The future for information management is bright - at least that is what the feeling was at the AIIM 2018 Conference held in sunny San Antonio April 10-13.

Intelligent Information Management

12 months ago, AIIM added their voice to the “enterprise content management system vs Content Services” debate by throwing a new term into the mix - Intelligent Information Management. They even went as far as to rename their organization as the Association for Intelligent Information Management. Furthermore, the overall message at this year’s conference was to build on this ideology and to add some meat to the bones. So what did that look like?

Get a tip sheet from AIIM on what does information management modernization mean

A key finding of that research found its way into AIIM President John Mancini’s keynote during the conference, which is that many of the challenges facing organizations today are related to scale. These include:

  • The amount of information hitting organizations
  • The ever increasing speed that it hits them
  • The myriad of places where that information can be stored within the business
  • The increasing diversity of new content types (such as video, images, audio and so on)
  • The ever growing size of that new content.

Collectively, this can be thought of as Big Content.

What is Big Content?

Some might say, “This sounds just like Big Data for content!” Well, not quite.

Big Data was really a technology - a set of tools and techniques to process and get value from large datasets. Some might say that in its infancy it was a technology looking for a problem - or a set of good use cases.

That is absolutely not the case with Big Content - for 2 key reasons.

  1. Big content is a definition of the challenge - not an attempt to be a solution.
  2. Whereas Big Data struggled to find good use cases, Big Content is being driven by use cases. End users are defining what they want to do with their information based on their Big Content challenges - and they’re looking for technology to solve those challenges.

And this is where content services can come to play, or more specifically where a Content Services Platform (CSP) can be used to address the challenges of Big Content, to deliver the promise of Intelligent Information Management systems. Let me give you an example.

Modern Problems Require Modern Solutions

For a long time, ECM promised to be the solution to all of the information management challenges within organizations. So what happened? Well, the ECM approach was based on all content (and content-driven processes) within an organization being placed and managed from within a single repository. That failed for a number of reasons, but a major one is that it ignored data - the stuff that comes with content to give it a context. They left that data in CRM, ERP and other line of business applications, and required custom links to be made with each and every one of those systems. Sometimes this happened, but more often than not, this just resulted in the proliferation of more and more data and content silos. This added to the complexity for IT and to the overall insanity faced by end users trying to locate information across these systems.

CSPs change that by both providing standardized connections to external systems and repositories, and by not requiring content and data to reside within their system (although interestingly some “legacy” ECM vendors at the AIIM conference were still insisting that content must be stored in their system - we’ll see how they get on with that).

The “Manage content in place” approach means that users can access all of the information and content they need from one central hub. IT can get value from their legacy investments by providing contextual access to the data that was previously locked in these systems (75% of organizations say that solving this problem is vital according to our research). In addition, over time they can strategically migrate away from those legacy systems in a controlled manner and on their own timeline. This flexibility removes the need for the big bang approach (that is both expensive and very risky), and can potentially save many thousands of dollars in maintenance and support costs.

Perhaps most importantly, with an underlying platform that unifies data and content from across the business, organizations can finally start solving their content chaos challenges by providing personalized solutions to users. How? Via the low code, rapid application development tools provided by Nuxeo and other CSP vendors.

Learn more about ways to solve legacy modernization challenges in our whitepaper.

These tools provide drag and drop environment that allows for the creation of solutions that connect content, data, and processes together to address the specific needs of end users.

That could be in claims management, HR onboarding, brand management, event management, integrated records management, or really any part of the business. I heard anecdotal evidence at the AIIM conference from a large enterprise that their average end user has seven (yes, SEVEN) applications open at any one time to do their job, cutting and pasting information between them as part of their custom content management workflows. Imagine the productivity improvements, the reduced likelihood of errors being introduced as part of that process, and simply the general increase in job satisfaction that the user would get from being able to bring together the relevant information and content from those seven applications via a centralized access hub.

This is what a Content Services Platform can do, and this is the real world manifestation of Intelligent Information Management in my opinion. Working smarter, not harder - and getting value from the investments you’ve already made.

Every single end user I spoke to at the AIIM conference was experiencing the challenge of Big Content, but none of them had solved the problem. By the time of the 2019 AIIM Conference next year, I’m confident that many of them will (with the help of Nuxeo) be sharing a very different story.

Frequently Asked Questions

Big Data was really a technology - a set of tools and techniques to process and get value from large datasets. Some might say that in its infancy it was a technology looking for a problem - or a set of good use cases. That is absolutely not the case with Big Content, for 2 key reasons:

  1. Big content is a definition of the challenge - not an attempt to be a solution.
  2. Whereas Big Data struggled to find good use cases, Big Content is being driven by use cases. End users are defining what they want to do with their information based on their Big Content challenges - and they’re looking for technology to solve those challenges.