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Your Data Is Useless If You Don't Have a Management Strategy

Data is mostly a raw material. You need a strategy to make something out of it.

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When speaking of the data revolution, bold, interactive dashboards with eye-opening insights come to mind. Behind those colorful charts is a solid data governance system. Data governance is the seemingly less-glamorous piece of business intelligence, but it’s the indispensable foundation of a modern data strategy.

Klaus Vedfelt | Getty Images

For definition’s sake, data governance is the management of the availability, usability, security and integrity of data in an organization. Without data governance, any business, small or large, will question the insights, quality and impact of any data set or insights derived from it.

In today’s data-driven business market, the reasons a data governance strategy is no longer simply an option, but a requirement, for business success include:

1. Tightening data regulations

2018 was the year of GDPR, and the impact of regulatory requirements around data will continue to grow more intensely in the future. Data governance is a safeguard against data compliance issues and penalties.

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2. Data volume is on the rise.

Data volume is increasing exponentially as more consumer data is captured with every web visit and as the new era of IoT unfolds. Not only is data being collected on our computers, tablets and mobile devices, it is also being saved by our thermostats, refrigerators and security systems. This mountain of data must be proactively monitored and managed.

3. Data democratization

Being data-driven isn’t a business buzzword anymore. Today, data-literacy is an expectation across most business roles. Most positions require some form of data analysis, and improvements in data management has made self-serve analytics a possibility. As more people across an organization access data, the need for data governance deepens.

4. The cost of poor data governance

Businesses unsure of whether they can afford the time or resources needed to implement data governance procedures should consider the cost of not doing it. The cost of poor data governance can be acute over time in terms of inefficiency, resource load and profit.

When data is not properly governed, it creates major inefficiency across departments and processes. Duplicate accounts become a drain on time and incorrect data in databases causes errors in reporting. The time spent correcting duplicate information and inaccurate data alone is money lost.

In the event that inaccurate data is not corrected, business decisions are at risk of being based on faulty information. Today, few key business initiatives happen without supporting data. Stakeholders rely more than ever on business intelligence for million dollar strategic choices. If the data underlying those reports is fragile, so is the company’s future success.

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5. Data governance drives ROI and customer satisfaction.

In contrast, when a data governance strategy is working well, a business’s future is bright. A healthy data governance program means data scientists are able to focus on what they’re good at -- insights. When data governance is solid, cross-functional teams can speak the same language and bring innovations to market faster. The entire organization benefits from data governance because time is saved and opportunities to make an impact through insights are amplified.

Perhaps most importantly, with proper data governance, the customer’s digital experience is improved, because customer data is accurate and centralized. The companies that create immersive, personalized experiences for customers in an increasingly digital world will be the ultimate winners.

Data governance starts with collaborative discovery.

Now that the benefits of data governance are clear, you might be wondering how exactly a business can begin to implement this important strategy. The key is in teamwork and collaboration. Management of data is a business-wide function.

Companies without a data governance program, or with a sub-optimal system, should consider a period of discovery. During this phase, key members from cross-functional teams should meet and discuss company data.

Results that should emerge from data governance meetings include the company’s data rules and standards, how those rules should be enforced and how the ongoing data governance should be managed.

Data democratization and data governance

At the outset, it may seem like data democratization is at odds with data governance. However, the opposite is true. When data governance standards are clearly outlined by a business, that clarity empowers teams to know exactly when to provide data access. Data administrators have much more autonomy to quickly provide viewing rights to cross-functional team members without waiting for decisions from additional stakeholders. Furthermore, tools create much more ease around data access with customizable permissions. Gone are the days of months-long permission hierarchy setup. Today’s data warehouse tools make the permissions process faster than ever.

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Data governance is a team effort.

Once a data governance strategy is defined and operating procedures are implemented, the work isn’t done. Data governance happens daily across the organization. Data rules and standards should be followed by anyone creating, managing and analyzing data.

Because data governance is such a holistic process, team members should be educated and engaged about the company’s governance policies. This education and engagement happens through consistency and conversation. Teams that are aligned with the ultimate vision of data governance, consumer protection and privacy, efficiency, and ROI will be the ones that thrive.

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