The sheer size and variety of data traversing today’s networks are increasing exponentially. This highly distributed data is generated by a wide range of cloud and enterprise applications, websites, social media, computers, smartphones, sensors, cameras, and much more — all coming in different formats and protocols. IoT contributes significantly to this rising volume — often by generating a high frequency of relatively small amounts of data. Our survey respondents predict strong growth in all types of connected assets (facilities, vehicles, and production equipment) driven by IoT. In fact, nearly 90 percent expect the amount of data transmitted by their networks to increase “somewhat” or “significantly” over the next five years. There are myriad IoT use cases that generate large amounts of operational data:
This wealth of widely distributed and often unstructured data is arriving at an accelerating rate — 90 percent of world’s data was created in the last two years.
Only by addressing all three can organizations turn raw data into information and actionable insights.
Whether it is in the cloud or at the edge, IoT data must be analyzed to identify actionable insights that can be used to create better outcomes (such as from process optimization or improved customer engagement). Without this critical step, data remains just “data.” Insights then need to be embedded into efforts such as process re-engineering and broader business transformations.
Analytics-driven insights will drive the opportunity for process change and optimization. In many cases, these insights will foster transformative rather than incremental changes in business and operational processes. For example, our survey respondents indicated that IoT has the potential to fully automate up to 50 percent of their existing manual operational processes.
The implications of this opportunity are difficult to overstate. In most cases, a company that automates 50 percent of its existing manual processes will look nothing like it does today.
Consider the following hypothetical scenarios:
While many organizations have not advanced as far as these examples on the IoT maturity curve, we are beginning to see process improvements of this magnitude. Amazon, for example, is currently employing scores of autonomous robots in its huge Seattle warehouse, which could help the online retail giant save as much as 40 percent on fulfillment costs.
When organizations optimize their processes for IoT, they can achieve a number of important business outcomes, including: