How Analytics Franchises Drive Data-Driven Transformation

In a world flooded with data, it’s easy to feel overwhelmed. Every business wants to “be data-driven,” but too often, their efforts stall in dashboards that no one uses, siloed data lakes, or governance models that can’t keep up. 

Gartner proposes a powerful solution: the analytics franchise. Just like a business franchise brings a trusted brand to local markets, an analytics franchise helps organizations scale data insights across departments—without losing consistency or control.

In this essay, we’ll unpack the key takeaways from Gartner’s 2025 presentation on analytics franchises and offer clear steps you can take to drive adoption, empower teams, and maximize the value of your analytics investment.

Why analytics? Why franchises?

Analytics is more than number crunching. It's the process of applying scrutiny and saliency to make sense of overwhelming volumes of information. It allows organizations to create understanding and insight, which are essential in a digital world that produces more noise than signal.

And why the franchise model? Because it empowers decentralized teams with the consistency of a global standard. A franchise doesn't just replicate tools—it transfers values, practices, and expectations. In analytics, this means bringing scalable, repeatable insights to every corner of your business, from HR to supply chain.

The evolution of self-service analytics

To understand the need for analytics franchises, it's helpful to trace the evolution of self-service analytics.

1. The centralized era (2001–2011)

During this period, data lived in on-premises warehouses, tightly controlled by IT. Reports were delivered through business intelligence platforms with predefined dashboards and OLAP cubes. The architecture was structured and centralized, which ensured quality—but lacked agility.

2. The decentralized era (2011–2021)

Then came the rise of self-service tools like Tableau and Power BI. Suddenly, business users could load flat files, blend datasets, and build visual dashboards on their own. While empowering, this approach became highly manual and created islands of insight without governance or shared best practices.

What do these two approaches fail to realize? As Gartner puts it, we didn’t realize that self-service analytics is a team sport.

The ongoing tug of war: Control vs. freedom

Most organizations today are stuck in a familiar debate: should we centralize data for control and consistency, or decentralize for speed and autonomy?

Gartner argues that this is a false choice. The right solution is a balanced model—one that delivers both structure and flexibility. You need:

• Control: Consistency, shared best practices, and a semantic foundation.

• Freedom: Autonomy, agility, and room for innovation.

An analytics franchise model allows you to have both. This approach aligns with the federated data governance model, which combines centralized oversight with decentralized execution, providing the best of both worlds.

What is an analytics franchise?

An analytics franchise is a repeatable, cross-functional team model that embeds analytic capabilities within departments. Each franchise blends:

• Domain understanding (knowledge of the business function)

• Analytic skills (how to explore and interpret data)

• Technical skills (how to access, prepare, and manage data)

These franchises collaborate with a centralized Data & Analytics (D&A) center of excellence, forming a network of collaborators that share insights, standards, and tools. As Steve Pimblett, former CDO of The Very Group, notes, establishing data centers of excellence that mirror the company's organizational structure enables leaders in respective functions to work closely with data experts best positioned to address their unique needs.

3 key ingredients:

1. A hybrid organizational structure: Mix centralized oversight with decentralized execution.

2. Prototype-first governance: Let teams experiment in a sandbox before scaling to production.

3. Multidisciplinary teams: Combine data engineers, scientists, translators, and business leaders.

Prototype → pilot → production

One of the most powerful concepts in the Gartner model is the analytics content lifecycle. Rather than rushing from idea to implementation, teams move through three stages:

• Prototype: In a sandbox, teams quickly build data views, dashboards, or predictive models. These are rough drafts that can be iterated rapidly.

• Pilot: The best ideas are tested more broadly to validate value and usability.

• Production: Proven solutions are scaled and shared across the organization, often with centralized support and service-level agreements (SLAs).

Despite the value of this model, Gartner found that only 50% of organizations have a protected environment for prototyping, and just 33% assign a product manager to analytic projects. That’s a missed opportunity.

The case for franchises in every department

Gartner recommends establishing an analytics franchise in every major function—from HR and finance to marketing and sales. But not all departments start at the same level of maturity. Some may already have strong analytic and tech skills, while others might need foundational support.

That’s why the first step is to assess your current landscape:

• Which teams already have the right talent?

• Where are the gaps in domain knowledge, analytic expertise, or tech skills?

• How can the center of excellence help fill those gaps?

Each franchise doesn’t need to be identical. Some might focus only on prototyping. Others may be trusted to bring content into production. The key is flexibility with structure.

Don’t forget governance: Certify your content

As organizations scale analytics, content governance becomes critical. According to Gartner:

• Only 41% of organizations have made dashboards and reports easily accessible via catalogs.

• Just 11% display certifications or watermarks to show whether a report or dataset is verified.

Integrating governance tools, such as Alation's data catalog, can aid in efficient data governance by providing a centralized overview of catalog growth and curation efforts within the organization. 

6 steps to start your analytics franchise network

Ready to start? Here’s Gartner’s step-by-step playbook:

1. Recruit business leaders as owners/operators. These are your franchise managers—business leaders who understand the domain and are ready to take ownership of analytic outcomes.

2. Build a balanced org model. Don’t swing too far toward centralization or decentralization. Instead, build strong communication channels between your centralized D&A team and decentralized franchises.

3. Create multidisciplinary teams. Think in skillsets, not just roles. Blend data science, engineering, and domain expertise.

4. Establish analytic sandboxes. Give teams a safe space to test ideas and build prototypes without the pressure of immediate production.

5. Define variable mandates. Not every franchise needs the same level of responsibility. Start small, then grow based on maturity.

6. Promote reuse and communication. Make it easy for teams to share what works. Use catalogs and certification frameworks to help people find and trust the best content.

Conclusion

Analytics isn’t just about building dashboards. It’s about building capability—in every corner of the business. The franchise model offers a path to scale analytics, improve data literacy, and drive real business outcomes without falling into the trap of either micromanagement or chaos.

By investing in people, process, and platforms, organizations can transform analytics from a bottleneck into a growth engine.

And just like any great franchise, it’s all about consistent quality, local ownership, and a brand your people can believe in.

Curious to learn more about scaling analytics? Book a demo with us today.