Data can be an incredibly powerful ally or a frustrating mess of outdated and incomplete information. Here are 4 strategies for fixing your organization’s data governance, writes, Chris Wilson, a partner of product innovation and customer service at Pearl.
Data might be one of your organization’s greatest assets. It can help streamline operations, drive innovation, identify prospects, and inform business decisions. But if that data is outdated, inaccurate, or incomplete, your greatest asset can quickly become your greatest liability — and lead to some dire data-driven decisions.
Inconsistent data ranks right up there with too many data sources as the leading cause of data quality issues. One surveyOpens a new window  had these two issues tied for the top spot, with 60% of respondents citing both as the most common data governance framework problems facing their organizations. Centralizing data to a single source is a tricky proposition, especially when departments become siloed and take ownership of their data.
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It also makes it difficult to keep data updated, accurate, and accessible — not to mention secure, which has also become a common data governance framework problem. Your organization will face constant new challenges and realities related to your data; by investing in a data governance framework, your organization is protecting its greatest asset for the long term.
Finding the Right Data Governance Framework
Naturally, a strong data governance framework needs to be designed specifically to fit the needs of a business. In most cases, however, large enterprise organizations reserve data governance for regulations and regulatory requirements. Data compliance is important, but companies need to protect the privacy and security of customer data. To enable more data-driven decisions, data governance should also include guidelines around data accuracy, accessibility, and aggregation.
As machine learning continues to evolve, systems can identify the data that needs to be protected as well as how it needs to be “served†based on regulatory requirements. The sheer amount of data now available has made machine learning technologies a near necessity. You cannot match the precision and speed that machine learning provides when it comes to optimizing, integrating, accessing, and securing data.
With the right policies in place, machine learning can identify precisely who within the organization can access information assets. From sales and marketing to legal and financial, you must manage and ensure the accessibility and security of your data daily. Not doing so puts you at regulatory as well as business risk — 32% of consumersOpens a new window  in one study reported they had switched companies or providers due to data security or data-sharing policies.
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Data Governance Best Practices
Building the right framework can be a challenge for many organizations. Just deciding where to start can leave even seasoned CIOs stumped, but there are a few areas you should focus on to ensure both your organization and its data are protected. Here are the top data governance best practices to follow:
1. Improve data accessibility. Data must be managed well if it’s to be usable, actionable, and accessible. Consider implementing a better way to access and use these insights. Doing so can help aggregate information from all data sources within an organization. This greatly improves accessibility for everyone who needs the data — especially marketing teams and C-level executives.
2. Establish data management protocols. As I’ve mentioned, data is your company’s greatest asset. It enhances business value and enables data-driven decisions. Despite this potential, many organizations fail to institute proper data management protocols to ensure data quality. It’s become such a significant problem that it’s now believed that poor data quality leads to an average of $15 million in business lossesOpens a new window  per year. Determine exactly what data will be available and how the analytics will drive decisions.
3. Update data regularly. While this should go without saying, you must put the proper guidelines in place to ensure your data is always current. Take a look around your organization, and you’ll probably see issues already. Marketing teams, for example, have always struggled to get salespeople to update contact information with any real consistency. As a result, you only update your data when team members have the time. A third-party provider might be the answer to your problems because it should come equipped with established policies for cleansing and appending data.
4. Institute data accessibility controls. Limiting who can access data — especially remotely — is big. After all, remote access is when security risks most often occur. Part of your data governance framework should include controls around access. In a larger organization, IT or risk management teams would be responsible for these policies. At the SMB level, those responsibilities fall to the IT team, president, or business owner. Regardless of who’s in charge, you’ll want to institute policies for where and when data can be accessed.
Keeping data secure, yet accessible, is the key to business success. Once you develop the right data governance framework, you remove the pressure and make it much easier to go about day-to-day operations — and improve your data-driven decision capabilities.