Cognitive science, business semantics, and human resources must come together to make IoT truly useful.
The Internet of Things (IoT) isn’t really about “things.” It’s more about the myriad disciplines that will make ubiquitous data, arriving across networks from a rapidly increasing number of sensors, safe and meaningful for humanity.
The Internet of Things Summit explored these ideas at Interop Las Vegas.
Human – Machine Interface
‘Safe’ and ‘meaningful’ aren’t guaranteed without a long look at the way the brain functions and how humans interact with machines in the IoT era.
Dr. Carmen Simon of Rexi Media began with a presentation on the cognitive skills that we possess and how those skills will allow humans to change how we see a world where data defines everything around us.
IoT will enable novel opportunities, but it can be hard to take a creative leap into the unknown.
“The brain needs more than beliefs to create action,” said Dr. Simon. “It needs tools.” We need to find and use the tools that will create new business systems to respond to the opportunities brought by IoT.
John Morris of Business Decision Models, Inc., continued the theme of human-machine interaction with his discussion of business semantics and how critical they are to the success of IoT projects.
First, the business case needs to be built around strong business semantics. In the IT world, that means improving project success by making business semantics “first class citizens” of your work.
Morris also talked about the challenge of how to fund IoT projects, which can get early interest thanks to the hype that surrounds IoT, but can fall off once people realize that there’s hard work ahead.
Morris noted, “Data is cheap and analysis is expensive.” This problem leads to end users drowing in information that doesn’t help them solve business problems. Business semantics are an investment that can’t be underfunded.
Lessons For CIOs
TIBCO’s Mark Palmer presented “8 CIO Lessons Learned from IoT Algorithmic Operations.” The lessons included the presentation of an IoT reference architecture that is centered around automation and event processing, as well as event-driven alerting and workflow management to control and manage real-time response to IoT-detected events.
Palmer also described the people challenges that CIO face as they introduce new automation technology to the business. This included best practices about how to start with automation and to make it non-threatening to operations staff,
He shared the example of a company that, over three years, used algorithmic automation to increase sales volume by seven times, while reducing support staff by 50 percent. But rather than cut its workforce, the company turned the rest of the staff into proactive, customer advocates and a sales function.
Finally, Palmer presented new steaming analytics programming tools, discussed how to interface streaming analytics with Hadoop and Spark, and described the role of in-memory data grid technologies for enterprise-class deployment of disruptive IoT systems.
IoT is far more than networks and sensors; it also requires a focus on business analysis, change management, and cognitive science to create real value.