Learn how Goodyear is making an intelligent tire, Southwest Airlines is saving millions on fuel, and Neurio is introducing energy monitoring for the home.
Traditionally, data streams in from just a few places.
Maybe it’s user activity on your website. Maybe it’s an internal log of orders. The point is, to get a full picture of your company’s data you used to only have to link up a couple of databases.
But that’s all changing now. Valuable data is being generated not just on the web and mobile but also on IoT devices, bots, and more.
We’re moving toward a time where everything will be capable of transmitting data. In the future, every aspect of your product will generate data and use that data to change. In many industries, like manufacturing, transportation, and home technology, this is already happening.
Goodyear takes data collection seriously — so much so that its vision for the future looks more like a telematics company than a tire manufacturer.
That’s because IoT is changing the entire business model of Goodyear, moving it from a product-only company to a service-based one. Goodyear’s new programs range from simple tire modifications to moving beyond tires altogether.
On the simple end are initiatives like adding RFID (radio-frequency identification) tracking to their NASCAR racing tire in order to prevent thefts and improve the accuracy of inventory. However, location is far from the only information their tires are generating — sensors can measure temperature, tread depth, tire pressure, and more.
When this data is transmitted to the cloud and analyzed, it enables a new class of Goodyear tire services:
Goodyear is even offering services that have nothing to do with tires. Since they’re already selling telematics to vehicle fleets, they’ve also built value-added applications on top. For example, they have a driver scoring application that measures behavior like harsh braking and fast acceleration, which causes fuel inefficiency and vehicle wear.
And Goodyear isn’t stopping there. Their vision for the future is an AI-powered, spherical tire that can alter itself physically as it gathers information from its surroundings — like growing small dimples to increase friction if it senses a wet road.
This is the future of the manufacturing industry. Products won’t just be objects anymore — they’ll be data generating, data ingesting, and adaptable.
For years, airlines have been using data on travel demand to determine which flights to offer between which cities. But to really analyze a flight, you need to know so much more than just how many passengers are on it — there’s fuel usage, temperature, turbulence, and so much more.
Southwest Airlines is now getting this sort of data through the industrial Internet, a digital network linking on-plane hardware like engines to the cloud. And one of the biggest opportunities this new data has provided is saving money on fuel.
Southwest spends about $5 billion on fuel each year, meaning even a small improvement in efficiency can lead to some hefty payoffs. But so much of that fuel is wasted. In 2014, airlines altogether lost $4.3 billion in fuel just from idling on the tarmac. And since flights need to account for so many factors, they often carry a much larger fuel load than needed — the weight of which limits the number of passengers and amount of cargo a plane can hold.
But with their new streams of data, Southwest can get a much more precise understanding of how much fuel planes will need for different routes and weather conditions. The system also gives pilots in-air knowledge, so they can weigh the costs of dropping a few thousand feet to avoid turbulence.
Precise information on fuel needs helps optimize purchasing decisions, as well. Southwest planes fuel up at several locations, each with distinct pricing. Southwest analysts can make on-the-spot decisions about filling a plane up with extra fuel at a cheaper location.
All this data helps Southwest run a more efficient business and provide better customer service .
Other airlines, like Qantas, are starting to follow Southwest into this world of industrial Internet. This trend is likely to extend to the rest of the transportation industry as well: car services, delivery fleets, and cruise ships will all benefit from vehicles generating data which can be analyzed to cut gas and find the fastest and most fuel-efficient routes.
The idea of the smart home has been around since the early 2000s, but a lot of the technology released in this area has been more about convenience than actual intelligence. Thermostats you could change from your phone and DVRs you could record shows on from anywhere.
But now homes are producing data — and one of the major things it’s being used for is energy conservation.
Neurio launched its Kickstarter campaign in 2013 and started shipping products two years later. Its main hardware is a sensor box that is mounted in your home’s electrical breaker panel. Once installed (by an electrician), you get real-time stats on your home energy usage on the Neurio Home app. Neurio has Appliance Detection so you know exactly how much your dryer, bedroom light, and oven are costing you in watts (and dollars, once you input your utility company’s kWh rate). Using Neurio’s technology, homeowners know what behavior they should change to conserve energy and which appliances would be the most cost-effective to replace with a more efficient machine.
But Neurio isn’t stopping at just collecting data from your appliances. They’re also working on using that data to automatically lower your energy bill. They just introduced Storage Optimization Analytics, which can maximize savings for solar users.
Many solar utility companies have a Time of Use (TOU) system where they buy and store the extra energy produced by your home’s solar panels during the day and sell it back to you at night. The price of electricity varies throughout the day, rising during daytime hours when factories and other businesses need it. By considering a homeowner’s TOU bill, along with expected energy generation due to weather conditions and expected home energy usage throughout the day, Neurio decides to keep rather than sell this energy at various times of the day to minimize cost, while making sure the home battery has enough energy to handle the expected load.
Neurio’s expansion mirrors the transformation of home appliances as a whole — first, an appliance is connected to a larger network, then it collects data, and then it acts upon that data. The “smart home” is truly approaching.
Even your garbage can is able to collect data now.
In the next decade, your company is going to have data streaming in from a huge number of sources. It’s vital to be able to easily pour this data into one location for a complete analysis. Imagine Goodyear just relying on logged maintenance calls and internal testing to find ways to improve their tires, rather than incorporating real-time data from tires on the road — not the situation they would want.

Sentiment rank: 1.9

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This interview with Isabel Evans, learn about artificial intelligence, communication, and the evolution of software testing in terms of Agile, QA, and DevOps.
At the StarEAST software testing conference in 2017, Isabel walked onto the stage during the popular “Lightning Strikes the Keynotes” session and delivered a presentation on ancient Scottish sheep farming practices. The talk, which could only last five minutes, was informative, witty, profound, and extremely relevant to software testing — all at the same time.
That is Isabel Evans for you. A highly regarded speaker in the conference circuit and luminary in the software testing world, she approaches the challenges of quality assurance with deep insight. Combine that with her thirty years in the IT sector and you get a rare, tour-de-force perspective — one that can tackle the daily challenges faced in QA from a broader, “big picture” position.
If you want to see Isabel speak in person (and you really should!), check out her upcoming events and master classes here .
Since then, I have developed several interests. I am interested in user experience, UX design, and testing, and about how you can take the engineering qualities in software and see how they merge into UX attributes like trust and flow.
Another area that I have worked in is organizational quality, where I explored organization excellence and improvement. IT is really just a tiny part of the picture; it is just a service into the rest of the organization. So how do we, as an organization, improve and build better things?
Within that, I developed an interest in team work and how people interrelate. That was partially driven by the fact that I am not particularly good at teamwork and networking myself. I realized that there are many other people in the IT industry who are not particularly comfortable with that either. It’s a bit of a stereotype, but sometimes those stereotypes are there because they fit.
So, I started looking at ways in which you can work with other people even if you are not necessarily comfortable doing that. A lot of the techniques companies put into place (for example, formal reviews) are about getting people to communicate and giving them a structure within which to do it. How do you develop those structures so that they are flexible and encourage people to communicate in ways that are positive?
All of that has come together into my main interest at the moment: The UX and usability of testing tools for testers. There is a big focus in the industry right now on the fact that test tools are not necessarily easy to manipulate. For a while, people have been saying that testers need to become more technical so that they can fit the demands of the tools they are trying to use and leverage them more easily.
So, it’s not an issue with testers only; it’s a whole UX problem within the software industry.
At the same time, development has gone from small focused teams working on a specific problem through to big projects with silo working and now coming back to people saying they need more frequent deliveries — essentially, the rise of Agile and DevOps.
I find it quite fascinating that it feels like we are just cycling.
It seems to me like there is a tension between a desire to create in a completely free sandbox and the need to control that space out of a desire to “become serious about it.” The problem is that if you control it too much, you damp down the creativity and people will eventually feel like they need to burst through into the “next thing” open sandbox. It’s a sort of evolution in how people deal with ideas.
Much of that fear now revolves around artificial intelligence, but the truth is that it still looks like we are nowhere near being able to relinquish the running of the world over to machines. At some point, if that arises, we may be in a new reality of perpetual leisure. But at the moment, all the automation we see requires human interaction or human direction. How long will that last?
When I was first in the industry, studying computer science, my final thesis was about whether machine intelligence would ever be possible. I focused on the subtopic of natural language processing. Back then, the idea that anything like Siri or Alexa would exist was laughable. It was not that long ago that people thought that kind of technology was simply impossible.
It’s the same with things like DevOps and continuous delivery.
The funny thing is that some people who were the earliest adopters of Agile are now saying that it has morphed into something that is not what they intended. As it becomes more widely adopted, it becomes standardized, there are certificates associated with it… it’s not new and exciting anymore. They are pushing things in place to make it safer, which makes it less appealing to the early adopters who will begin looking for something new. Agile needs to change and adapt in order to be agile.
So when we talk about that tension between the free sandbox and the need to be “serious” about doing something, we can identify the same tension in Agile and DevOps.
When you set up an agile co-located team, you will certainly have shared spaces, but it is also beneficial to have “caves.” Once you go into your cave, you can be left alone and work on something without needing to communicate. That gives you the rest you need to be able to deal with things in a common space. Remembering those human factors is very important because it is just as bad to force everyone to be in constant communication and interaction as it is to force people into silos.
Here is another question you need to consider in regards to whether communication is improved or not. Suppose you have set requirements that are stable and very complex. The best way to communicate those requirements could be to write them down and then study them very carefully. And if you are dealing with something that is stable and complicated and you have the time to do it, a formal review might just be a better solution than attempting to understand the requirements via Agile story cards.
There can be a “baby and the bathwater” issue with this sort of thing. The principle of Agile is that you are flexible to change how you do things based on the project or requirements. Not all the practices of Waterfall are bad; sometimes, they are the best approach, and it should be within the scope of Agile to realize and implement that appropriately. The challenge is recognizing what is most applicable to the project.
You don’t have to take a standard operation like Waterfall and make it bureaucratic for everyone. And you don’t have to take Agile and say that now we can never have documentation. You can blend it; you can empower people to make sensible choices for the situations that you are in. That is the idea of Agile.

Sentiment rank: 0.9

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