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4 Data Points that Should be on Every Insurance Executive’s Radar

Aug 17, 2017 10:00:00 AM by John Mancini

 

Solve your Talent Problems with Digital Labor & Content Services Solutions

Every industry is facing accelerating disruptive challenges, but perhaps none more so than the insurance industry, one of the original “crossing the chasm" industries for content management. Consider the following data points highlighting the need for a more innovative approach to digital labor and content services:

1) “According to a study by McKinsey and Co., 25% of the professionals in the insurance industry will retire by 2018, leaving an enormous talent and experience gap in an industry that is already experiencing a worker shortage.” Property Casualty 360.

Implication: Unless organizations can begin to access and interpret all of the "dark" data they have accumulated over the past three decades, they run the risk that a significant source of knowledge will exit the building when the baby boomers retire. The key to competitive advantage does not rest on simply hiring more workers, but on maximizing the productivity of existing workers through technology.

2) “Millennials will comprise more than one of three adult Americans by 2020 and 75 percent of the workforce by 2025.” Brookings Institution.

Implication: Technology expectations in the workplace are about to change dramatically. Organizations with business systems that resemble those that might be found in a computer museum will find themselves at a distinct competitive disadvantage when it comes to hiring the best talent.

3) 57% (of millennials) say it is important to work for a company that provides flexibility to work outside the office. 48% say it is important to work for a company that is “very innovative.” While Gen Z is only slightly more familiar with the insurance industry than millennials, more than 60% of Gen Z and millennial respondents feel unfamiliar with the industry. The Future of Insurance: Bye-Bye Boomers, Hello Digital Natives.

Implication: Inflexible systems that are not designed for a modern mobile workforce will further exacerbate the brain drain that will occur as the baby boomers leave the workforce.

4) Only 4% of Millennials consider insurance to be an attractive industry in which to work, with many describing the industry as “boring.” The Hartford’s 2015 Millennial Leadership Survey.

Implication: Insurance companies face a perfect storm in the future battle for talent due to:

  • Legacy systems that have not been updated and not taking advantage of the latest cloud and mobile technologies.
  • A continuing set of compliance and regulatory obligations that are more complicated than the average industry and are not going away.
  • An older workforce than average that will soon retire.
  • A generation of new employees that has a negative view of the insurance industry.

Based on these data points, it is clear that something needs to change.

However, according to PwC’s 2017 Top Issues report, “the industry’s traditional conservatism and the dizzying pace of technological change has made it difficult to change.”

This “traditional conservatism” is based, in part, on the fact that insurance companies do face more significant content management challenges than many other industries.

Insurance organizations must deal with the reality that business must be transacted at the convenience and location of the customers’ choice, in a digital manner that is secure, accessible, and defensible.

Regulatory compliance, customer responsiveness, and operational agility are key to maintaining and growing their customer base. It is also vital for insurers to establish and maintain a solid information ecosystem, based on a strong IG framework that meets or exceeds the regulatory and legal compliance requirements. Most importantly, all of this must be done within a business context of multiple and inconsistent content and process management systems, both “native-born” and acquired.

The solution to this complex set of challenges is not business as usual.

While there are many parts to the puzzle of attracting millennials to the insurance industry, one part of the puzzle is providing an innovative work environment, engaging technology, and pushing systems to address the emerging set of analytics and machine learning opportunities.

While it may seem daunting, attracting millennials is vital for the industry’s success. RhinoDox CEO, Justin Ullman, puts it this way, “Let’s assume that the insurance industry can truly embrace a culture of rapid innovation and attract the talent needed to drive that. While the work ethic of millennials is often questioned, most people can agree that they are innovative, entrepreneurial and purposeful. Put that mindset to work and ask for their best ideas, and there isn’t a better demographic to help a legacy industry like insurance. As long as the right tools, processes and mindsets are in place, improvement is sure to follow.”

The mission-critical nature of many legacy systems means you cannot just rip them out without unacceptable carnage. The key to this evolution is embracing low- and no-code process solutions, semantic enrichment, modern approaches to enterprise search, and more flexible document databases to extract greater value out of existing systems.

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You might be interested in one of my recent e-books -- From Documents to Content to Data.

PS. It's free.

Click to register for The AIIM Conference 2017

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Topics: data, semantic web, ecm, big data, data analytics

A Trip to the Computer Museum

Jun 29, 2017 4:48:26 PM by John Mancini

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?

rhinodox - do new hires think your organization looks like a computer museum

 

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Topics: data, content management, ecm, big data, rhinodox

Guest Post - Five Keys to Leading in the Age of Analytics

Apr 17, 2017 2:31:31 PM by Andrew Wells


[Note:  This is a guest post by Andrew Wells and Kathy Chiang. Andrew Roman Wells is the CEO of Aspirent, a management-consulting firm focused on analytics. Kathy Williams Chiang is VP, Business Insights, at Wunderman Data Management. They are the co-authors of Monetizing Your Data: A Guide to Turning Data into Profit-Driving Strategies and Solutions. For more information, please visit www.monetizingyourdata.com.]

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Topics: analytics, big data, data analytics

11 Cool Quotes About Big Data

Nov 28, 2016 9:00:00 AM by John Mancini

11 Cool Quotes About Big Data

  1. Hiding within those mounds of data is knowledge that could change the life of a patient, or change the world.” (Atul Butte, Stanford)
  2. "Information is the oil of the 21st century, and analytics is the combustion engine” (Peter Sondergaard, Senior Vice President, Gartner)
  3. “War is 90% information.” (Napoleon Bonaparte)
  4. "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)
  5. Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.” (Geoffrey Moore, author and consultant)
  6. “The world is one big data problem.” (Andrew McAfee)
  7. “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)
  8. “The temptation to form premature theories upon insufficient data is the bane of our profession.” (Sherlock Holmes, fictional detective)
  9. "The most valuable commodity I know of is information."  (Gordon Gekko, Wall Street)
  10. "If we have data, let’s look at data. If all we have are opinions, let’s go with mine." (Jim Barksdale, former Netscape CEO)
  11. “Processed data is information. Processed information is knowledge Processed knowledge is Wisdom.”  (Ankala V. Subbarao)
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Topics: content analytics, case management, big data

10 Content Management videos you need to see

Oct 18, 2016 4:25:37 PM by John Mancini

Here you go!  10 ECM videos and their accompanying tip sheets and white papers.  

Click on the link to download the tip sheet or white paper; click on the video to get an idea of what they're about.

Feel free to share them with you friends and colleagues.

What's Happening with File Sync and Share - White Paper

Linking the Physical and Digital Worlds -- 6 Tips on Asset Lifecycle Information Management -- Tip Sheet

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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Topics: metadata, enterprise content management, ecm, big data, content management marketing

Big Data, Content Analytics, Information Capture and the Hype Curve

Aug 3, 2016 2:57:56 PM by John Mancini

Last year, Gartner created quite a stir by retiring the “Big Data” Hype Cycle from its popular “Hype” curve series (see Why Gartner Moved Big Data Off the Hype Curve).

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Topics: content analytics, mobile capture, big content, big data, capture

Content Analytics -- What does it mean to YOUR organization? 5 Key Obstacles

Mar 2, 2016 2:18:34 PM by John Mancini

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:

The capacity of computers to recognize meaning in text, sound or images has progressed slowly and steadily over many years, but with the constant arrival of faster computing resources, and the continual refinement of software algorithms, we are in a position where both the speed and the accuracy of recognition can support a wide range of applications.

In particular, when we add analysis to recognition, we can match up content with rules and policies, detect unusual behavior, spot patterns and trends, and infer emotions and sentiments. Content analytics is a key part of ‘big data’ business intelligence, but it is also driving auto-classification, content remediation and Information Governance, security correction, adaptive case management, and operations monitoring.

That smart content analytics can be of huge value to an organization is clear. But it is equally clear that there are a number of obstacles to content analytics adoption that need to be overcome. At the most recent meeting of AIIM’s think-tank, the Executive Leadership Council (ELC), the following obstacles were identified as particularly pertinent:

  • 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.
  • There is an on-going lack of specific use cases to really demonstrate value.
  • There is a splintering of data -- and data responsibility -- in the enterprise.

As with any emerging technology, there has been a wave of content analytics early adopters. The ELC agreed that it was imperative to learn strategic lessons from these early implementers, particularly focusing on:

  • Addressing data structure, tagging and permissions as close as possible to the point of creation.
  • Defining a clear set of corporate objectives for content analytics initiatives.
  • Always remember that the hardest part of a content analytics project is not the technology.
  • Done right, content analytics should drive you to rethink the questions you ask about your organization.
  • Position your content analytics initiatives as a means to both enhance customer value AND address information security.

In conclusion, a lot is happening in the world of content analytics, and it is happening very quickly indeed. But organizations must embrace the changes and the pace at which they are happening, as content analytics takes its place at the heart of many organizations.

Per Vladimir Lenin: “There are decades in which nothing happens and there are weeks in which a decade happens.”  Per ELC Leader Thornton May: “The status quo is perpetually on trial. But that doesn’t mean you can stand by and wait. It wasn’t raining when Noah started building the ark.”

Check it out; free download.

Download new Content Analytics report! FREE!

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Topics: content analytics, big data, elc

11 Cool Quotes About Big Data

Aug 20, 2015 7:30:00 AM by John Mancini

11 Cool Quotes About Big Data

  1. Hiding within those mounds of data is knowledge that could change the life of a patient, or change the world.” (Atul Butte, Stanford)
  2. "Information is the oil of the 21st century, and analytics is the combustion engine” (Peter Sondergaard, Senior Vice President, Gartner)
  3. “War is 90% information.” (Napoleon Bonaparte)
  4. "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)
  5. Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.” (Geoffrey Moore, author and consultant)
  6. “The world is one big data problem.” (Andrew McAfee)
  7. “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)
  8. “The temptation to form premature theories upon insufficient data is the bane of our profession.” (Sherlock Holmes, fictional detective)
  9. "The most valuable commodity I know of is information."  (Gordon Gekko, Wall Street)
  10. "If we have data, let’s look at data. If all we have are opinions, let’s go with mine." (Jim Barksdale, former Netscape CEO)
  11. “Processed data is information. Processed information is knowledge Processed knowledge is Wisdom.”  (Ankala V. Subbarao)
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Topics: content analytics, big data

11 Facts You Didn't Know About #Content #Analytics and #BigData

Jun 16, 2015 10:28:00 AM by John Mancini

11 Facts You Didn't Know About Content Analytics

The information below is from the new AIIM survey, Content Analytics: automating processes and extracting knowledge.

Fact #1 -- Content analytics is fast becoming a pivotal business tool, with six in 10 enterprises saying it will be essential within five years’ time.

Fact #2 -- Three-quarters of enterprises believe there is real business insight to be gained from content analytics, further highlighting its position as a technology that adds true value to an organization.

Fact #3 -- Content analytics – which analyzes and derives insight from inbound and legacy content - is also seen as increasingly essential to addressing risks associated with incorrectly identified content. Respondents felt auto-classification of content helps protect against security breaches, sensitive or offensive content, and exposure to compliance regulations. More than half of enterprises (54 percent) feel that their organization is at considerable risk from such threats. 

Download new free report on Content Analytics

Fact #4 -- Despite contact analytics’ potential, 80 percent of survey respondents have yet to allocate a senior role to initiate and coordinate analytics applications. This lack of designated leadership and shortfall of analytics skills is restricting the potential and holding back the deployment of content analytics tools, according to almost two-thirds (63 percent) of the research respondents.

Fact #5 -- Around three-quarters (73 percent) of respondents feel that enhancing the value of legacy content is better than wholesale deletion, while more than half (53 percent) say that auto-classification using content analytics is the only way to get content chaos under control.

6 MORE key facts about content analytics:

  1. Nearly two-thirds of respondents say that content analytics is either essential (17 percent) or something they definitely need (48 percent).
  2. Thirty-four percent of organizations are using content analytics for process automation, information governance, contextual search or business insight.
  3. Benefits from inbound analytics include faster flowing processes (50 percent), happier staff (32 percent) and improved governance (20 percent).
  4. Content analytics early adopters are already seeing the benefits, with 68 percent reporting ROI within 18 months or less.
  5. Most survey respondents expect to spend more on content analytics in the next 12 months.
  6. Incoming customer communications and help desk streams top the list for live or near-time alerting.
A few thoughts from Doug Miles, the author of the report:

 “We have seen increasing interest and adoption in recognition and routing of inbound content, automated classification of records and email, metadata addition and correction, and all of the improvements in access, security, de-duplication and retention that flow from this. But content analytics can offer so much more than this, with many applications and uses yet to come, and by 2020 will be one of the primary tools used by any enterprise.”

Check out our brand new Content Analytics course!

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Some other recent posts that might be of interest...

The research for ‘Content Analytics: automating processes and extracting’ was underwritten in part by Kofax, Rocket Software, SPS and OpenText.

The full report, which includes a number of recommendations for progress, is free to download at http://info.aiim.org/contentanalytics

The survey was taken using a web-based tool by 238 individual members of the AIIM community between April 17, 2015, and May 8, 2015.

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Topics: content analytics, information governance, analytics, big data

Stop Having Every #BigData Conversation Begin and End with #Hadoop

Feb 9, 2015 2:15:00 PM by John Mancini

How to Move Beyond Having Every Big Data Conversation Begin and End with Hadoop

Organizations of all sizes are struggling with how to extract insight and mitigate risk relative to the massive volumes of information and data that they're accumulating.  This isn’t just a question of big data—it is also a question of dark data, trapped in long-forgotten repositories, often without metadata. This is content and information that just begs for the light of day through semantics and analytics.

Big data initiatives to date have been almost exclusively driven by IT.  These initiatives are focused on the question of "how do we apply technology to manage large volumes of data?"  

New content analytics and semantic technologies allow you to move beyond the sheer volume question and ask "What kinds of questions and hypotheses should we be testing with our data?" In other words, how does insight into our data change the very nature of the questions we ask and hypotheses we form in our businesses?

How can your organization get business INSIGHT out of all the information you are gathering?  At AIIM15, find out how to change to conversation about Big Data from a conversation about Hadoop to one about the BUSINESS role of Big Data.  Get a preview of the INSIGHT sessions HERE.

Here's a fun ebook, free to all, covering some of the sessions at #AIIM15.

Download the free AIIM15 ebook.

Check out -- 23 Things I Wish I Knew BEFORE My First ECM/Content Management Project.

 

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Topics: content analytics, big content, big data

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