One of the buzz words getting thrown around a lot in tech circles these days is the “Internet of Things”. At first glance, it can seem both mysterious and vague, like some sort of futuristic platform where we can send physical objects over email. (Okay, maybe that’s not so futuristic. 3-D printing has essentially accomplished that). But no, what the Internet of Things, or IOT for short, refers to is the growing connectivity of all of our devices. Of course, this increasing connectivity leads directly to an increase in available data. When everything from your TV to your thermostat, your car to your phone, even billboards, becomes connected to the internet, you’re going to have readily accessible data chronicling almost every aspect of life.
While the standard privacy issues are always something to watch out for, this influx of data has the potential to streamline our lives through communication between devices. Your alarm clock will know your schedule, looking at traffic to estimate how long it’s going to take you to get to work, and adjusting your wake-up time accordingly. In turn, your car will start a few minutes before you leave on cold mornings. At the end of the day, your car will tell your thermostat when you are on your way home, and your house will heat up in time for your arrival, without wasting energy by staying on all day. It is this combination of cost savings and efficiency that keep this idea present in the minds of everyone from developers to science-fiction writers. Click here for an interesting infographic from Cisco detailing what may soon be possible. The data may be a few years old, but the ideas are still relevant.
While this completely interconnected reality may still be a ways off, the foundation is already there, and it is rooted in Big Data. In order to make this work, the world is going to need people to process this data. According to a recent McKinsey Report, the value of this information is apparent, but the manpower to process and analyze it isn’t there yet. This is why it is important to promote the importance of analytics and Big Data research within different sectors, such as the retail industry. This is where the manpower and capital to make this change reside. In the CPG industry, the value of analyzing Big Data has already been realized, and it goes by the name of Category Management. If a company hopes to be competitive, whether on the manufacturing side or the retail side, they need to be able to read this data and use it to know what the consumer wants, and where they want it. Learning Evolution has realized this, and has worked to bring the necessary training and knowledge to some of the world’s largest CPG companies, creating a win for the company and a win for the consumer. While the scanner data currently available is good, it will only continue to get more specific, both in terms of the shopper and the store, as the technology for collecting this data improves. You can rest assured that as the availability and utility of this data evolves, Learning Evolution will evolve along with it, bringing the best, most up-to-date training to the places where it’s needed most.