In the digital age, the success, growth, and maximization of opportunities of an organization depend on insights gained from data. Analytics and business intelligence (ABI) tools enable organizations to drive greater meaning from their data to protect revenue streams, minimize risk, adapt to rapidly changing business environments, and better serve their customers. 

In many cases, however, only specially trained, highly skilled IT professionals and data analysts have access to these tools and the data that fuels them. By restricting data to these elite few, organizations are doing themselves a disservice. With the right leadership, education, and tools, nontechnical users in departments such as sales, marketing, and business analysis, as well as executive teams can also uncover brilliant opportunities for their company. In a data democracy, data is of the people, by the people, and for the people. 

What Is Data Democratization?

Data democratization is the process by which data is made accessible to all employees in an organization, rather than only to a team of specially trained data scientists. It provides everyone in the organization with the opportunity to “own” their role’s relevant data, analyzing trends and opportunities, enabling faster decision-making, and optimizing outcomes without waiting for IT teams with limited bandwidth to process queries and pull reports. In short, data democratization allows nontechnical users to avoid depending on other teams for data-driven insights. 

Data democratization can also significantly improve the customer experience – an essential component to the success of an organization. For example, marketing departments can analyze the success of past strategies to provide tailor-made offers and marketing campaigns to attract customers, improving sales and overall revenue. Product designers and customer support teams can correlate customer feedback data in order to improve their products, services, and interactions with customers.

Other benefits of data democratization include:

• Increased collaboration between teams
• A strong sense of ownership and empowerment for employees
• Greater productivity and more efficient workflows
• More accurate KPIs and goals, with more buy-in from stakeholders
• Increased trust and confidence in the data and the intelligence it fuels

Best Practices in a Data Democracy

Data democratization can be part of an organization’s larger digital modernization strategy, but it’s also a worthwhile goal for those just embarking on digital initiatives. Data democratization can lay the foundation for other, broader, loftier ambitions.

Taking data that was only in the hands of a few and giving it to the hands of many can seem overwhelming, but by taking strategic incremental steps and following a set of best practices, it’s completely attainable for organizations of any size. The following list can help ensure your organization (and employees) reap the many benefits of data democratization.

1. Start by establishing a culture of data literacy. Data literacy is the ability to gather, read, analyze, and extract insights from data. Fostering data literacy in an organization motivates and empowers all employees to incorporate data analytics into their day-to-day operations, using the extracted information to make decisions that foster the success of their initiatives. That empowerment is an essential ingredient in a data democracy. 

Further, Data literacy should be taught top-down, meaning leaders must talk to their teams about the value of their organization’s data – why it exists, where it comes from, and how it’s used.

2. Embrace self-service analytics tools. Providing access to data is not enough for a nontechnical employee to develop game-changing insights. You must ensure the data is easy to find, retrieve, comprehend, and analyze. Self-service ABI software helps display data in readable, user-friendly formats, which helps the end user find patterns, trends, and outliers. 

Further, these applications often have robust data visualization tools and drag-and-drop modules that allow for nontechnical users to manipulate and “play” with data, making those patterns and trends evermore discernable (and visually pleasing to boot). Self-service ABI tools enable decision-makers, and those that support them, to devise market strategies that help organizations stay a step ahead of the competition.

3. Company-wide training and education. Although ABI tools get more user-friendly with every release, very few employees can jump in and teach themselves how to work proficiently within them. Organizations must provide comprehensive training to their employees to guarantee that new users will be comfortable with using these tools. With encouragement and opportunities to practice, that comfort will turn into confidence, and you’ll soon have employees making empowered, informed, data-driven decisions.

It’s not just about the tools though. Training end users in the core concepts of Data Management will increase their efficiency, accuracy, and confidence. With data democratization, users have more freedom – but they also have more responsibility. Knowing how the data is entered, processed, managed, and stored helps to ensure strategic, thoughtful work as well as a reduction in mistakes.

Consider creating a user manual containing best practices, policies, and procedures for business intelligence tools to help your organization and employees understand the available resources, where to find them, and how to use them. Not only will a user manual guarantee that everyone is following the same protocols, it can also promote independent learning (another confidence builder).

4. Implement user permissions and create policies for data accessibility. As we’ve established, a successful data democratization model means that data must be accessible to everyone in an organization. When widening access to other teams, however, you must create and deploy policies to ensure the continued credibility and quality of data. Policies such as the authentication, authorization, and documentation for modifying or erasing data will improve the quality and impact of the insights derived by nontechnical users.

Instituting different access levels of user permissions based on the needs, roles, and skill levels of individual users ensures that the right people access and comprehend the right data. It’s important to make sure that users access data that is relevant to their department and position. Not only does this promote credibility among end users, but it limits unwanted manipulation. 

5. Ensure high-quality data. Maintaining data quality plays a vital role in a company’s growth. There’s an adage that business intelligence is only as good as the quality of data informing it. The same is true for a data democracy – organizations will see the biggest benefit when their employees are working with high-quality data. Insights extracted from flawed data will lead to flawed decisions. Data that is stale, inaccurate, or incomplete can have consequences that not only negatively affect business decisions, but also undermine the trustworthiness of the data analysis and the confidence of the nontechnical users in their own work. 

Create rigorous standards to evaluate data for the five main criteria of quality: completeness, accuracy, consistency, timeliness, and integrity. Assign tasks like data formatting, data cleaning, and processing unstructured data to non-technical employees. If you educate your nontechnical users about data quality management, they can act as a safety net for your existing quality procedures, spotting inconsistencies and errors and raising the alarm (or better yet, fixing it themselves). 

Data is everywhere and it impacts every aspect of business. It makes sense that people from roles that haven’t historically interacted with data would begin to do so. In a data democracy, anyone can (and should!) access, interpret, and act on the intelligence they glean from their role’s relevant data. When fueled by data, even little decisions and insights can impact your organization in big ways.

After all, according to Bernard Marr, author of “Big Data in Practice,” “Data democratization is an evolution where each small win, when non-technical users gain insight because of accessing the data, adds up to ultimately prove the merits of data democratization.”