This week Kaybus saw a number of interesting stories looking at the enterprise collaboration space and the future of work. From a report from AIIM that found sixty percent of organizations think content analytics will "become an essential capability" within the next five years, to an article from Computerworld that explored how organizations can leverage data more effectively and a startup looking at the next steps in natural language processing, it seems the future of work and analytics are top of mind. The common thread here is that content continues to explode and the search tools of the past can no longer cut it. Let us know what you think by joining the conversation. Click on the link above to view all three articles.
Content analytics is not a new concept but its relevance and importance to business’ success is quickly becoming a reality to many organizations. Implementing content analytics is vital but companies are facing issues with lack of expertise and setting Information Governance (IG) policies before beginning the process. Doug Miles, AIIMs chief analyst, describes content analytics as “the single most valuable tool at an enterprise's disposal.” They view the first step in successfully implementing content analytics as trying to find the right people with the right expertise to manage it and all of its capabilities.
Organizations have a tremendous amount of data ready at their fingertips but the actual process of gathering and finding that amount of information isn’t structured for producing “data-driven decisions.” Ivan Chong discusses the top factors that prevent an organization from leveraging their data. A major issue Chong explains is that businesses rely on strategic analysis to structure their business processes and then monitor for how those processes are working. Organizations don’t make decisions based off readily available data which could allow them to add more value to their decision choices. Chong believes that in the future, organizations will no longer need to spend time tracking down where there data exists. Instead, data will be delivered to an organization in a contextualized, secure structure delivered directly to them, allowing them to spend time on implementing decisions and executing their business processes instead of searching for what they need.
Many of us are familiar with Facebook’s face recognition in photos or Google Now’s capability of answering the questions we verbally ask. But what comes next with the innovation of machines and their ability to understand natural language? AI startup MetaMind, recently published their research on their effort to teach online platforms to not just understand natural language, but to comprehend full paragraphs and even the sentiment of a message. Metamind is doing this through what is called “deep learning” and “episodic memory.” These two processes allow machines to have a short-term memory similar to what humans have and the ability to answer question exactly rather than providing multiple links.