Understanding Collaborative Analytics and Its Importance for Data Democratization

Collecting and analyzing data to make critical decisions is how data and analytics leaders drive a business forward—collaboration being at the heart of this process. Leaders must introduce collaboration and empower business users to align with data analysts and engineers through the right BI (Business Intelligence) and analytics tools to democratize data and enable analytics across the organization.

In this blog, we will discuss why eliminating data silos and bringing teams together to harness the power of data can create synergy and better decision-making.

What is Collaborative Analytics?

Collaborative analytics is the process of bringing the analytics workflow together across departments, technologies, and domains. This helps to eliminate silos and reduce the time consuming back-and-forth process that occurs during decision making. Collaborative analytics ultimately bridges the gap between technical and non-technical analytics users and aligns the enterprise, enabling teams to work more efficiently together and the business to move as fast as its data.

Importance and Benefits of Collaborative Analytics

As organizations grow, decision-making becomes more complex and the ability to collaborate cross-functionally goes from a nice-to-have to a need. As per the 2021 Gartner analytics Consumerization-democratization Survey predicts, “55% of organizations are using hybrid (fusion team) as one of the most prevalent models for ABI.” “The traditional sharing function of analytics content is not sufficient to address two-way or multiway communication on the analytics content along with driving actions.”

Bringing collaboration into the analytics process shifts the decision-making from self-service oriented to community-oriented analytics. This enables cross-department collaboration and aligns goals, making them clear and easy to work towards. With this more collaborative approach in the workplace, employees are empowered to gain the most value from their roles ultimately using analytics to answer complex questions with ease and increasing overall data literacy across the organization.

Enabling D&A (Data & Analytics) teams to seamlessly collaborate with business users and participate in the analytics process can have a profound impact on decision-making. Just creating dashboards with visualizations as many companies do today, is not enough to maximize decision-making. Organizations can look ahead by including other applications within their workstream collaboration tools where business users already communicate and work together.

How Collaborative Analytics Tools Can Help

It is well known that better-connected data makes for better decision-making. However, business users often have difficulty extracting insights from data without the need for a data analyst or engineer with coding and technical skills to step in. This Business Intelligence (BI) paradigm creates a disconnect between business users and technical users which results in long wait times to generate insights and data silos within the organization.

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In order to combat this paradigm, organizations will need to invest in BI tools that provide collaboration opportunities between teams and self-serve analytics to make decision-making faster. This will reduce time to insights—allowing analysts and engineers to focus more on strategic projects to drive the business forward.

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According to the latest Gartner® report “Innovation Insight: Analytics Collaboration” “a capability that helps teams communicate to converge upon new insights and helps drive faster decision-making and action by combining diverse perspectives.”

Easier Collaboration Between D&A, Other Departments, and Individuals

While there are new collaboration features available within analytics tools such as personalized sharing, commenting, and version control, there’s still a challenge when it comes to enabling different groups or departments to seamlessly and efficiently deliver analytics. Some of these issues have workarounds such as integration with GitHub so developers can continually manage and create custom analytics solutions to stay agile and improve efficiency. This is more applicable to technical users, leaving much to be desired for business users as they must rely on the engineers and analysts if they run into any issues.

D&A leaders within organizations should encourage community building where individuals with different levels of experience can collaborate to scale analytics efforts. In a 2021 Gartner Analytics Consumerization-Democratization Survey, “Of all the participants, 22% measured and 18% achieved diversity, equity and inclusion outcomes related to the consumerization and democratization of analytics in their organization.”

More Efficient Analysis

Decision-makers are essential to every business, however, the analysis process could be improved and made more efficient. While business users tend to be passive users within a data analytics tool, it does not mean they should not be able to answer their own questions. The less back and forth between departments and D&A users the faster the business can make decisions. It can be difficult for teams to wait for answers from D&A, especially if there are multiple requests from different departments. Sometimes teams have to wait days or weeks before they can make a decision but by then the data could be stale.

Analytics tools that enable business users to easily collaborate with other teams can make a big difference in saving time and reducing the amount of ad hoc requests for D&A users. With organizations moving to the cloud and modernizing their data stacks, it’s more important than ever to find a tool that enables self-service analytics and collaboration while also democratizing data. With low and no code analytics platforms and technology advancements, more and more business users are able to do more with data.

Ways to Improve Collaboration Efforts

• Leveraging existing collaboration features within current analytics platforms.
• Integrating analytics tools and digital workplace applications.
• Create collaborative workflows in A&BI tools by using communications platforms such as Slack and Teams.
• Installing verified third-party plugins to increase the capabilities of current analytics tools.

Overall, enabling teams to collaborate can positively impact the business by increasing productivity, reducing time to insights, and helping data-driven decisions across the organization—without having to make disruptive changes to their daily workflows or adopt new analytics software.

As the data analytics industry continues to grow and evolve, we will continue to see an explosion in collaborative features in existing and new analytics tools. Businesses should be forward-thinking in democratizing data, removing silos, and allowing users to answer questions themselves.

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Gartner, Innovation Insight: Analytics Collaboration, Julian Sun, David Pidsley, 2 September 2022

Gartner is a registered trademark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved

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