Business Performance – How Can You Change Cultural Attitudes Towards Data Usage?

Aug 8

4 min read

The Real Problem: Great Solutions. No Buyers.

In 2019, Petrobras found itself stuck.

Despite building technically robust solutions—semantic data models, machine learning forecasts, dashboards—the business wasn’t using them. A finance analyst famously quipped: “You gave me a gourmet menu. But I just wanted rice and beans.”

This isn’t just Petrobras’ story—it’s a familiar one across enterprises. The tools were there. The value wasn’t felt. The culture wasn’t ready. It is a layered problem. You are intimidated by the tools you use for accessing data – even if we present an GenAI interface, the question playing in the minds of people are – now I have to learn something that will replace me?

Then comes the self-service skills that are intimidating to adopt for many. Demonstration or seeing your colleague use it can create the incentive to overcome this hurdle. There is also an inherent fear that - WHAT IF - Using it makes me replaceable by anyone else? I get my job done why do I need to learn something new?

There is still the challenge of any learning curve- interpretation and proper use of reports that comes with lack of confidence and trust of the new process. Fear, wariness, suspicion, ignorance are surmountable challenges within business culture. As PetroBras shared with me, It took them one team at a time, enterprise level stakeholder support to win the trust of their partners supplying the financial information. They were creative as well, introducing a "wall of praise" company wide publicity of teams that won performance goals using data-driven enablers. They were able to demonstrate usefulness, growing adoption, and value delivered of the process and tools that had been made available to the community.

🧠 Practitioner Insight: Strategy Isn't Enough Without Trust

Many organizations view data governance as a checkbox. But Petrobras flipped the script: governance became the launchpad for automation, analytics, and AI at scale. This is where their story received applause at the EDW DGIQ summit 2025, I recently attended. ( Petrobras presenters in a group selfie)

(Anup Singh, Team BROU- Gustavo Mesa and Alejandro Izetta , Team PetroBras- Frederico Humberto Frossard de Lima , Amanda Lopes, Sidney Junior )

Their insight? Culture change starts not with tooling, but with shared understanding, storytelling, and aligned incentives. In a five-year transformation, they turned data skeptics into active users—delivering $5B in measurable impact and scaling database usage to 3M monthly queries.

Reviewing their playbook, there are 5 points that stand out for me that would be great learning points.

💡 Lesson from the field: 5 Lessons From the Petrobras Playbook -What They Did

1. Start With Pain, Not Possibility

Workshops helped them uncover real pain points from the business—long before developing any solutions.

2. Governance as a Service

They built a business glossary (400+ terms), but more importantly, embedded governance in usable, everyday tools.

3. Co-own the Future

Roadshows and design thinking workshops involved stakeholders in envisioning the future—creating accountability through ownership.

4. Prioritize Quick Wins

Instead of selling grand vision, they solved tangible problems quickly. That’s what built trust.

5. Deliver First, Then Scale

Each successful use case opened the door to another. One AI model alone informed $5B in strategic investments.

💡 Your Tip To Go:

“Governance is foundational—but no one lives in a foundation. People move in only when there are walls, windows, and working lights.”

Petrobras’ team didn’t just build infrastructure—they built trust structures. Their cultural pivot wasn’t top-down or compliance-driven. It was participatory, iterative, and grounded in shared goals. They coached and evangelized the role of humans in the loop, and showed the way for productive decisioning based on standardized information flows.

A Personal Lesson: The AI Forecasting Challenge

If you recall my recollection of the time I spent in AT&T- I can recall spending my early years in AT&T, responding to calls from the finance team- reconciling my teams forecast numbers for network demand capacity for 240 countries globally, each month. Several budgeting hours spent!!!!! Had I access to a self-service dashboard, We could have spent more time digging deeper into the data and not working on pulling data summary tables together (printed material!!!).

Over the years, as technology evolved, I have focused on getting the data layer established first. This has helped marketing with a 360 view of the customer market (B2C Telecom) or the customer support at the sales center a birds-eye view of a Business (B2B Tech Product Sales), and for strategic planning a holistic view of Branch locations + customers channel use (Banking).

Pattern Watch: Others Are Doing It Differently—Or Not At All

Petrobras succeeded where others stalled—because they treated culture as infrastructure, not an afterthought. This is also the approach that McLeod Software like many large tech companies are taking in building AI-fluency with their users and customers through discussion and value demonstration.

✍️ Reflection Prompt (Engage With Me Below!):

What’s one thing you’ve tried to shift attitudes toward data in your team or company?