The Hidden Toll on Engineering Teams
Engineering teams juggle complex designs, tight deadlines, and extensive collaboration. When data is scattered or outdated, engineers spend valuable hours locating or verifying information instead of innovating.
Much like a patient troll lurking in the shadows of the only bridge in town, the issues caused by improper data management sneak up on unsuspecting engineering teams, stealing precious time as well as their lunch money.
Addressing these issues restores capacity and speeds up development cycles.
- Outdated Information: Engineers work with obsolete data 28% of the time, leading to design mistakes and extra rework.
- Time Spent on Non-Value Activities: Almost 40% of engineering hours are spent on collaboration and rework caused by poor data practices, nearly matching the 50% devoted to design tasks.
- Cycle Delays: Design timelines extend as teams chase file versions, manage manual approvals or correct late-stage errors.
By improving data integrity, teams can focus on innovation and quality rather than searching and correcting.
Enhance efficiency, reduce delays. Explore smarter SOLIDWORKS data management strategies.
Learn More Financial Consequences for the Business
Poor data control affects more than engineers, with every lost hour impacting budgets and margins. Strong data practices protect both schedules and revenue.
The results from Tech Clarity’s survey indicate that businesses who are not using data management effectively struggle with higher development costs.
Outdated information can also consume up to 20% of engineering resources, expanding budgets.
Product costs may also be elevated, as late-stage fixes often require expensive workarounds or feature cuts that increase unit costs and potentially weaken the market position of both product and business.
Data Management provides:
- Seamless Collaboration: Central storage ensures every stakeholder accesses the same, up-to-date information. Review cycles shrink when designers, analysts and manufacturing engineers converge on a single source of truth.
- Faster Decision-Making: When validated data is a few clicks away, it becomes straightforward to compare design alternatives, evaluate materials or validate compliance requirements without time-consuming searches.
- Greater Efficiency: Automated workflows and metadata tagging eliminate repetitive tasks such as manually renaming files or updating spreadsheets. Engineers focus on design, not on document wrangling.
- Cost Control: Reducing duplicate effort and minimising rework lowers development expenses. Organisations recoup their investment in data management tools by avoiding the hidden costs of lost or outdated data.
- Improved Quality: With an audit trail of every change and robust version control, teams can pinpoint root causes quickly when issues arise, minimising defects and supporting regulatory compliance.
When data management is poorly implemented or absent entirely, teams risk overshooting product development deadlines and missing out on significant revenue.
These delayed launches hand the advantage to faster competitors and reduce the time available for the product developer to generate returns.
It’s therefore clear, that investing in systematic data management helps to reduce wasteful spending and provides a structure for projects to remain on schedule and within budget.
Why Data Management Matters More Than Ever
A cliché? Perhaps... Although data management will always remain relevant and integral in successful product development cycles.
Product ecosystems span multiple disciplines, locations, and external partners. Workflows and processes are continuously ‘streamlined’ or evolving, yet data streams only seem to get larger.
Data Management systems provide security to files and teams through controlled, user-based permissions. And, as new technologies like artificial intelligence (AI) emerge and are adopted, the complexity of a business’ processes rises – as does the risk of misaligned data and costly errors:
- Supply Chain and Outsourcing: Up to 16% of design work may be external, yet 59% of companies find synchronising this data only moderately effective or worse.
- Regulatory and Quality Requirements: Strict traceability rules mean poor data control can lead to compliance failures or product recalls.
Unified data practices enable all stakeholders to work from the same reliable information, turning complexity into a competitive advantage.
Common Challenges for Engineering Teams
Even well-resourced organisations confront data silos and inefficiencies.
Identifying these barriers is the first step to choosing the right solution, and from there, suitable tools can be evaluated and deployed to reduce these common challenges:
- Disconnected tools create isolated data pools across CAD systems, spreadsheets, and standalone applications.
- Manual file-sharing via email or network drives leads to confusion over the current version.
- Limited access for non-engineering teams creates delays in procurement, manufacturing, and customer feedback loops.
Overcoming these challenges requires a cohesive strategy that unites systems, automates workflows, and provides easy access to all users.
Best Practices to Reduce Design Costs
It should be clear by now that effective data management is a great way to reduce inefficiencies when designing new products.
How much time and resource could you recover by better managing your data?
Don't you have enough to do already? PDM systems establish background processes that allow design & engineering teams to increase their efficiency and navigate challenges. Here are a few simple ways businesses can benefit before implementing any formal data management system and establish a foundation for ongoing improvement:
- Centralise Your Data: Adopt a single centralised system so that every user accesses the most recent files.
- Automate Version Control: Build workflows that issue automatic notifications for changes and enforce approval steps.
- Streamline Communications: Apply consistent processes for all your engineering, procurement and manufacturing teams as well as customers.
- Raise and Track Issues Early: Encourage early collaboration between engineers and analysts to identify issues before they reach production and follow them to resolution.
- Gather Customer Feedback Early: Securely share preliminary designs to confirm requirements and avoid late-stage changes.
- Adapt to your Needs: Your processes and workflow will naturally evolve over time and product development, regularly review your requirements and consider whether there are more efficient ways of working.
These measures reduce hidden costs and support a culture of agility and continuous refinement.
Exploring Your Data Management Options
Fortunately, poor data handling is avoidable with relative ease. Consolidating information, automating critical processes, and providing transparent access across teams, organisations can recover lost hours, cut rework, and accelerate launches.
Consider how your business can benefit from implementing a data management system, like SOLIDWORKS PDM, the SOLIDWORKS Cloud Services, or advanced ENOVIA solutions.
Get in touch with our experienced consultants to discover how data management and services can help you implement tailored data management strategies.
We can help you combining leading PDM systems, cloud collaboration tools and expert consultancy.
Contact us to discuss how our solutions can streamline your operations and strengthen your bottom line.
Take the Next Steps
Take a deeper dive into SOLIDWORKS PDM and learn how this highly configurable data management system can work for you and your business.
Or learn to master data management with our CPD-accredited SOLIDWORKS PDM training courses delivered by industry experts.