What worries us most is often not what actually gets us—that is, causes us our biggest problems. The enormous human capacity for worry can result in productive focus and taking action. Artificial Intelligence (A.I.) inspires our imaginations, invokes our worst nightmares and touches our deepest fears. Near-term, it threatens to take away our jobs and leave us with no way to feed our families.
Unfortunately, I’ve had a few recent encounters with our healthcare system. As you would expect, I paid attention to the recordkeeping process. The spectrum ranged from paper to born-digital and has me thinking about my health records in a new way. If you’re interested in the backstory, you can read it on my personal blog. Suffice it to say, last Friday, I needed to establish an account with a local hospital’s online health portal. My expectations were low. Healthcare professionals have always impressed me with their medical knowledge and talent, not so much with the way they embrace technology. In general, I was pleasantly surprised. I wasn’t surprised that the results from test taken at 2:00 AM were not available at 1:00 PM. I was surprised that the results from an MRI I had in May, from a radiology clinic affiliated with this hospital, were available. I found it reassuring to know that I was being given access to same record that my providers use. I wondered what else is in there. For example, I can see the MRI report, but can my ENT see the images of my brain? I had the thought that I want to consume all my healthcare through this network – being able to access these records has marketing value. Today, this technology serves the providers and is extended to me. The fact that I like having access to this information means I have to add a non-medical attribute to my healthcare decision making process, or I have more work to do. I have the option to add other caregivers to the system. I like the fact that I can grant them that permission, but I worry that they will have their own systems that they will want me to use. I worry that we’ll end up with medical Kayck/Trivago-like middle men linking various healthcare systems. I worry that that will inevitably expose my health records to more companies. You see the problem? This is information about me but it's not my information. This realization made me think of the AIIM ELC meeting I attended in June where Robert Kahn, a man who was instrumental in the development of the Internet, spoke about Distributed Digital-Object Services. He described what may be the end game for Intelligent Information Management – when information belongs to the person, process or device that collects it or whose condition it represents. What if my medical information existed as a distributed object that had its own storage, knew who I was, who my medical providers were, who my health insurance company was, and what if these entities could access and update that record as necessary, and as permitted by me? I can almost hear the gears turning in some of your heads – How would this work? How would it be secured? This would make a lot of today’s technology obsolete – I worked with distributed objects in the late 1990s. This can work. Robert Kahn, a man who once said during an interview that: "…the development of the Internet was a learning experience..." says it will happen. As we explored the future of Information Management at that ELC meeting, we discussed the ways cybersecurity, regulations and emerging and disruptive technologies like blockchain, AI and machine learning, will all play roles in that future. The summary paper will be available soon, and since it will include the experience from the European ELC, I can’t wait to see it. About today's guest poster - Dan Antion is the Chairman of the AIIM Board of Directors. He has spent almost 40 years developing information management systems, in a wide variety of industries. For the past 30 years, he has been Vice President, Information Services for American Nuclear Insurers, where he is responsible for data, content, and systems development across a broad range of platforms. His opinions do not represent American Nuclear Insurers, AIIM or the AIIM Board of Directors. You might also be interested in... Are you ready to take the Certified Information Professional (#CIP) exam? Canon Norway Standardizes on CIP
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.
Never have the risks of disruption – and the rewards of nimbleness and agility and creativity -- been higher. SaaS solutions to enterprise problems – with far less aches and pains to business types -- have swept through corporate America. For years, Boomers had the benefit of numbers – after all, they still represented the majority of the workforce and dominated the C-Level within organizations. By 2020, those pesky Gen X, Y, and Z folks will be 80% of the workforce. The Boomers – and the institutional knowledge they have – will largely be gone. The question facing many organizations -- How do we create a business technology environment for the millennial majority that looks a lot less like a technology museum? Think about how out-of-control things have gotten relative to the core business challenges of managing, controlling and utilizing information. So how do organizations make sense of all this? How do they begin to update their core infrastructure – and minimize the amount of chaos that will inevitably ensue? How can they optimize the productivity of their human capital? The answer lies in 1) more effective management and utilization of the content and information housed – often locked away -- in existing systems; 2) rationalizing multiple content systems; and 3) moving from legacy to more modern platforms. Ironically, this problem is more challenging in industries that were leaders in the first wave of content automation. In the late 1990s, Enterprise Content Management became a mainstream technology (at least for large organizations) by first focusing on early adoptors eager to automate high-value, mission-critical, and document-intensive processes critical to gaining competitive advantage. Examples of these initial “breakthrough” processes include the new drug application process in the pharmaceutical industry, claims processing in the insurance industry, and check processing in the banking industry. The challenge of modernizing this legacy investment is somewhat akin to trying to change the wiring in a house while the power is still on. Find out more in my new Tip Sheet -- Do New Hires Think Your Organization Resembles a Computer Museum?
“Content is data in context.” Don’t quote me on that. I didn’t say it. I don’t know who said it. To be accurate, I should say that I don’t know who said it first. Lately, whenever I hear that statement, it’s in the form of “They say, content is data in context.” “They.” I suppose they are the people who are good with content. My forty years of experience tell me that there aren’t many of them. I think I know why. It’s the ‘context’ thing. “A train leaves Washington, D.C. at 8:10 am, traveling to New Haven at 88 miles per hour...” The dreaded word problem – that’s data in context. The people who are good with content, want to tag that as: ‘travel’ ‘railroads’ ‘train’ ‘Washington’ ‘New Haven’ and probably ‘America’ and perhaps ‘Vermonter’ and ’56.’ The people who aren’t good with content, simply want to know when the train will arrive in New Haven. They don’t like word problems. They’ve never liked word problems and they were never good at separating the data from the relevant context – ‘relevant’ because Mr. Gadzooks, the Algebra teacher always included superfluous context to throw us off. You know, “John was boarding the train with two suitcases…” – and, let’s face it, in the real world, we just want the data and we don’t want to work for it. The real world replaced the context of that statement with a timetable. Find your train. Look for Washington to see the departure time and then look for New Haven for the arrival time. Easy-peasy. Just like every spreadsheet in every organization. But, that was yesterday. Today, we have an app for that. Well, AMTRAK has an app, but so does the Metro North – which train are we on? Do we have that app? Is it up-to-date? Do we know how to use it? It doesn’t matter. Apps are almost yesterday. Tomorrow, for many of us, today, we just ask Siri or Alexa or that Google girl “what time does the train get to New Haven?” But wait, that wouldn’t work. Siri, Alexa and, what’s the Google person's name? Oh, right, she doesn’t have one. That doesn’t matter either; they can’t answer that question. They need more information. They need the date. They need to know that you’re traveling on AMTRAK and they actually need to know that your leaving from Washington, D.C. They need enough data to put you in context – to put you on the Vermonter, AMTRAK Train 56. Sure, they might be able to use your location and determine that you’re in Washington, but they still need to know when you want to travel, because the Vermonter is one of several trains traveling between those two cities, each day. They need enough information to put you in context so they can extract the relevant data from a database. Alexa, Siri, the Google woman, and every other information system we use won’t always need as much information from you in the future, but only if we do our jobs well. As Information Professionals, a.k.a. content people, we need to realize the new ways the information we collect, curate and store is being used. We need to create/support easy, consistent and reliable ways to extract data from the information while continuing to meet the traditional information management requirements that have shaped our industry. The role of information is becoming more important. The demands on information systems are becoming more critical. The expectations of relevance, accuracy and availability of information are growing. We need to make sure information can meet the challenge. You might also be interested in... Are you ready to take the Certified Information Professional (#CIP) exam? Canon Norway Standardizes on CIP About today's guest poster - Dan Antion is the Chairman of the AIIM Board of Directors. He has spent almost 40 years developing information management systems, in a wide variety of industries. For the past 30 years, he has been Vice President, Information Services for American Nuclear Insurers, where he is responsible for data, content, and systems development across a broad range of platforms. His opinions do not represent American Nuclear Insurers, AIIM or the AIIM Board of Directors.
Digital Transformation requires that organizations meet a new generation of process challenges. Holistic customer journeys that embrace multiple sub-systems and processes, often owned by different departments, require a different way of looking at process problems. Looking to specific industries, consider some of the following (per Michael Croal from Cornerstone Advisors). Healthcare: Patient Tracking: Admission to Discharge Patient Billing: Service/Supply to Bill Satisfaction Patient Surgery: Diagnoses to Follow-up Energy: New Production: Land Acquisition to 1st Barrel Refining: Raw Material to Final Product Insurance: Claims Adjustment: Initial Contact to Final Resolution New Policy: Request for Quote to Renewal Banking: New Customer/New Account: Sale to 1st Anniversary Consumer Loan Delivery: Application to Lien Perfection Mortgage Loan Delivery: Lead to Investor Sale Commercial Loan Delivery: Expression of Interest to Annual Review Collections: Past Due to Current Loan Servicing: Boarding to Collateral Release The next generation of business problems require a 360-degree view of information and access to this information – both data and content, in geometrically increasing volumes, and regardless of where it is stored. Organizations can no longer afford to look at data management and content management disciplines in isolation. While all of the above processes are vastly different, their core characteristics say a lot about why the past bifurcation between data management and content management is becoming blurred and strained. BOTH Data and content are needed to solve these problems. The scale of the data and content challenge is increasing geometrically, and will increase even more rapidly with the internet of things. The data and content needed to solve these problems does not reside in a single repository or system, but is scattered throughout the organization. The data and content to solve these problems – assuming you can find it -- in many cases does not inherently contain sufficient metadata to make these information assets either understood or actionable. Traditional ETL (Extract, Transform, Load) approaches focus on bringing big data and content into a common data warehouse. These are proving to be too expensive, too complex, and too slow. Traditional relational/SQL databases are straining to meet big data demands and new semantic, NoSQL approaches are arising. And the world of content management is being transformed by concepts and disciplines from this new world of data. Get my e-book, From Documents to Content to Data for more details. You might also be interested in... What if your enterprise search was better and more encompassing? -- The power of semantics
Since the 1980s, relational databases have been used to store business information. They were a huge step forward over hierarchical databases, which organized data into rigid tree-like structures with connections between data elements defined by the links in the structures.