Lucas Systems and CMU team up on data models for warehouse workforce planning

Research aimed at warehouse supervisors

Lucas Systems, a provider of software for warehouses and distribution centers, announced its latest partnership with Carnegie Mellon University on research that it says has potential commercial impact for the logistics industry. The work focuses on new ways to help supervisors use data analysis when deciding how to deploy labor and assign tasks.

According to the company, the contribution could have significant commercial impact for thousands of companies in the logistics sector.

The starting point is a gap Lucas Systems describes in the market. Despite an overabundance of warehouse data, operators still lack the tools to fully use those insights to manage labor and tasks efficiently. The company says the landscape is so complex and requires such constant observation that it becomes impossible to rely on human decision making, and argues that modern problems call for a more sophisticated approach that only smart technologies can provide.

What the CMU students contributed

Master's level students in the Spring 2026 cohort of CMU's Master of Science in Applied Data Science took part in the project. According to Lucas Systems, they provided prediction models after studying hundreds of data attributes related to warehouse users and behaviors.

Lucas Systems Director of R&D André Lessa said the students "collaborated with us on the very complicated math." He added: "As a result, we have a strong foundation to realize our vision."

The company's data scientists and software engineers say these state-of-the-art perspectives could be a game-changing leap forward in an industry they describe as still overly reliant on guesswork and tribal knowledge when it comes to planning. The source does not give performance figures or a timeline for turning the research into a product.

Views from both sides

Kent Szalla, Lucas Systems VP of Software Engineering and Customer Success, put the problem bluntly: "Warehouse managers are drowning in data but starving for insight." He said they make "million-dollar decisions based on experience and gut feel because the data they have isn't organized in a way that tells them what to do next."

Szalla said the research points toward a future "where the system surfaces the right signal for planning at the right moment." In his words: "Supervisors aren't guessing, they're deciding."

The project is one of several ongoing collaborations between Lucas Systems and CMU. Nynke Niezink, Associate Professor in the Department of Statistics and Data Science at CMU, called the partnership "extremely valuable." She said students are trained to tackle challenging problems, but that translating very large data into practical solutions in a real-world context is something they can only practice with industry partners. In the capstone projects with Lucas Systems, she said, "we harness the power of data to understand and improve warehouse productivity."

What it means for logistics operators

For now, the announcement describes research and a foundation rather than a finished product. Lucas Systems says it has been building warehousing software for nearly three decades and uses AI, machine learning and optimization models to improve distribution center performance. The CMU work is meant to support its vision of systems that tell supervisors what to do next, instead of leaving them to rely on experience alone.

Logistics operators that already collect large amounts of warehouse data are the intended beneficiaries. Whether and when the prediction models reach customers is not stated in the release.