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NPI: A How To Guide for Engineers & Their Leaders
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Leading from the Front
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Marcel Tremblay: The Olympic Mindset & Engineering Leadershippopular
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Anurag Gupta: Framework to Accelerate NPI
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Kyle Wiens on Why Design Repairability is Good for Business
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Nathan Ackerman on NPI: Do The Hard Thing First
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JDM Operational Excellence in NPI
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Building the Team
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Quality is Set in Development & Maintained in Production
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3 Lessons from Tesla’s Former NPI Leader
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Maik Duwensee: The Future of Hardware Integrity & Reliability
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Reject Fake NPI Schedules to Ship on Time
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Leadership Guidance for Failure to Meet Exit Criteria
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Screws & Glue: Getting Stuff Done
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Choosing the best CAD software for product design
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Screws vs Glues in Design, Assembly, & Repair
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Best Practices for Glue in Electronics
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A Practical Guide to Magnets
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Inspection 101: Measurements
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OK2Fly Checklists
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Developing Your Reliability Test Suite
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Guide to DOEs (Design of Experiments)
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Ten Chinese phrases for your next build
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NPI Processes & Workflows
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Production: A Primer for Operations, Quality, & Their Leaders
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Leading for Scale
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Proven Strategies for Collaborating with Contract Manufacturers
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Greg Reichow’s Manufacturing Process Performance Quadrants
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8D Problem Solving: Sam Bowen Describes the Power of Stopping
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Cut Costs by Getting Your Engineers in the Field
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Garrett Bastable on Building Your Own Factory
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Oracle Supply Chain Leader Mitigates Risk with Better Relationships
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Brendan Green on Working with Manufacturers
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Surviving Disaster: A Lesson in Quality from Marcy Alstott
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Ship It!
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Production Processes & Workflows
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Failure Analysis Methods for Product Design Engineers: Tools and Techniques
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Thinking Ahead: How to Evaluate New Technologies
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How to Buy Software (for Hardware Leaders who Usually Don’t)
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Adopting AI in the Aerospace and Defense Electronics Space
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Build vs Buy: A Guide to Implementing Smart Manufacturing Technology
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Leonel Leal on How Engineers Should Frame a Business Case for Innovation
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Saw through the Buzzwords
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Managed Cloud vs Self-Hosted Cloud vs On-Premises for Manufacturing Data
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AOI, Smart AOI, & Beyond: Keyence vs Cognex vs Instrumentalpopular
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Visual Inspection AI: AWS Lookout, Landing AI, & Instrumental
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Manual Inspection vs. AI Inspection with Instrumentalpopular
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Electronics Assembly Automation Tipping Points
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CTO of ASUS: Systems Integrators for Manufacturing Automation Don't Scale
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ROI-Driven Business Cases & Realized Value
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Webinars and Live Event Recordings
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Build Better 2024 Sessions On Demand
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Superpowers for Engineers: Leveraging AI to Accelerate NPI | Build Better 2024
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The Motorola Way, the Apple Way, and the Next Way | Build Better 2024
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The Future of Functional Test: Fast, Scalable, Simple | Build Better 2024
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Build Better 2024 Keynote | The Next Way
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Principles for a Modern Manufacturing Technology Stack for Defense | Build Better 2024
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What's Next for America's Critical Supply Chains | Build Better 2024
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Innovating in Refurbishment, Repair, and Remanufacturing | Build Better 2024
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Leading from the Front: The Missing Chapter for Hardware Executives | Build Better 2024
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The Next Way for Reducing NPI Cycles | Build Better 2024
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The State of Hardware 2025: 1,000 Engineers on Trends, Challenges, and Toolsets | Build Better 2024
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Scaling Manufacturing: How Zero-to-One Lessons Unlock New Opportunities in Existing Operations | Build Better 2024
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Design for Instrumental - Simple Design Ideas for Engineers to Get the Most from AI in NPI
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Webinar | Shining Light on the Shadow Factory
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How to Prepare for Tariffs in 2025: Leaders Share Lessons and Strategies
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Tactics in Failure Analysis : A fireside chat with Dr. Steven Murray
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Every 0.5-star improvement in Amazon rating increased sales by 3% across all channels.
Research from Pattern Data Science
E-commerce platforms are on the verge of a new era of transparency, requiring brands to up their game on electronics quality and returns. Consumers have had access to peer consumer reviews on e-commerce sites like Amazon for years. However, consumers still spend significant time reading reviews to determine whether poor ratings equate to poor electronic device quality. The star ratings themselves significantly impact sales. According to research by Pattern Data Science, for every 0.5-star improvement in Amazon rating increased sales across all channels by 3%. For less-established brands, Andre Neumann-Loreck, founder and managing partner of On Tap Consulting, shared, “The difference between five stars and four stars on Amazon can be 50% of sales numbers”.
Recent changes are causing a shift toward more transparent information. This could have ripple effects through electronics brands’ supply chains, particularly in competitive categories. For example, Digitec Galaxus, a Swiss e-commerce platform, started listing return and warranty rates for all of the items it sells in January of this year. For brands in competitive categories, Galaxus and Digitec will show their statistics and those of their competitors. Similarly, Amazon recently started rolling out “frequently returned” labels for some items. Returns are a huge cost for retailers – the National Retail Foundation reports that 16.5% of online retail purchases in 2022 were returned. The intended effect of these transparency initiatives is likely to drive consumers away from low-quality products that cost retailers money in reverse logistics costs and towards higher-quality ones.
Product quality data has become increasingly front and center for customers during the buying process. Brands are now forced to re-think whether their return rates are acceptable when clear alternatives are available. Even brands with excellent scores will likely begin to feel pressure from competitors. It’s reasonable to assume these brands already invest in core best practices for low return rates. Best practices likely include keeping product design and quality in-house, having rigorous reliability qualifications and ongoing reliability tests, and investing in production oversight. Collecting data on your products and manufacturing processes is no longer enough since your competitors are likely doing the same. Turning that manufacturing data into intellectual property is the next frontier to staying ahead.
Data becomes intellectual property when it can be uniquely leveraged to produce the best business outcomes, such as unique product performance, lower return rates, and strong margins. This means more than just collecting data. It means turning those manufacturing analytics into actionable insights to improve product quality, the rate of escapes that result in returns, and the efficiency of the manufacturing process. One priority for these brands will be to invest in advanced analytics tools (like Instrumental's) to identify new patterns and insights in their data. Another is to move from one-time insights to real-time oversight – with alarms set up when process capability shifts. As transparency becomes the norm, brands that make investments here will be able to drive down the costs of escapes and win more top-line revenue from their competitors.
In the end, the message is clear: transparency is coming. Brands that want to maintain or grow their sales must invest in the infrastructure and tools needed to turn their data into intellectual property. By doing so, they’ll be able to outpace their competitors and provide customers with the electronics quality and reliability they demand.