For decades, access to Business Intelligence (BI) solutions was reserved for data scientists. But as global business becomes more unpredictable and competitive, knowledge workers outside the data field need greater access to insights from BI and advanced analytics to compete. Gartner predicts that analytics adoption will increase from 35% to 50% by 2023, driven by role-specific analytics for a wide variety of users.

 

Without a doubt, business decisions driven by data improve business performance; “the data itself is clear on this,” as Harvard Business Review (HBR) describes. Logically then, if a wider variety of business users have access to data-driven insights, they can drive business value in each of their unique roles.

 

Indeed, Gartner also predicts that the world’s most competitive companies will outperform their peers based on their analytics; and by 2023, “60% of organizations will… build business applications infused with analytics that connect insights to actions.” Here we explore how democratizing data access followed by a strategic, iterative approach to organizational adoption can yield these competitive results.

 

 

Transforming Decision Making in Your Organization

 

Accelerating access to insights from analytics is made possible by “data democratization”: the process of giving any number of business users access to analytics tools in unique capacities which they understand and which help them in making role-specific decisions. As we will find, transforming an organization in this way requires substantial changes to company culture, technology, and strategic planning.

 

Why Democratize?

 

Historically, restricting analytics to highly technical data scientists had distinct advantages. These skilled professionals were trained to understand legacy analytics tools; they alone could interpret Big Data and deliver insights directly to business users in formats those users could understand. Limiting data access provided advantages in terms of governance as well, where organizations rarely risked giving the wrong person access to sensitive data.

 

But there are even more advantages to democratizing data access—especially as analytics tools become more robust, sophisticated, and accessible to non-technical users. “Data science programs that focus on professional data scientists ignore the vast majority of people and business opportunities,” HBR observed in March 2021. “Organizations are loaded with… data-driven decisions that can be… made by small teams of knowledge workers, middle managers, and partners using small amounts of data.”

 

A Cultural Revolution

 

There are common misconceptions to how democratization succeeds, the most common of which his that it begins with technology. But technology is only complementary to an iterative, strategic approach to transforming organizational culture.

 

“Creating a data-democratized organization isn’t about allowing everyone to see and do everything from day one,” as Forbes describes. In fact, data leaders are right to limit analytics access to only data scientists and few business users—those aligned with solving a specific, early use case.

 

It’s through early successes; a proactive, supportive environment with dedicated resources that promote data literacy; and carefully aligned digital tools that empower business users (rather than impose analytics upon them) that data leaders can foster a culture of analytics success.

 

 

5 Steps to Realizing your Analytics Transformation

 

Through experience, careful review, and third-party research, the analytics experts at Uvation have identified five universal steps organizations in any industry can take to build their own internal culture of data-driven decision making. Consider these steps as you look to adopt leading analytics tools and expand analytics access to your variety of business users—including your executives.

 

1. Start with decisions that yield quick and powerful results.

 

Upon securing the right analytics technologies, start by engaging a single, applicable problem that has a high potential for yielding business value. Ensure your data scientists can empower business users responsible for that particular challenge with data literacy training and analytics access.

 

Encourage these teams to “work the problem” until they yield the desired results, achieving a deep understanding of the opportunities and challenges future use cases may present. Then, evangelize the success of that initiative as you share your democratization agenda with other business groups.

 

2. Build a culture that encourages data literacy.

 

“Data and analytics leaders must leverage the collective intelligence of the organization to compose effective and augmented analytics solutions,” as Gartner describes. But extending analytics access to the breadth of business users requires two things: (1) their willingness to adopt analytics as part of their existing workflows; and (2) their ability to use analytics and understand data-driven insights once they are adopted.

 

Using a top-down approach, prepare department heads, managers, and team leaders with supportive resources for training workers under their leadership. In partnership with your analytics technology provider, encourage data leaders and data scientists to develop educational programs that will help business users understand how to interpret data in the context of their roles.

 

3. Empower business users with analytics tools that are right for them.

 

As Forbes describes, “Creating a more data-literate organization usually requires the implementation of modern data architecture in the form of self-serve business intelligence (BI) dashboards and tools.” Indeed, self-service is essential for advanced analytics to take hold across the organization. Analytics tools that augment business users’ existing workflows in helpful ways rather than attempt to replace them are key to this success.

 

But while each individual worker needs roles-based access to analytics—that is, an interface that accommodates that worker based on that worker’s unique responsibilities—all users should nonetheless have a shared view of data: a universal access to a “single version of the truth,” albeit through differing interfaces. Modern analytics prevents data silos from forming by making this possible as well.

 

4. Optimize data governance for a democratized analytics environment.

 

As suggested, modern analytics tools can optimize data governance, even with the complexity of democratization. Data governance leaders can use a combination of purpose-built manual tools and automation to mitigate risks even as they empower individual users with the “just right” among of data for each particular role. In this way, business leaders can continue to broaden data access without risking the exposure of sensitive data to the wrong parties.

 

5. Strategically scale analytics to other parts of the organization.

 

Although businesses are best served with broad access to analytics across their organizations, they still must take a strategic, iterative approach to scaling—or risk the cultural dimension of their analytics goals failing. Creating a formal coalition for analytics growth can ensure organizations avoid individual pitfalls from worsening and jeopardizing that transformation (e.g., individual business groups “holding out” against analytics adoption).

 

Gartner predicts that by 2024, 75% of organizations will have their own centers of excellence for centralized data and analytics to support such initiatives and prevent enterprise failure. In time, your organization’s data culture can reach near or complete universality, with analytics access on a steady course of ongoing optimization and success.

 

 

Aligning with Individuals for Enterprise Analytics Success

 

The analysts at Harvard Business Review often ask business leaders a simple question: “Which would you rather have: a newly-minted PhD data scientist or 20 people who can conduct basic analyses in their current jobs?” nearly all will choose the latter. Nonetheless, organization leaders must adopt the right analytics tools to succeed—those that will seamlessly augment business users’ existing workflows with insights that make daily tasks easier, not the other way around.

 

Learn More About Analytics & Big Data with Uvation

 

Uvation can help you identify the analytics solution that is right for your business and analytics users, as well as your business growth. We are a strategic partner as you scale and realize ongoing analytics success as well. Visit our Analytics & Big Data service page to learn more, or start a conversation about analytics options today.