Two respected professionals offer perspectives about new ways business intelligence will likely be used in the calendar year to come.
If one asks the experts, the use of data-processing software to "learn" new ideas -- loosely called cognitive intelligence -- will be going mainstream in some business verticals in 2016.
By definition, cognitive intelligence is the capability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly and learn from experience. Humans are born with this; machines need humans to make them "smart." But humans are finding new ways to insert intelligence into IT machines wherever and whenever possible for business purposes.
A cognitive intelligence system such as IBM Watson can scan scads of data and process it far faster and more accurately than any human can. It also can offer various solutions based upon various use cases, and then lay all of them out to be decided upon by a human.
Having this capability within an IT system enables C-level leaders to use all their business data to its best purpose: to look at the big picture of the business and its market; see the important trends, and use only facts in the data to make informed decisions that enable the business to grow.
At the end of each year, eWEEK
receives and selects a number of prediction submissions from IT professionals, offering their takes on trends and predictions in various sectors of the tech world. In this article, we offer some points of view from two respected pros about new ways business intelligence will likely be used in the calendar year to come.
From Chris McLaughlin, Chief Marketing Officer, Enterprise Content Division, EMC:
--Beginning in 2016, smart machines and cognitive systems will form the foundation for automating knowledge work, and play an expanded role in enterprise content management -- not only in speeding access to information and better personalizing customer experiences, but also in automating routine knowledge worker activities.
--Smart machines will play a critical role in customer service and engagement.
Not only can Web content be personalized, but cross-channel customer service interactions can be similarly personalized and highly automated. Gartner Research predicts that, by 2017, "70 percent of customer communications will be digital, contextualized and consumed on demand via multiple channels, including the Web, mobile devices and social media." My prediction is that, beginning in 2016, many of those communications will be machine-generated, and that by 2020, smart machines will entirely automate many routine customer communications and service interactions, effectively mimicking human-to-human interactions to provide engaging customer experiences while dramatically reducing costs.
--Smart machines will automate how new content is captured and ingested
. One of the ongoing challenges many companies face with digital transformation is that much of their existing knowledge and information is still analog, or trapped in traditional paper forms. Beginning in 2016, machine learning will begin to play a critical role with document-capture technologies, automating how paper-based content is captured and ingested into corporate knowledge bases. This will not only take tremendous cost out of traditional back-office capture activities, it will also greatly expand the pool of information or knowledge that is available to the organization for reuse, analysis and decision-making.
--Smart machines will increase knowledge worker productivity.
A knowledge worker spends much of his or her day searching for existing content and creating new content. Beginning in 2016, we will see expanded applications of cognitive technologies to help knowledge workers find critical and relevant information. Smart machines will be used to observe user behaviors, understand user roles, and to proactively deliver critical information to knowledge workers, eliminating valuable time lost each day in searching for content.
But the opportunity for automation doesn't end there. Beginning in 2016, smart machines will also be applied to accelerate new content creation. Smart content curation will move beyond simple recommendation engines, automating how even complex documents are created. Routine reporting activities, like regulatory and financial submissions, will become increasingly automated. Existing content and knowledge will be intelligently sourced, new document templates will be automatically created and instantly provided to knowledge workers. And, by 2020, many routine reports and communications will be entirely automated.