The AIIM Blog
Keep your finger on the pulse of Intelligent Information Management with industry news, trends, and best practices.
We use Case Management to improve the way we serve our partners and customers by grouping all of their related information together, front-and-center, in an easy to access “case.” At the heart of serving customers is the daunting task of trying to put all of the information included in a case to work by making a decision or an informed action. But, in a world that seems to triple its information output every year, this task is becoming harder and harder to manage. So, how can you possibly know all there is to know to run your business?
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Analytics | Big Data | Capture and Imaging
Last year, Gartner created quite a stir by retiring the “Big Data” Hype Cycle from its popular “Hype” curve series. According to Betsy Burton at Gartner, “We’ve retired the big data hype cycle. I know some clients may be really surprised by that because the big data hype cycle was a really important one for many years. But what’s happening is that big data has quickly moved over the Peak of Inflated Expectations and has become prevalent in our lives across many hype cycles. So big data has become a part of many hype cycles.”
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Making an ECM implementation successful requires planning and attention to detail. The best way to create the right solution is to identify organizational goals and priorities. Learn how to manage a successful implementation in our free guide.
Content Analytics has hit the industry in a big way. According to our research, over 75% of enterprises say that there is real value to be gained from content analytics -- in business insight and risk mitigation. This new technology is rightly taking its place amongst the corporate toolset, but that same research study shows mixed progress for implementation. Business insight (or big data / big content) projects are still in something of an early-adopter phase. However, interest and adoption for recognition and routing of inbound content, automated classification of records and email, metadata addition and correction is rising. To help clear up the confusion and fear of implementation, let's look at the tip implementation tips for Content Analytics.
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As with any relatively new software application like Content Analytics, interest tends to be high, while progress is mixed. AIIM's independent research study on the topic garnered some interesting responses. Consider the following stats from the study (Content Analytics: Automating Processes and Extracting Knowledge): A quarter of our respondents feel that they are stuck in a world of paper processes. 37% either have no one tasked to investigate, no mandate from above, or no budget to proceed (or a combination of these) For 23%, a start has been made, but progress is slow, or of mixed success. 11% are underway and encouraged by the results. 4% are already showing a return on their investment What's leading to these mixed results? This same research helped us identify 5 common barriers to user adoption of content analytics. Let's take a look at each of these in greater detail. Definitions of what content analytics actually is are poorly understood and inconsistent. There is still too much focus on technology and not enough on business value; who truly are the buyers, influencers, and key stakeholders, and how are they different from those of yesteryear? The pace of technology change is accelerating and running ahead of the ability of organizations to consume it. We lack specific use cases. There is a splintering of data and data responsibility in the enterprise.
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Deriving meaning and insight from the different forms of content held and managed within most organizations is fast becoming one of the number one challenges and priorities for many in business. AIIM’s June 2015 Industry Watch Content Analytics: automating processes and extracting knowledge, revealed that six in ten enterprises believe that content analytics will be essential within five years’ time:
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“Hiding within those mounds of data is knowledge that could change the life of a patient, or change the world.” (Atul Butte, Stanford) "Information is the oil of the 21st century, and analytics is the combustion engine” (Peter Sondergaard, Senior Vice President, Gartner) “War is 90% information.” (Napoleon Bonaparte) "Big Data will spell the death of customer segmentation and force the marketer to understand each customer as an individual within 18 months or risk being left in the dust.” (Ginni Rometty, CEO, IBM) “Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.” (Geoffrey Moore, author and consultant) “The world is one big data problem.” (Andrew McAfee) “I keep saying that the sexy job in the next 10 years will be statisticians, and I’m not kidding.” (Hal Varian, chief economist at Google) “The temptation to form premature theories upon insufficient data is the bane of our profession.” (Sherlock Holmes, fictional detective) "The most valuable commodity I know of is information." (Gordon Gekko, Wall Street) "If we have data, let’s look at data. If all we have our opinions, let’s go with mine." (Jim Barksdale, former Netscape CEO) “Processed data is information. Processed information is knowledge, Processed knowledge is Wisdom.” (Ankala V. Subbarao)
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