll break down the steps for creating a data governance framework that you can implement at your business.
Data Governance Framework
If your team invests in data governance, it can provide your organization with continuous customer insights. The steps below outline what your business needs to do to create a successful data governance strategy.
1. Set a team goal.
The most important step in creating a data governance framework is defining its goal. After all, it's difficult to know which data is valuable if you don't have an end game in mind. Consider a goal that can produce long- and short-term results. While you certainly want to see quick returns, you also want to make sure your process will grow to scale as your business continues to succeed.
This is also a good time to determine your key metrics for how you'll measure success. It's hard to achieve your goals if you don't have a way to measure your progress. Outlining these details will ensure your team is on the same page and that everyone is working towards a common goal.
2. Adopt a data governance office.
Once your goals are set, you'll need employees to achieve them. While you could assign one or two people, the most effective way to implement data governance is with a complete team. Your team should include management, data stewards and liaisons, and any other company stakeholders involved in obtaining or securing data. These people will be considered your "data governance office" and will be in charge of making important managerial decisions.
3. Determine a data governance model.
The next step is to create a data governance model for your team to work off of. This model should describe the hierarchy for who can view and distribute different types of data. This ensures that sensitive data is placed in the hands of your most trusted employees and isn't shared without authorization. You can view one example of a data governance model below.
You should also describe your rules and regulations for data collection. Outline your standards for securing data as well as which channels you'll use to obtain it. This will create consistency in your data collection which will lead to more reliable and accurate takeaways.
4. Create a distribution process.
The last step in creating a data governance framework is determining how you'll distribute each type of data. As we mentioned before, some data is sensitive and shouldn't be shared throughout your organization. So, you need a reliable process in place to categorize it and highlight who it can be shared with. You should also define the channels that can be used for distribution as this will foster smoother and more consistent communication.
These steps should provide your business with a fundamental framework for data governance. But, if you really want to take it to the next level, take a look at the next section for some best practices you should use when managing your data.
Data Governance Best Practices
Data Governance isn't data management.
Encourage the team to organize independently.
Integrate data governance into every department.
Create risk milestones.
Consistently refine your data governance framework.
1. Data governance isn't data management.
It's important to remember that data governance differs from data management. Data management is the actions your business takes to execute your data governance framework. Data governance then acts as the decision-making function that has authority over data management actions.
For example, if your company uses a CRM to store customer data, that's a form of data management. Data governance would then outline how the information in your CRM should be used by your employees. If that information gets lost or mishandled, data governance would explain the next steps to take to rectify the situation.
2. Encourage the team to organize independently.
Your data governance office should consist of employees who know how to best manage your customer data. These people are capable of meeting on their own and determining the most ideal process for organizing information. As a business owner, it may be tempting to add to the decision-making, but it's important to give your team space when designing the framework. This will allow them to optimize the process and personalize it for your business's needs.
3. Integrate data governance into every department.
Once you have your framework in place, it should be integrated into every department at your business. This will ensure a consistent stream of data collection and will provide your marketing, sales, customer service, and product development teams with insights that will help them achieve goals.
For example, your data governance office should be informing your product management teams about consumer behaviors and product usage reports. This information should be readily available and influence how you design product updates. With data governance, customer insights are streamlined to ideal endpoints, improving productivity across your entire organization.
4. Create risk milestones.
When creating your data governance framework, it's important to consider your potential risks. Customer data is valuable and over time its security can be jeopardized as it's shared throughout your organization. Risk milestones highlight risks that can occur whenever data is shared or moved within your company. This helps your team avoid costly setbacks that can negatively influence customer relations.
5. Consistently refine your data governance framework.
Your data governance framework should be a consistent process for data collection and distribution. But, as your business grows and develops, it's important to adapt your strategy to account for organizational changes. If you don't update it, you may overlook customer data or accidentally leak sensitive information.
For more tips on managing your data, read this comprehensive guide to data governance.
Originally published Jul 3, 2019 8:00:00 AM, updated November 22 2019