by Rob Schilling, Space-Time Insight
Situational intelligence applications correlate and analyze multiple disparate streams of data from the Internet of Things, such as real-time data from fleets of construction equipment.
In a recent Gartner survey, 63 percent of executives said the Internet of Things will have a significant or transformative impact on their business over the next five years and beyond. Twenty-six percent of respondents said they plan to establish a Center of Excellence for the Internet of Things within five years.
Does this sound like you? The Internet of Things-the ability to easily connect nearly anything in the physical world to data networks-is a shift in how we shape, understand and interact with our entire environment, from monitoring oceans to communicating with sensors the size of a grain of sand. We are entering a new era when intelligent devices in cars, homes, businesses and factories can generate data and communicate. But how to make sense of all that data?
Through smart technologies such as smart meters and synchrophasors, as well as accommodating new technology trends such as smart thermostats and mobile, digital customer service, utilities already are wrestling with how to gather, store, analyze and visualize large amounts of data. Utilities can struggle with deriving value from analyzing just a single silo of data, such as meter reads. A challenge of the Internet of Things for utilities lies in analyzing multiple, disparate sources of data to answer big and useful questions such as:
•Where are the things I care about? (Trucks, field crews, customers, substations, etc.)
•What is the condition of the things I care about?
•What behaviors do my customers exhibit?
•What will happen next?
•What’s the best action?
The answers can’t come from just one type of device or source of data. No such single device or source exists. By itself, adding more devices to the Internet of Things doesn’t help with important questions like these. What’s needed is the ability to analyze and visualize in real time the data from the multiple disparate data sources across the Internet of Things.
Situational intelligence is a new class of software designed for extracting value from the multiple, disparate data sources spawned by the Internet of Things. Situational intelligence works by correlating disparate sources from across an organization into common patterns and offering intuitive visual analytics for quickly making sense of complex events to support faster and better decisions. Examples of situational intelligence in leading utilities around the world include:
•Tracking tens of thousands of utility vehicles in real time to increase utilization, driver safety and fuel tax rebates;
•Analyzing individual and collective risk across millions of transmission and distribution assets to improve capital efficiency; and
•Combining the output of millions of smart meters with other data sources such as customer billing, weather, calendars and more to identify energy theft.
To excel in the Internet of Things, utilities must consciously mature their analytics capabilities. They need to move from simply analyzing what happened using standard reports, tables, charts and scorecards toward understanding what is happening in real time and what is likely to happen. For mature analytics that can work across the multiple streams of data coming from the Internet of Things, utilities will need to tackle new, complex processes and concepts such as streaming analytics, anomaly detection, machine learning and more.
Performing these new levels of analytics is only part of the answer. The results of those analytics must be readily accessible and understandable across the utility. Workers from the meter shop to the CEO need access to useful, appropriate analytical information that improves their work on behalf of shareholders, ratepayers and the wider community.
Utilities became economic linchpins by transforming lives through the safe, affordable and reliable delivery of power to drive life-changing appliances and devices. Utilities can continue to thrive as long as they have a strategy for providing value to customers based on insight from all the data that will come from the increasing number of connected devices. Situational intelligence applications provide a proven platform for analyzing multiple sources of data in real time and delivering insights that drive improved service on behalf of all stakeholders in the utility.
Rob Schilling is CEO of Space-Time Insight, where he has guided the company’s strategy since 2011. Previously he was senior vice president and general manager of the SAP Utilities vertical in North America and the Western region. He also held roles as chief operating officer for SAP Japan and executive positions at Oracle, Siebel Systems and Comergent Technologies.