The AIIM Blog
Keep your finger on the pulse of Intelligent Information Management with industry news, trends, and best practices.
Intelligent Information Management (IIM)
Maybe it was a bad idea to start a blog post after dinner because I have one thing on my mind… ICE CREAM! Are you craving it, too, now? Well, grab a bowl and read on. Trust me; this does eventually tie into Information Management.
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I would like to introduce myself to those who do not know me. I am Anthony Peleska, CIO of Minnesota Housing Finance Agency and Chairman of the AIIM Board of Directors. As a CIO and technology leader, I became involved with AIIM to help myself, my team and my organization understand and tackle the challenges we face with people, process, information, and technology. The insight we have gained and partners we have developed through AIIM have helped us increase our profits, decrease our technology budget spending and mitigate risk at a variety of levels. Our success has fueled a passion that I want to share with others, to help them tackle the business challenges they face today through involvement with AIIM.
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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.
Digital Transformation | Intelligent Information Management (IIM)
#1 -- Know where the puck is going. Danielle Galmore, Steelcase: “Technology moves faster than companies, as a rule. Be cognizant of what is happening and ready to adjust if new technology or new needs arise. Your first project may have to pivot if too much time has elapsed, and relevancy is lowered.”
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Digital Transformation | Intelligent Information Management (IIM)
Consider the following: “The speed of current breakthroughs has no historical precedent.” --Klaus Schwab, World Economic Forum, 2016 “For the first time in history, the world’s leading experts on accelerating technology are consistently finding themselves too conservative in their predictions…” --Steven Kotler “Uber, the world’s largest taxi company, owns no vehicles. Facebook, the world’s most popular media owner, creates no content. Alibaba, the most valuable retailer, has no inventory. And Airbnb, the world’s largest accommodation provider, owns no real estate. Something interesting is happening.” --Tom Goodwin, Havas Media, in Techcruch What the heck is going on, and what does it have to do with Information Professionals?
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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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