For the last few years, the business world has been laser-focused on one thing: data. Companies like Google and Facebook are making billions of dollars in profits from the data they collect, while companies like Netflix and Amazon are gaining market advantages through their analytics programs. They started doing so because it just made sense to monetize the over 4.4 zettabytes of data that had already been created by 2013.
Now, with the Internet of Things (IoT) set to accelerate the creation of data to unprecedented levels, experts predict that over 79 zettabytes of data will exist by 2025 – a scant five and a half years away. For businesses, that means their existing big data operations probably aren’t anywhere near sufficient enough to handle the volumes of data to come. It also means that they don’t have very much time to remedy the problem, and they risk losing a major advantage due to insufficient big data planning and infrastructure.
Creating An IoT Data Proof-of-Concept
The first thing that businesses should invest in to prepare for the coming flood of IoT data is to build a solid proof-of-concept project to figure out what IoT data might be of use, and what will be a waste of resources to collect and store. That means forecasting what IoT devices will produce usable data and which won’t. For example, manufacturers will have to determine what machine sensor data might be useful to improve efficiency, lower production costs and aid in equipment maintenance. With that task done, it’s time to run a trial program and continue to iterate to improve results. Only then can the business figure out what their needs will be in terms of infrastructure.
Investing in Storage Systems
With a good idea of what kind and volume of data will be collected via IoT devices, the next area of investment should be into backend storage solutions to accommodate the new data that will be on the way. First, a data management plan must be considered to prevent all of the new valuable data from becoming a major liability. In addition, the proof-of-concept should have also made it possible to craft a logical and cost-saving data retention policy to inform infrastructure spending and to avoid any overallocation of funding – which will be essential to making sure an IoT strategy doesn’t turn into a costly boondoggle.
Making Organizational Preparations
One of the unheralded parts of big data and IoT business integrations is just how complex it can be to prepare an organization to use them. Still, it’s a task that can make or break any data strategy, since failing to do so robs the data of its’ biggest value proposition: the ability to guide sound business planning and decision making. To avoid such a fate, businesses must take steps to adopt a sound IoT-focused business culture. Without it, any future IoT data strategy will likely have a profoundly limited effect. Businesses should begin by beefing up budgets for employee big data education and build out policies that establish how and when new data sources and insights are to be used to guide operations. That will make it possible to ease the changes in more slowly and achieve an organizational buy-in that is critical for success.
Time to Get to Work
With the clock already ticking, businesses don’t have much time left to put the above initiatives into action to prepare for their IoT futures. Those that do will reap the rewards by being ready to hit the ground running when the time comes, while those that don’t will find themselves in a fruitless game of catch-up. I’m sure it’s apparent which of those two outcomes is preferable. All that’s left to do now is to get to work.