December 4, 2017 | Written by: Wired Brand Lab
Categorized: Blog | Continuous Engineering
Share this post:
Product life cycles used to be straightforward—manufacturers designed, built, and serviced. Now, with the IoT and software-enabled devices, the cycles have accelerated and even reversed themselves. The stakes are high, and it can be hard to know where to start. Almost every high-performing piece of equipment—from dishwashers to factory robots—has baked-in intelligence. Sensor-packed devices constantly relaying data are among the billions of things that make up the Internet of Things.
Harnessing these things creates a competitive advantage for companies that can augment them with nascent forms of artificial intelligence. According to Gartner Group, by 2020, nearly all IoT devices will have some element of AI functionality. AI systems tap into sensor data to understand, learn, and derive insights that companies can use to help them improve operations, design new product variations, and even discover new business models.
Through omnipresent IoT connectivity, physical products are no longer seen as hunks of plastic or metal but as dynamic, “always-on” software platforms. Cars can download assisted-driving systems, entertainment options, navigation tools, and even power upgrades. Software can create marquee features every six months, compared with the two-year life cycle of hardware revisions. In this climate, companies with sophisticated IoT platforms can advance ahead three product cycles in the time a traditional hardware vendor builds a single new model.
From reactive to predictive
Take Sears Home Services, for instance, one of the largest field-service networks in the U.S. Every year, its technicians handle 7 million service calls. Those include more than 300,000 trips to homes for unnecessary requests and 600,000 additional trips for which the right part wasn’t in the truck—prompting an equal number of costly return visits. As CTO Mohammed Dastagir knows, that process doesn’t just waste resources, “it hurts our business.” Small wonder, then, why Sears is turning to IoT technologies to streamline operations. “We’re trying to get ahead of it,” says Dastagir. “If we get this right, we have a chance to create a benchmark standard for the industry. If we get one shot at it, we’re going to take that shot.”
In an industry that hasn’t been disrupted in years, Sears Home Services is creating a new customer experience.
Sears is shifting its service model from not just responding to customer issues but predicting them. A washing machine, for example, will soon warn of a critical failure within three months, using IBM’s Predictive Maintenance suite. To get it right, Sears is feeding a century’s worth of product manuals, service outcomes, and test results into Watson, IBM’s platform for natural language processing and machine learning. Sears provides service to almost all brands, so it is working closely with partners to receive and interpret live IoT data. With its own Kenmore appliances, Sears is also experimenting with acoustic sensors to supplement other data: Customers may no longer need to mimic an ailing appliance over the phone…“It’s making a thunka, thunka sound.”
Here’s the scenario they are working towards: Alerted by the machines themselves, service techs at headquarters will wire a software fix or steer the customer towards the right DIY solution. When a home repair is needed, technicians will arrive with the right information (and parts) to solve the problem. “No longer is it waiting for a guy with a screwdriver and a manual to roll up between 2 p.m. and 6 p.m.,” says Dastagir. “The appliance will send a message: ‘Something is failing, come help me.’”
Virtuous cycles of design feedback
The wider vision, of course, is to connect these new capabilities back into design—feeding IoT data into the product design cycle and manufacturing. Products such as IBM IOT Continuous Engineering can then manage the flow of IOT data and Watson’s analytics to mine new insights that keep feeding intelligence back into the system. Designers can create new appliances tailored to real-use cases emerging in the market as they happen. Coders can drop in new features.
Other companies integrate similar IOT feedback into the heart of their manufacturing operations. For instance, Flex (formerly known as Flextronics), which manufactures Fitbits along with tens of thousands of other products for major brands, plays a central role in the design and manufacturing of IoT machines, with the design expertise of 200,000 employees and vast global factory capacity. Using Watson predictive analytics, Flex has lowered the number of flaws on networking gear in one factory by 90 percent. And it is eliminating failures for car transmission parts in another.
Building the right partnerships for IoT innovation
In the IoT era, partnerships also factor significantly into competitive advantages. Bob Wolpert, SVP of quality custom distribution at Golden State Foods, points out that investment in the IOT yields more long-term dividends if it’s seeded with lots of outside relationships. “It’s important to get involved in small pilots now so you know how to play in the game,” says Wolpert. An early partnership with an IoT platform vendor, for instance, will help familiarize it with your business and will provide access to more business intelligence.
The lessons learned from those early partner projects can extend into new markets and business models. For example, Golden State Foods runs a significant trucking business, delivering to more than 125,000 stores and restaurants across the country, including McDonald’s and Starbucks. Within five years, data insights culled from routes and customer deliveries can be transferred to autonomous vehicles. In the meantime, Golden State Foods has introduced a wearable device for drivers to talk to Watson for weather and traffic data. It also plans to create a simple conduit for drivers to solve tough delivery hitches quickly on the road.
While Golden State Foods “stamps” hundreds of thousands of hamburgers per hour for its customers—shaping a lump of beef into the perfect shape for grilling— it also aims to help partner restaurants manage inventory on-site. Wolpert’s team and IBM developed a data dashboard, drawing from 25 sensors in pilot restaurants. As a result, predictive analytics has reduced inventory management duties for on-site staff by automatically prompting for resupply. That allows workers to focus more on customer experience. “It means less time in the back of house, and more time helping customers at the front counter,” says Wolpert. Golden State Foods can also save workers time by using high-speed visual inspection systems. Once such “smart cameras” go through a training period, they can catch defects and imperfections faster and more reliably than humans.
Says Wolpert: “Think really big, but chunk it up to start small and go fast.” He counsels companies to shore up employee skills and education so that they can actively engage with partners. In addition, he suggests forging ties with organizations of global scale so they can keep pace with your growth and new ventures.
Golden State Foods is one of the largest suppliers of produce to the food service and retail industries.
In adopting the IOT, lean-forward companies also suggest techniques to protect data and enhance its value. Open-source software is often a choice that ensures all partners have access to resources. In terms of security, AI and other emerging technologies “could help address current security concerns around connected ecosystems,” according to a 2017 report by Frost & Sullivan. Security also hinges on the choice of partners; companies should realize that some partners expect to yield additional value from your data. It’s better to pick a technology provider who maintains an explicit policy against data sharing.
Crossing the physical-digital divide
With the IoT and connectivity becoming ever-more ubiquitous across every industry, brands seeking a competitive advantage must embrace this transformation from physical to digital. “Products are shifting from being mechanically driven to software driven,” says Harriet Green, General Manager, Watson Internet of Things. “They offer differentiation and operational savings, redefine a client’s competitive position in the marketplace, attract new partners, and open new sources of revenue.” The IoT is taking products we’re all familiar with and investing them with new intelligence and connectivity, launching creative shifts no one could have foreseen. It certainly makes one look at the humble washing machine … and the hamburger … in a whole new light.
6 product design tips for the IoT era
- Use the aftermarket as a trove of great design research.
- Use IoT data to inform and iterate next design cycle.
- Train staff to understand the challenges and opportunities of the IoT.
- Partner early—and often.
- Make sure partners have security-minded business models.
- Tap into AI capabilities that can enhance security.
Industrial Design’s New Challenge: Success Through Connection
Watson IoT 2017 Continuous Engineering Summit
Golden State Foods and IBM Watson IoT set new standards in foodservice industry