Data-Driven Design: Using Real-World Results to Define New Products

Written By: Cat McClintock
  • 6/14/2017

Analysts expect more than 70% of global, discrete manufacturers to offer connected products by the end of 2017. Like your competitors, your business has probably either already started transforming your engineering processes to leverage the potential of the Internet of Things (IoT), or is exploring how to start.

Performance-Based Analysis (PBA) is a powerful first step on the journey to transform your digital engineering design. PBA brings real-world data generated from your product prototype and its specific use cases into your CAD system to optimize product design and development.

Imagine that you’re establishing design requirements for a tractor: In the past you had to make assumptions about factors such as what maximum load your tractor’s bucket should support. Every assumption increased the risk that your product would be over-engineered (adding time and cost) or under-engineered (decreasing performance and customer satisfaction).

PBA solves this problem. With sensors on a connected prototype, you can capture and use real data (instead of assumed data) from testing to precisely understand design boundaries and constraints and design more efficiently.

Harness the power of many with Data-Driven Design (DDD)

Even more value comes from the next step in the journey: Data-driven design (DDD). Data-driven design uses real-world use data from fleets of connected products in the field to improve quality and ensure that your next generation of products meet your customers’ needs even better than today’s.  

This moves beyond using real-world data based on a single prototype. You can now harness data from thousands of products in the field today to help you understand use and behavior trends. 

Imagine that tractor again—but now you’re harvesting data from a whole fleet of smart, sensor-enabled tractors. With DDD, you can run analytics on that data and identify trends across geographies, climates, and use cases.

You might find that certain parts are failing more in one climate than another, or that the maximum load for that bucket is much higher in cold climates than in hot climates, for instance. You can use what you learn to design better quality products that truly meet your customers’ needs in different regions.

You can then feed that analyzed data back into your CAD system to take forward into the design of the next generation of your tractor or family of tractors. Your company might even use the trends that emerged to explore branching out to offer different tractor models best suited to different climates.


 Using real-world data to drive design

Data-Driven Design (DDD) harnesses real-world data from populations of connected products in the field to drive more informed next-generation design decisions.

With DDD, real-world data available at scale makes it possible to

  • Drive improvements in quality and reliability.
  • Analyze the impact of potential design changes.
  • Simulate your design to improve the system design or software control systems.
  • Better understand the engineering working envelopes of your products.
  • Make better business decisions for the your product’s next generation.

In the end, better real-world data gathered and analyzed at large scale means more efficient product design, better business decisions, improved product performance, and more satisfied customers.

Learn more about the future of smart connected design

Wherever your design team is on the path to leveraging the potential of smart, connected products, PTC has the solutions to solve today’s design challenges and the vision to support your journey to making the potential of IoT a reality. Learn more about emerging technologies that can help you along your way with insights from industry thought leaders in the eBook, Smart Connected Product Design.

The Future of Product Design. Download the eBook


  • CAD
  • Retail and Consumer Products
  • Connected Devices
  • Predictive Analytics

About the Author

Cat McClintock

Cat McClintock edits the Creo and Mathcad blogs for PTC.  She has been a writer and editor for 15+ years,  working for CAD, PDM, ERP, and CRM software companies. Prior to that, she edited science journals for an academic publisher and aligned optical assemblies for a medical device manufacturer. She holds degrees in Technical Journalism, Classics, and Electro-Optics. She loves talking to PTC customers and learning about the interesting work they're doing and the innovative ways they use the software.