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Data Analytics, Machine Learning Will Power an Enterprise Content Management Evolution
Aref Matin, CTO, Wiley
ECM, particularly for digital content and media publishers, is becoming a must-have tool to maintain a competitive advantage. Delivering richer atomized content that garners more value for customers, partners and consumers can enable a business to bolster its function, lower solution development costs and diversify the company’s product and services offerings.
While some content companies have foundational capabilities in place for smarter content classification, it is the proprietary tools that organize content and enable ECM to connect the dots between seemingly unrelated materials that will deliver the best results for the customer. Those companies that combine ECM capabilities with ML and analytics will enable their system to identify patterns in their existing content to predict what the user needs, thus rapidly developing automated capabilities.
But exactly how does this work? Is there a way to transform that information into a better product or service? Let’s say there are millions of questions that are classified with learning
objectives and millions of research articles with associated classification data. This data set, combined with the usage data, then becomes a highly valuable asset to accelerate the company’s ML capability. ECM will be able to summarize content, automate mundane content processing tasks, extract information from that content, then provide indexes and insights into content stored on the platform. Data analytics and ML are not just hot topics in content management—they are integral to a thriving ECM.
Automated Content, Smarter Content
There will be several ways that data analytics and ML drive content in the near future. For one, they will be able to originate content by drawing on existing content—and that will create new digital products. They will also make it possible for that automatically generated content to be better tailored to the needs of the end user.
ECM, particularly for digital content and media publishers, is becoming a must-have tool to maintain a competitive advantage
For example, if an online learner is not ready to take a specific course, he or she may better prepare for that by completing a remediation module. Data analytics can assess the student’s learning needs via assessment questions. Based on those results, the system will then formulate custom content consisting of specific remediation modules that can help the student prepare. This adaptive personalization fits exactly what the user needs and gives the learner the chance to enhance his or her understanding of the subject, but only if there is a strong enough system to craft custom content. When this personalized content is created, the ECM offers content providers a great opportunity to upsell. The student gets the correct remediation model to adequately prepare for the course, and the content provider can sell more products or services.
Here’s another example of how ML, analytics and enrichment can enhance a company’s offerings. In the case of a professor building content for a course, he or she can look into topics and allow the ECM to suggest relevant content. Based on analytics from other professors’ work, the instructor can further refine those suggestions. It will also let professors make a broader evaluation of how the class is doing and give valuable insights to propel the curriculum of the course going forward.
Data analytics generates better outcomes for businesses on the whole. For instance, clients in the education industry need to gauge the return on investment of content tools, so it is important to be able to determine how well the product is being received. Data analytics will give users financial insights into the products they plan on, or already have, purchased. Having data available, and the means to make data-driven business decisions based on it, can help generate new business or retain an existing customer. This creates another availability to upsell. But again, you have to have the additional products in place to upsell. That’s why a next-level ECM has to eliminate the need for manual content creation and transform itself into a content creator.
The Future of ECM
Right now, entering content for many companies is a manual task for the most part. Data analytics will fuel machine learning to be a productive content producer all on its own.
For us, ML involves feeding the machine more information. When it has more data, and the tools to process that information, it can draw up more scenarios and further customize results. Then it can predict and create user-specific content.
In the next three to five years, more companies will implement automated, curated content product models in the ECM—not just better search capabilities. Data, along with artificial intelligence (AI), is poised to take content to the next level. Businesses in all industries must implement these innovations to provide this next-level content. They cannot rely on manual processes for content creation and editing…even for devising metadata. In addition to written content, a more robust ECM can transform images into infographics that are automatically powered from the existing content. That’s powerful content, and it’s also a huge competitive advantage regardless of your industry.
Organizations who fail to evolve with a smarter ECM won’t be able to keep up with an industry that embraces this evolved model. And they definitely will not be able to create secure, customized products based on the needs of an individual. Companies that get ECM right will be the true disruptors and failing to do so will result in lost business. Content providers that embrace ECM evolution will be able to continue offering a top-notch service or product that is more relevant and more useful—progressing ECM to a whole new level.