Lean thinking applies to manufacturing and data. In aerospace & defense manufacturing, data is part of the product. Government contracts require more than physical parts—they demand digital models, genealogy records, and audit trails that track every step from design to sustainment. That information needs to be accurate, accessible, and valuable.
But too often, data piles up across disconnected systems. Engineers copy and paste between screens. Outdated records linger. Conflicting numbers lead to confusion. The same inefficiencies Lean principles address on the shop floor show up in the digital thread, slowing down operations and clouding visibility.
The DOWNTIME framework, originally designed for manufacturing, helps companies clean up their digital processes, reduce inefficiencies, and make data work for them instead of the other way around. Every inefficiency in data management falls into one of these categories:
- Defects
- Overproduction
- Waiting
- Non-utilized talent
- Transportation waste
- Inventory excess
- Motion waste
- Excess processing
Each affects the digital thread, making it harder to get value from data.
Defects
Preventing data defects starts with treating data like any other critical input—investigating recurring defects, defining a single source of truth, and thinking critically about changes to data systems. Trustworthy data goes beyond supporting effective execution. It enables advanced capabilities like data science used in prognostic health monitoring (PHM). Instead of a standard time-to-failure estimate based on usage hours, accurate manufacturing data could help pinpoint the lifespan of individual parts or assemblies.
Overproduction
More data is not always better. Engineers sometimes require data measurements on thousands of part characteristics when only a handful of key characteristics affect performance. Just like excess inventory slows production, unnecessary data makes it harder to find what matters. Lean data management focuses on what drives compliance, reliability, and customer value. Reducing the volume of data collected to truly valuable data must be part of every product lifecycle.
Waiting
Slow data flow holds up production. If engineering stores work instructions in a PLM instead of a Manufacturing Execution System (MES), shop floor operators may be idle while workflows are executed that are not germane to engineering definition. If supply chain planning runs on outdated lead times, teams make the wrong calls. Just like materials must arrive on time, data must move at the speed of operations. Avoiding delays means ensuring information stays in the right system—where it’s needed, when it’s needed—so production keeps moving.
Non-Utilized Talent
Skilled employees shouldn’t spend time on tasks automation can handle. If engineers are re-entering the same data across systems or analysts are manually cleaning up spreadsheets, something is broken. When a supplier portal already holds accurate lead times, procurement shouldn’t have to key them into an ERP. Lean data management removes unnecessary steps so teams can focus on solving problems instead of managing data.
Transportation Waste
Unnecessary data transfers create confusion. Pulling entire datasets from ERPs or MESs into data lakes “just in case” leads to multiple versions of the same information, making it harder to know what’s correct. AI models trained on mismatched data produce unreliable insights. Data should move only when it serves a clear purpose—improving the product, supporting decision-making, or enhancing the customer experience.
Inventory Excess
Storing data isn’t free. Cloud costs add up, and excessive storage slows retrieval and muddies analytics. Stockpiling too much raw material clutters a factory, and hoarding outdated or redundant data makes it harder to find what’s valuable. Engineering revisions, supplier records, and quality data should follow clear retention rules. If a dataset has no defined purpose for compliance, decision-making, or product improvement, it’s just taking up space.
Motion Waste
The greatest motion waste of data is the swivel chair. If someone is capturing data from a system or paper and putting it in a system, attack this waste immediately. This is a trifecta of waste, as you are not utilizing talent to its potential and are guaranteed to introduce defects to your data. When operators click through multiple screens to check a work order or engineers manually extract CAD data for suppliers, that’s motion waste. Information should be accessible at the point of use, and data should only originate once. Lean data management eliminates extra steps, keeping critical insights within easy reach.
Excess Processing
Simple data delivered at the right time is often more valuable than a highly polished report. A production manager doesn’t need a complex dashboard if a real-time machine status alert can prevent downtime. A supplier doesn’t need a massive data export if a targeted update on lead times keeps an order on track. Over-processing data—merging, transforming, and formatting without a clear benefit—can add unnecessary steps. A Lean approach prioritizes getting the correct information where needed, supporting execution, and maintaining the digital thread without adding complexity.
Building a Lean Digital Thread
Avoiding waste in data is just as important as eliminating inefficiencies on the shop floor. Poor-quality data, unnecessary processing, and disconnected systems create bottlenecks that slow production and increase costs. Data DOWNTIME poses the same business risks as sourcing, production, and delivery inefficiencies. A strong digital thread keeps operations running smoothly, ensuring data flows purposefully instead of piling up as waste. When engineering, supply chain, production, and quality systems stay connected, manufacturers gain traceability, efficiency, and control—without the need to re-engineer their entire data ecosystem.
A MES purpose-built for A&D can help you create a Lean digital thread. It keeps key manufacturing data structured and accessible, connecting operations without unnecessary duplication or movement. When MES integrates with enterprise systems, it becomes a real-time system of record that strengthens decision-making and streamlines compliance. With the right data strategy, manufacturers avoid waste, reduce complexity, and make better decisions.
Discover how Solumina MES provides the tools to make data Lean, structured, and valuable.
