Information Management Blog

The AIIM Blog

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big data  |  bigdata  |  digital transformation,

Role of Big Data in Human Resource Management

Those who have been practicing Human resource management for years knows the importance of relying on data analytics for creating an enhanced work culture or else they might lag behind that of other departments. Many of you tend to hold the purse strings that HR deals with people, they do not require dealing with large-scale data efforts and have gone to the back of the queue as a result. With the ever-growing technology advancement, Human Resource professionals have started embracing the future: data analysis.

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Compliance and records management  |  big data  |  governance  |  intelligent information management  |  security

Bridging the Gap Between Security Awareness and Action

The amount of data stored on electronic systems today is exploding and growing at an exponential rate. Data breaches, privacy concerns, and growing e-discovery costs continue to evolve how organizations approach controlling their business data while balancing worker productivity. Aged or poor data hygiene can further increase organizational inefficiencies, in aggregate costing billions annually.

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14 Steps to a Successful ECM Implementation

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.

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big data  |  bigdata  |  digital transformation,  |  podcast

[Podcast] A Small Problem with Big Data

We have a small problem with Big Data...the majority of us just don't completely understand it. Sure, we've all heard the term "Big Data" - but I'm willing to bet if I asked a room full of people what it was, I'd get puzzled looks and shrugged shoulders from about half the room...and I'm sure I'd lose most of the other half of the room if I followed up that question by asking how to leverage big data for real business value.

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big data  |  data  |  digital transformation,  |  information professional

Four Ways the Data Scientist Has Evolved to the 21st Century

In 1989, I took my first decision sciences course, and started coding in SAS at the age of 20. I greatly enjoyed pulling discoveries buried within mounds of data, although and even small datasets had many discoveries back then. At the root of every model I’ve built, even the simplest, was a solid understanding and foundational rigor of statistical theory. When computing simple statistics or developing descriptive models, I thought through the math behind the model and how this would impact the formation, application, and interpretation. It was about 30 years ago when I started my decision sciences journey, and I’m still applying techniques and building models to empirically solve problems, answer questions, overcome challenges that improve, reduce error, or otherwise benefit a situation. Over the past three decades, I’ve noticed trends and shifts, an evolution of sorts, in the foundational underpinnings of development and application within this interesting profession. I’ve come to the following conclusions that illustrate the evolution of the data science function over the past few decades:

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big data  |  digital transformation,  |  digitization  |  office365  |  records management

Don’t Let Data Overwhelm You

Are you finding yourself overwhelmed by the amount of data you have to manage? While it's great to stay up with the latest technology, digital transformation can sometimes leave people feeling like there was a document "explosion" in their department. Not to worry, we're here to help.

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Blog Feature

big data  |  data  |  data analytics  |  ecm  |  semantic web

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

  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. ----- You might be interested in one of my recent e-books -- From Documents to Content to Data. PS. It's free.

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