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Democratizing Data in Your Organization

Published May 1, 2017
Doug Rose
Author | Agility | Artificial Intelligence | Data Ethics

Democratizing data involves making it available to personnel throughout an organization and providing them with the tools and training needed to query and analyze that data. In this post, I discuss the potential benefits and drawbacks of data democratization and provide some general guidance for democratizing data.

Benefits of Data Democratization

  • Distributing data and business intelligence throughout an organization delivers the following benefits:
  • Having more people examine the data from different perspectives increases the organization’s knowledge through discovery and learning, leading to greater innovation.
  • Democratization is a self-service model, which removes some of the burden of analyzing data and producing reports from the data science or IT team, so they can focus on higher level tasks.
  • Enabling personnel to access data and analytics on-demand increases the pace of business. Personnel can ask and answer questions and make decisions on their own (when appropriate) without necessarily having to go through the data gatekeepers.
  • Everyone in the organization has the resources to make data-based decisions, which, at least theoretically, leads to better, faster decisions.

Potential Drawbacks of Data Democratization

Nearly every organization that democratizes its data properly reports that the benefits of doing so far outweigh any potential drawbacks. However, organizations do need to address the following concerns:

  • Increased risks to data security, privacy, and integrity. For example, storing employee records in a central data warehouse makes those records more susceptible to security breaches.
  • Misinterpretation of data or analytics by untrained personnel can lead to bad data-based decisions.
  • Duplication of effort across different teams may be more costly than having a central data science team.
  • With different teams performing their own analytics, an organization may end up with multiple versions of the truth, which can lead to diminished confidence in the analytics system.

Drivers of Democratization

Traditionally, the IT department has owned the data and was in charge of extracting meaning from it and presenting the information to executives and managers. The development of various technologies, tools, and techniques is driving the movement toward greater democratization of data:

  • Central storage, particularly cloud storage: Instead of having each department manage its own data, which results in the creation of data silos, all data is stored in a central data warehouse, so an organization has a “single source of truth.”
  • Business intelligence (BI) dashboards: BI dashboards facilitate the process of selecting, aggregating, and analyzing data, often displaying the results graphically in the form of tables, graphs, maps, and so on. These visualizations make the data easier to understand.
  • Enterprise agility: To remain competitive, organizations have an increasing need to achieve enterprise agility — the ability to quickly adapt to market changes and capitalize on emerging opportunities. Democratizing data increases enterprise agility by empowering teams at all levels across an organization.

Democratizing Data in Your Organization

Democratizing data is not a simple matter of providing everyone in the organization unfettered access to all of the organization’s data, especially if the organization stores sensitive data. To democratize data safely and effectively, consider the following guidelines:

  • Establish strong governance to protect privacy, security, and data integrity. Each person given access to the data and BI tools should have a username and password, so IT can assign an access level to each user. For example, human resource managers may be the only ones who have access to personnel records.
  • Train personnel on how to use the data and tools. Technology is no replacement for education and skills. Everyone using the information system should know how to use it and for what purposes. Preferably, any training will focus on applications relevant to the person’s position and job duties.
  • Encourage personnel to ask questions and use the system to answer them. Don’t assume that “If you build it, they will come,” to borrow a phrase from the movie Field of Dreams. Just because you place a new, powerful technology in the hands of users doesn’t mean they will embrace it. Make sure the C-level executives actively promote the information system. Celebrate any “wins” that can be attributed to the information system. Once people experience the value of data and BI for themselves, they’ll be hooked, but you need to grease the wheels to get them moving.
  • Shift the data science team’s responsibilities. When you democratize data, you’re distributing the data science team’s analytical burden throughout the organization. This frees up the team to explore data at a deeper level. However, the team should allocate some of that additional time to finding better tools, sharing them with other teams in the organization, and providing training on how to use them. In other words, the data science team should put some effort into empowering personnel across the organization to become better data scientists.

If your organization currently places the power of its data in the hands of a few, I hope this article encourages you to strongly consider the possibility of democratizing your organization’s data. By placing the power of data and analytics in the hands of the many, you’re likely to be surprised by the resulting increase in innovation and agility. Your organization will be much better equipped to adapt in a competitive landscape that’s constantly changing.

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