Analytics will take center stage as the volume of data generated by embedded systems increases and vast pools of structured and unstructured data inside and outside the enterprise are analyzed. Companies will need to manage how to filter the huge amounts of data coming from the IoT, social media and wearable devices, and then deliver exactly the right information to the right person, at the right time. Analytics will become deeply, but invisibly embedded everywhere. Big Data is an important enabler for this trend but the focus needs to shift to thinking about big questions and big answers first and Big Data second — the value is in the answers, not the data.
Analytics techniques are growing in complexity, and companies are applying machine learning and predictive modeling to increasingly massive and complex data sets. Artificial intelligence is now a reality. Its more promising application, however, is not replacing workers but augmenting their capabilities. When built to enhance an individual's knowledge and deployed seamlessly at the point of business impact, advanced analytics can help amplify our intelligence for more effective decision making.
But even the case of analytics raises some usability questions:
How can insights be delivered to a specific individual performing a specific role at a specific time to increase his or her intelligence, efficiency, or judgment?
Can signals from mobile devices, wearables, or ambient computing be incorporated into decision making?
Can the resulting analysis be seamlessly and contextually delivered to the individual based on who and where they are, as well as what they are doing?
Can text, speech, and video analytics offer new ways to interact with systems?
Could virtual or augmented reality solutions bring insights to life?
How could advanced visualization support data exploration and pattern discovery when it is most needed?
This amplified intelligence creates the potential for significant operational efficiencies and competitive advantage for a company. Discovery, scenario planning, and modeling can be delivered to the front lines, informed by contextual cues such as location, historical behavior, and real-time intent. As a result, intelligence is put to use in real time, potentially in the hands of everyone, at the point where it may matter most. The result can be a systemic shift from reactive "sense and respond" behaviors to predictive and proactive solutions.
Data analytics is in its early days, but the potential use cases are extensive. The medical community can now analyze billions of web links to predict the spread of a virus. The intelligence community can now inspect global calls, texts, and emails to identify possible terrorists. Farmers can use data collected by their equipment, from almost every foot of each planting row, to increase crop yields.
Leveraging smart glass hardware, analytics, and back-office tools, a global oil and gas company created a pilot platform for amplifying the effectiveness of rig workers. The goal of this effort was to deliver hands-free job aids, decision support, and workflow automation to individuals working in remote locations.
The platform works as follows: When field equipment malfunctions on an oil rig, sensors detect the issue and proactively notify a nearby field service agent via smart glass. Analytics then delivers critical diagnostic information on the issue. This information, augmented by powerful analytics capabilities applied to sensor and other relevant back-office data, includes step-by-step instructions for repair.
Using a laptop or a cumbersome paper manual to triage and troubleshoot malfunctioning equipment might require service agents to remove their gloves and step away as they look for answers. However, smart glass makes it possible for them to view needed information in real time and on the spot— thus enhancing worker efficiency, accuracy, and safety. Moreover, with a simple wave of the hand, the agent uses a gesture control armband to initiate a video conference with level-three support back at the home office. The remote expert can see what the agent sees, talk to him or her through the procedure, and even provide annotated instructions that appear on the agent's augmented display.
The agent can also send data to a central database. With a head nod or tilt, he or she can maintain a log or "checklist" of completed activities and create new notations via voice as the repair is being made. That repair log then becomes available to the next technician who services the field equipment. Critical information isn't lost in stacks of paperwork; it becomes digitally organized and accessible to those who need it.
Use cases for platforms like this are not limited to oil and gas field workers. At distribution centers, for example, drivers often conduct vehicle inspections prior to turning the ignition. In many instances, drivers must look for vehicle and manifest-specific details — details that would be almost impossible to memorize without years of training. Virtual instructions accessed via smart glass can guide drivers through inspections, accelerating the entire process and increasing its accuracy and effectiveness.
The combined power of smart glass technology, analytics, and back-office systems (knowledge databases or warehouse management systems) can help companies in almost any industry or sector realize the vision of a better informed workforce by offering information to the right people, in the right manner, when it counts.
For the IT department, data analytics offers a chance to emphasize the role it could play in driving the broader analytics journey and directing advances toward use cases with real, measurable impact. Technically, these advances require data, tools, and processes to perform core data management, modeling, and analysis functions. But it also means moving beyond historical aggregation to a platform for learning, prediction, and exploration.
Jeff Bertolucci, "10 powerful facts about big data," InformationWeek, June 10, 2014, http://www.informationweek.com/big-data/ big-data-analytics/10-powerful-facts-about-big-data/d/d-id/1269522?image_number=4
Deloitte University Press, Intelligent automation: A new era of innovation, January 22, 2014, http://dupress.com/ articles/intelligent-automation-a-new-era-of-innovation/
by Ovidiu Mățan
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