The Data Trust Gap: Why Reams of Information Drive Pilots to Fail

We asked Eric Fidler a direct question on Wisdom at the Wellhead. What is the biggest challenge oil and gas companies are struggling with right now, regardless of size? His answer was immediate. They've got reams and reams of data they don't know what to do with.

Then he took it a step further. He said you can ask any CEO of an oil enterprise whether they see value in their data, and they know they have a lot of it. They just don't understand what to do with it. And that confusion doesn't stay at the top. It filters down through the entire organization. It shows up in the field as distrust. It shows up in pilot programs as failure. It shows up on airplanes as engineers carrying a stack of paper three inches thick because they trust the pages more than the screen.

Eric said the successful scaling rate for pilots in this industry is "ridiculously small." Not because the technology doesn't work. Because even when the answer is right in front of people, they don't trust it. That's the data trust gap. And until we close it, no amount of new technology is going to change the way this industry operates.

The Problem Starts at the Top

Here's what I've seen over the years. When the CEO doesn't know what to do with the data, everybody underneath them feels it. It might not be spoken. It might not show up in a memo. But it shows up in behavior. The production manager keeps running his own spreadsheet on the side. The field supervisor sticks with handwritten logs. The engineer pulls the numbers into his own model because he doesn't trust what the system is giving him.

None of those people are doing anything wrong. They're doing what makes sense when you don't have confidence in the information you're being asked to rely on. They're building their own safety nets because the official system hasn't earned their trust yet.

That's the part most technology vendors miss completely. They see the workaround and think it's a training problem. It's not. It's a trust problem. And you can't train someone into trusting data that hasn't proven itself to them yet.

Why Pilots Die on the Vine

Eric's point about pilot programs is one of the most important things said in that entire conversation. The industry's success rate for scaling pilots to full deployment is painfully low. And the reason is almost never technical.

What happens is this. A vendor comes in with a promising tool. They run a proof of concept on a few wells. The data looks good. The demo is clean. Everybody nods. And then nothing happens. The pilot sits in a folder. The field goes back to doing what it was doing before. And the company adds it to the list of "things we tried."

The reason it stalls is that the pilot proved the technology worked, but it didn't prove the data was trustworthy in the context of how that team actually operates. The demo was clean because the conditions were controlled. The moment it hits the messy reality of a real field with real operators and real pressure, the cracks show. A number doesn't match what the pumper saw that morning. A timestamp is off by an hour. A sensor reads differently than the gauge. And just like that, trust is gone. The paper comes back out.

The Structure Has to Come First

I've always told people, it's okay to be creative with the data you use to find better solutions. But it's not okay to be creative with the structure in which that data hits. That structure is everything. If the data isn't organized, validated, and delivered in a way that people can rely on, it doesn't matter how much of it you have. Volume without structure is just expensive noise.

This is where a lot of companies get it backward. They buy the tool first and worry about the data foundation later. They put a beautiful dashboard on top of a messy data set and wonder why nobody uses it. The dashboard isn't the product. The trustworthy data behind it is the product. The dashboard is just the window. If what's on the other side of the glass doesn't match reality, people stop looking through it.

That's why we've focused so heavily on data architecture at Total Stream. When you bring in SCADA data through Sensia's Avalon platform and position it in a structured data warehouse in real time, you're not just collecting information. You're building a foundation that an engineer can actually trust. You're taking care of that itch every production engineer has that says, "I don't want to spend 90% of my time chasing data. I want to do the work I was hired to do."

Eric Fidler's Advice for Closing the Data Trust Gap

Eric has watched pilots fail and succeed across every kind of operation, from mid-market independents to multinational producers. Here's what he's learned about what separates the ones that scale from the ones that sit in a folder.

Fix the data before you fix the workflow. If the information coming off the wellhead isn't accurate, timely, and structured, nothing you build on top of it will be trusted. Start with the foundation. Make the data right at the source before you ask anyone to change how they work based on it.

Don't prove the technology works. Prove the data is real. The industry doesn't need more demos that show what a tool can do under perfect conditions. It needs proof that the data matches what the field is actually experiencing, every time, under real conditions. That's the bar for trust. Meet it and the adoption follows.

Let results do the talking. You almost have to create a situation where someone looks across the road and says, "That guy did this and I didn't, and look how much further he is than me." That competitive instinct is real in the oilfield. Win one or two operators. Let them talk about what changed. Word of mouth goes a long way in this business.

Respect the paper. When someone carries a stack of printouts onto a plane instead of trusting the screen, don't judge them. Understand what that behavior is telling you. It means the system hasn't earned their confidence yet. That's not their failure. It's yours. Close the gap and the paper goes away on its own.

Final Thought

We don't have a data problem in oil and gas. We have a trust problem. Every company in this industry is sitting on more information than they know what to do with. The question isn't whether the data exists. It's whether anyone believes it enough to make a decision based on it.

Eric put it plainly. Even when the answer is right in front of them, they don't trust it. That's the gap. And it won't be closed by better sensors, faster processors, or prettier dashboards. It will be closed by getting the structure right, proving the data is real, and earning the confidence of the people who have to stake their decisions on what the screen is telling them.

The technology is ready. The question is whether the data behind it is trustworthy enough for someone to put down the paper and believe the screen. That's the only metric that matters.

If this hit home, you'll want to hear the full conversation.

Join Eric Fidler on Wisdom at the Wellhead as he breaks down why the data trust gap is the biggest obstacle to digital transformation in oil and gas, what makes pilots fail, and how operators can build a data foundation their teams will actually believe in.