Case Study

Okland Construction

Okland Standardizes Submittal Register with AutoSpecs, Easily Transfers Data to Procore

Challenge
Utah-based Okland Construction was growing fast, and was feeling the constraints of a slow, inefficient submittal log creation process. The multiple project teams each had their own way of recording submittals, leading to inconsistencies between projects that further slowed an already tedious process.

However, these disparate processes had their similarities. None of them could offer a high-level overview of the logged submittals by type, and all of them took valuable time and resources to create. Brad Wagner, a Process Improvement Manager at Okland, was called in to help.

Standardize, Streamline, and Save
Brad turned to Pype AutoSpecs. Using the software, Okland standardized their formatting and process, adding a high level of detail to their submittal registers across all project teams. The dashboard provided an easy to navigate dive into the submittals, clearly displaying them by type. The comprehensive register allowed for project teams to quickly and efficiently notify the design team of errors and incorporate the revised specs into their submittal logs, and then push the log into the integrated project management tool Procore.

Impressed, Okland quickly became an AutoSpecs enterprise client of Pype. According to their estimates, Okland now saves two weeks of man hours on every project. This resulted in a direct ROI of 400% from time savings alone, but an immeasurable ROI from the company-wide consistency AutoSpecs provides.

“Pype AutoSpecs has helped us standardize our submittal management process faster than we ever thought possible. What took weeks, now takes minutes. As an enterprise client, we benefit from using AutoSpecs from Precon to Closeout to quickly digest and consistently execute on all project requirements.”

Brad Wagner
Process Improvement Manager, Okland Construction

Case Study by Pype

Pype provides software solutions to the construction industry to automate manual processes using AI.

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