Top Four Takeaways from Thomas Industry Update Podcast

Dev IQ featured in Thomas Podcast

Last week, Dev IQ’s CEO Shawn Davison joined Tony Uphoff, president and CEO of Thomas, for a conversation about Industry 4.0 on the Thomas Industry Update Podcast. We highly encourage you to check out the podcast for yourself (it lasts only 20 minutes). If you don’t have the time, we’ve put together the top four takeaways from our conversation around manufacturing, industry 4.0 and Industrial Internet of Things (IIoT). Check them out below:

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1. UX is Driving Demand

One of the driving factors making the industrial market ripe for software development is the demand for quality user experience (UX). End-to-end ecosystem design that spans all devices connected within system and empowers them work together is very much in need in the industrial manufacturing space. Industrial software development is no longer just about speed and efficiency. It’s about creating an experience that works and enables users to be productive – creating value for the business and a better experience for end users and customers alike.

2. Businesses are shifting from widget-makers to Product-as-a-Service (PaaS)

2020 will be the tipping point for Industry 4.0. One factor pushing it over the edge is that industrial businesses are increasingly leveraging IIoT technology to shift their business models from a widget-model to a product as a service model. For example, a company that used to be a lighting manufacturer might leverage IIoT to transition to an industrial lighting as a service provider.

The benefits that this shift brings to the manufacturer and end user can be significant. Think: better service, better user experience and proof, and better margins and long-term contracts. And while the shift in mindset can be difficult for organizations to visualize, from a technical standpoint, the requirements for such a transition are pretty straightforward – they only need a product that is connected and that collects data to jumpstart the process.

3. Artificial Intelligence will eat software and data

Software has traditionally been very siloed and procedural. Artificial Intelligence(AI) allows us to move beyond that and take functions that have been done in a complex way and put them into a model that predicts and provides information that’s far beyond anything we’ve experienced. But what AI requires is a lot of data.

Take predictive maintenance for example. Organizations have to start with an ecosystem where they can connect their products/components and collect data from those machines and devices. Then, they have to be able to ingest all that data within a cloud environment or a place where that can be processed using machine learning tools. It’s only then that organizations can start creating AI-powered prediction algorithms and learning models that can be pushed back down into edge devices. There’s a lot of opportunity here, but still a lot of work to get these data capture and processing systems in place.

4. Automation is a requirement, not an option

Software and technology is becoming more complex, not simpler. Today there are more devices, more components, and software is more distributed. What mitigates that complexity and its risk is automation. For example, Dev IQ automates testing because we’ve found that without automation the risk of regression is really high. In the near future, automation will be a requirement, not an option.

If you’re ready to hear more, you can check out our full conversation here. Then let’s connect. We’d love to help your organization think through its Industry 4.0 strategies and the systems you need to enable your digital transformation.

Let’s build something beautiful together.
blog author jamie murphy

Jamie Murphy

Marketing Strategist, busy mama, & blogger extraordinaire

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