The moment a new product is released, it’s on its way to obsolescence. Something bigger, faster, cheaper is just around the corner or your competitors will come out with something exactly the same, nullifying your market lead.
Nowhere is this more apparent than in the consumer technology market. Phones from just a few years ago now look clunky and old-fashioned.
In most industries, being good at new product development and seizing a market opportunity before competitors, is the difference between success and failure.
But new product development is a risky business and littered with failures. Just think of Coca Cola’s C2 coke spin-off in the US, the Sinclair C5, the Segway…
You are never going to be able to obliterate all the risk, and neither is that desirable – you can’t innovate without taking a risk. But what you can do is make the best informed decisions you possibly can to lower that risk.
And that’s where data and the analytics that go hand in hand with it can make a huge impact.
The right insight into data can improve the efficiency of the product development process, shortening time to market, stripping out costs, improving performance and most importantly of all, giving customers the kind of product and experience that they want.
The data available to inform product decisions is growing not only in volume, but also in breadth. Alongside traditional sources of data, organizations also need to listen to what their customers are saying on social media platforms.
But the next great source of information will come from the products themselves, as embedded sensors record exactly how the product is actually being used, rather than people’s opinions of how they use it (and as any GP who has asked someone how many units they drink a week or their weight will tell you, people are not that reliable).
This kind of product data includes data from embedded sensors in everyday devices from cars, coffeemakers to fridges.
Gartner predicts that by 2020, there will be 26 billion of these Internet of Things (IoT) units in place, each sending information. Naturally, there is a whole industry emerging to take advantage of this new market. Gartner anticipates that product and services will push revenue to over $300 billion by 2020.
That’s a hell of an opportunity, so not surprisingly companies are looking at ways to explicitly cash in on that expanding market. GE, for example, is reported to be investing $1bn to develop what it calls “industrial internet” – the ability to connect people, data and machines.
The applications of this are huge. By knowing how many times every day people go the fridge, use their coffeemakers or slam on their brakes, the R&D department will be able to feed that information into future product design. For example, they could make their products more durable because they’d underestimated usage patterns.
It gives organizations the power to use that information in the next product development cycle. Those sensors could also be tweaked to provide customers with information, along the lines of existing driving sensors or utility usage monitoring devices.
The amount of product usage data that potentially be collected is mindboggling. Huge potential, yes, but it is not without its challenges. Setting aside the not insignificant issue of how you will actually capture and use that information for product development or enhancement, there’s also a serious ethical considerations. The problems of securing this data and the privacy issue of whether people actually want you to have this data have yet to be sorted out.
More data from more channels means more complexity and that puts more pressure to keep that data secure. And it creates additional storage and management requirements.
What this new interconnected world means is that companies will have more personal data on how people use devices, potentially at the individual level.
We’ve become used to loyalty cards that glean personal information and we’ve become used to CCTV cameras, but will this be a step too far? Or will we think that the benefits – for example, better, more personalized services or better management of our devices, outweigh our big brother concerns?
One suggestion is that consumers will be given the option to opt-in or out of allowing their data to be used by suppliers. Or even to allow that data to be used, but at a price.
I guess the answer lies, ironically, with big data and analytics themselves. Companies will use analytics, which some refer to as the analytics of things and others as the IoT analytics, to establish exactly what is and what isn’t acceptable for customers.
Regardless of the finer points of IoT, it is well on the way to a fridge or a coffeemaker near you and you’d best work out how it can work for your business.
If you haven’t, as yet, then you’re in good company. A Computing Technology Industry Association (CompTIA) survey revealed that while just over half the respondents thought the opportunities warranted the hype, roughly the same percentage, 48%, saw it as more hype than substance.
But today’s hype has a tendency to become tomorrow’s necessity.