When Three Weeks Becomes Three Clicks: Real Stories from the Factory Floor

Getting the right information at the right time shouldn't feel impossible. Yet for years, that's exactly what it felt like for manufacturing and supply chain teams trying to make sense of their data.

We recently gathered three leaders from different corners of the manufacturing world to talk about what's actually working. Jim Shane from Composites One, Joe Persio from Zeus, and Hamal Solanki from Sooner Pipe share the messy reality of spreadsheets, the frustration of waiting weeks for answers, and the surprising speed at which things can change when you fix your data foundation.

The Problem Everyone Recognizes

All three companies started from the same place: data everywhere, answers nowhere.

Jim described what many in manufacturing face daily. "We have lots of disparate data sources. We needed a way to thread all of that information together and present it in a way that actually helps people make decisions more quickly."

At Zeus, Joe saw the same pattern. "The company was basically Excel spreadsheets, Apex forms, Oracle reports that were 15 years old. They really didn't allow you to take different parts of your ecosystem and put them together to get a holistic picture."

For Sooner Pipe, Hamal pointed to a critical trust issue. "You look at the summary report, it gives one number. The detailed report gives a different number. Even though the difference wasn't major, anytime an accountant is using it, even a difference of a hundred dollars matters unless you can explain it."

When your team doesn't trust the numbers, they go back to Excel. Every time.

The Inventory Problem That Never Goes Away

Every manufacturer on the panel brought up inventory. Not as an aside, but as a primary pain point that demanded immediate attention.

Jim's team at Composites One tackled aged and excess inventory that had piled up during supply chain disruptions. "We were really bulking up on inventory. We had a lot of that sitting around, kind of stagnant. We did not have an elegant way of addressing that using our newer ERP and legacy systems."

The solution was more than seeing what inventory they had, it had to be a way to give sales teams the insights they needed to act in real time."We needed a platform to pull it all together, make it easy to digest, and provide the visibility that you just wouldn't have had otherwise. Quickly, concisely, and in a more real-time format."

At Zeus, Joe took inventory optimization even further by combining detailed data with AI. "We were able to do a recipe in our AI platform and push that into our system. Now we have a dashboard for our ops team that shows them every hour: you've got this on the shelf, this just came in or has been sitting, these exactly match, let's ship it out."

That dashboard, which Joe built in 30 minutes with Incorta, sped up inventory optimization by 300%.

From Three Weeks to Three Clicks

The time reclaimed from manual work started to change what questions teams could actually ask.

Joe explained the shift: "Something that used to take three weeks now takes about three clicks. If you think about that in your ecosystem, the ability to take all that away and put it in one place has completely changed the game on how people are going to engage with your data."

The impact goes beyond speed. When answers come quickly, people start asking better questions. When data is trustworthy, teams actually use it to make decisions instead of second-guessing every number.

Jim shared a moment that captures this shift. A user questioned an on-time delivery metric that didn't match what they saw in their ERP. "We can show you where we're getting it from. Well, it turns out the business logic was different in SAP. It's not a matter of one thing's right, one thing's wrong. It's just looking at it in different ways. Now we can prove where everything's coming from, and folks in the user community love the fact that you can prove it to them."

Making Space for What Actually Matters

When Hamal's team at Sooner Pipe needed to replace their reporting infrastructure, they faced a choice: spend months and millions upgrading their existing setup, or find a different path forward.

They chose speed. "We were able to convert all our legacy reports that were developed over 12 years within four months."

The data extraction process that used to take two and a half hours now completes in one hour. Reports that once required IT intervention now let different teams look at data in different ways with just a few clicks.

"Before, anytime they needed something different than what they already had, they had to come to IT. The turnaround time was so long that by the time the information came back, it was usually too late," Hamal explained.

Now their sales team, purchasing team, and operations can all view the same data through their own lens without waiting in line for developer time.

Where AI Actually Fits In

The conversation naturally moved to AI, but not in the way you might expect. These aren't theoretical use cases or future possibilities. They're practical applications happening right now.

Hamal's team is building an AI model to predict raw material prices. "In our industry, the raw material we purchase goes through a lot of ups and downs based on drilling activity, oil prices, GDP, inflation. We're going to feed a lot of data into our system and create an AI model that predicts the price of our purchases."

The goal is practical: should the purchasing team do a speculative buy now, or wait because prices are expected to drop?

Jim is working on similar predictive capabilities. "We're looking at bringing in leading economic indicators and drawing correlations between what's going on out there and how that's impacting us within our four walls. Then potentially leveraging generative AI to ask: what's that going to look like in the future?"

But here's what matters: none of these AI initiatives would be possible without getting the data foundation right first.

Joe put it plainly: "My data all lives in one place. So for me, it's very easy to get to my data in the way that I need to get it. We're able to model the data quicker. This is months of effort that I don't have to do."

What This Really Means

Joe shared something that gets to the heart of why this matters: "We've made Incorta a household name. You talk to anybody here; that is our platform of choice. We have about 1,200 use cases under our belt now."

When people trust their data, they use it. When they can get answers quickly, they ask more questions.

Jim said it well: "We've got a lot of flexibility, and we can prove where everything's coming from. Folks in the user community love the fact that not only can they see it, but you can prove it to them. I truly believe this is the best source for all this."

None of these companies started with a perfect plan. They started with specific problems: inventory sitting too long, buildings running out of space, reports that didn't match, questions that took weeks to answer. They fixed their data foundation first, and eerything else followed from there.

As Joe reminded the group: "Bring the problem, bring what you want to do. I brought it, and everyone's happier because we're partnering and showing value in a different way."

The manufacturing leaders who are winning today aren't the ones with the most sophisticated technology. They're the ones who can get the right information to the right people fast enough to actually matter. Sometimes that's the difference between three weeks and three clicks.

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