Here is the world we want to live in: When we get in our car, we don’t have to put a key in the ignition; we just press “start” and we drive to work. When we get to work in the morning and sit down at our desks, our computing devices automatically contextualize to our user profiles and all of our content is readily available. We can easily hand off voice, text and video communication between devices and communication protocols. When we walk down the street for lunch, we get contextual ads based on our known preferences from area restaurants competing for our business. When a group of us goes to our neighborhood pub for happy hour, the music changes because we represent an influential minority and one of the TVs switches to a sporting event we are likely to want to watch. When we go home and pull into the driveway, the garage door opens automatically, and the lights turn on according to our user profile and time of day. When we go to the restaurant, bar, night club, sporting event or theater, we form an ad-hoc social network of proximally-related people, all with wireless devices in our pockets.
Lately, we've been seeing a lot of snark about the IoT. The Internet of Shit? I'll be first to admit that it's pretty bad right now, and it's worthy of the satire, but I can't help but think that many people jumping on this bandwagon are missing the big picture: This is only a phase.
WHY IS IT LIKE THIS?
Companies that make things have decided to make “Internet of Things” things and the product managers of those Things think putting the Internet in their Things means putting the current version of the Internet in their Things. And this is how you end up with a refrigerator that streams Pandora music or a cooktop that can give you Facebook updates. (These are real products, and I won’t even bother you with a link.) When you do this, you aren’t building smart things, you are building dumb things. You are building things that people laugh about behind your back.
At some point, you have to cost-justify your analytics project. “We know we need this, but we have to make the case to the accountants.” Sound familiar? You’re not alone.
You are making a decision to make better decisions with data, and those decisions need to make financial sense, otherwise you shouldn’t make the decision. While you cannot know your full ROI until you implement, making data-based decisions is better than whatever you are doing now.
If you are a TL;DR kind of person, here you go: It is less expensive than you think and it is measurably more valuable than you imagined. So if you just Googled “IoT analytics ROI Analysis” for your project, this post is for you.
A study released by Deloitte Canada a few months ago showed that 82% of more than 300 CMOs they surveyed have been asked to interpret consumer analytics data and admitted that they felt unqualified to do so based on previous experience. This is a problem made bigger by the fact that 70% of respondents in the study said their companies expect marketing decisions to be based on analytics and that they are expected to treat data as the “voice of the customer.” It is no wonder, then, that almost 70% of the same respondents reported that they expect agencies to play a key role helping them analyze and interpret data.
I recently wrote about how IoT Analytics is the new CRM. The point was that if a CRM system exists to give you insight into your customers who are using your products, then IoT Analytics gives you insight into the products themselves.
For product companies looking for an edge, IoT Analytics is an important component, and this phase of the IoT evolution will continue for at least a decade, but IoT Analytics is at the heart of a revolution that extends far beyond that. Here is what is going to happen:
Hello, product-based company of some sort! Whatever you are building is going to be awesome. One of the main reasons it is going to be awesome is that its connectedness and its ability to provide real-time analytics data is going to give you and your customers a new dimension of insight.
If you are embarking on an IoT project and you are reading this, you already have a sense that the data generated by your devices is valuable and must therefore be captured, analyzed and leveraged for your (and your customers’) benefit. This is true. You are also likely to see a conflation of the following concepts: IoT, Big Data, and Analytics. I guess that makes sense to some degree; billions of connected devices are going to generate big amounts of data, so clearly a big data solution is needed, yes? No.
If the Internet of Things is comprised of smart, connected objects, then wearable technology is certainly a visible and exciting category that enables people to understand the promise of the IoT. At the intersection of analytics and wearable technology is the quantified-self, the result of the output of data derived from sensors you wear that measure what you do.
Do you know which vendor can actually provide analytics for your particular IoT deployment? The data analytics industry is huge, and there are many subcategories. The most familiar to most people are web analytics and mobile app analytics, but there are companies serving practically every vertical where there is measurable and actionable data. Financial services, social media, server infrastructure and shop floor automation all have nuances that require a highly specialized approach to analyzing data.
We humans like to think about time in eras. We define styles and trends of the past neatly into decades. We talk about the “Industrial Revolution,” the “turn of the century,” the “21st Century” and the “Information Age.” With the Internet of Things finally becoming a reality, I recently looked back at one description of our next big thing as the “Post-PC Era.”