You’ve read countless predictions for ECM in 2020. Here are the two that matter the most.
As a principal consultant at Doculabs I spend most of my time working with clients in insurance, financial services, healthcare, and manufacturing. I’ve helped with a wide range of content management projects and enjoy the diversity of philosophy I encounter at each client.
A quick review of industry blog postings from late 2019 reveals a myriad of predictions for 2020. Most imply that our universe of information management will be dramatically and irreversibly transformed in the coming eleven months! Everyone will be focused on implementing sophisticated content services platforms, powered by micro services, while armies of citizen developers take IT matters into their own hands. Traditional ECM will never only be spoken of again except as a silly "I remember when..." story that we tell to make the interns laugh.
Such trends have exciting future potential to improve the way we work. But a lot of our clients aren’t building that next-gen platform right now, because they’re busy with digital transformation, massive migrations to Microsoft Office 365, dismantling legacy ECM, and other tactical initiatives.
So why should you care about ECM predictions and trends? Because they help you assess the direction of your individual vision, provide validation when you’re already following the best-known path, and gauge the maturity of your own roadmap against your peers.
So, which of these 2020 trends may be the most important for the work you’re probably doing right now? I think there are two in particular: artificial intelligence and low-code applications.
Important Trend #1: Artificial Intelligence
Artificial intelligence, or AI, is one of those terms that is liberally applied in all types of contexts. While some tend to think of AI as something that is “coming soon,” it’s already part of many of the business platforms that you use and manage in your organization today— especially Microsoft Office 365. It’s important to understand the role that AI will play, as you plan your longer-term rollout of the platform.
The Office Graph is the most obvious implementation, where AI learns about a worker’s activities, objectives, interests, the people and processes associated with their work activities. These learnings are subsequently applied by helping knowledge workers find the information they need, locate subject matter experts, reduce the time and uncertainty associated with validating information and creating content. AI in Office 365 applications can anticipate a worker’s needs, and proactively assist.
Knowing how AI functions— and how it is being implemented over time, in the Office 365 product suite — can inform solution-building within your organization, especially as Microsoft improves the integration of the myriad of applications and content stores. Also, many aspects of AI and machine learning can be tailored. To get the best results, understand the scenarios when it works best for you, and where it is failing, and fine tune the inputs and outputs.
I believe that artificial intelligence and machine learning capabilities are not reserved for the largest companies, and the technology does not just apply to the most-used productivity applications.
To validate (or challenge) my assertions, I contacted two content management solution and services firms – M-Files and Nuxeo – both of whom have long histories of delivering ECM solutions while continuing to innovate as times change.
- Chris McLaughlin, the Chief Product & Marketing Officer at Nuxeo, suggests that practical examples of artificial intelligence and machine learning are already delivering real business value especially when used for common use cases of OCR and text extraction. Many organizations rely heavily on document capture solutions for the ingestion and processing of paper forms, applications, invoices, inbound letters and countless other types of communications. These systems typically require a team of human operators that monitor and adjust the processed documents to ensure they are ingested, processed, and routed correctly. Artificial intelligence and machine learning reduces the reliance on human operators and has the potential to increases the accuracy of document recognition to 100% in some cases.
Chris also notes that forward-thinking IT leaders will begin to develop and deploy their own, highly customized AI models to gain even more meaningful insight into their specific industry, process, and content. I couldn’t agree more— especially because I know from experience that hardly anything in our business is “one size fits all.” Take the example of information architecture; when we help an insurance industry client create an enterprise metadata framework, it is tailored to their environment and culture, even though intuitively it may seem that all big insurance organizations manage information similarly.
- Greg Milliken, the SVP of Strategic Alliances for M-Files widens this view by asserting that AI and machine learning is not only beneficial, but critical to efficiently absorbing the accelerating growth in volume of information being generated and ingested by our organizations. Having the ability to automatically classify and deliver information in a context useful to information workers will drive process improvements, productivity and compliance on a massive scale.
For me, this makes perfect sense. The classic example for almost any industry is managing a large collection of documents that related to a specific topic, customer, or project. Today, most organizations rely upon users to provide this classification and association by naming, organizing and storing (and sometimes tagging) each file in a particular way. It’s a model as old as the file room days and is universally unreliable. AI and machine learning to the rescue?
Greg reminds us that if we can “...reduce or eliminate the dependence on manual interaction, and automatically classify, relate, secure and process information while also ensuring accuracy, it offers the potential of huge improvements in productivity, quality and compliance.”
Important Trend #2: Low-Code Applications
In 2019 there was a lot of discussion about “low-code” platforms, which has a wide range of definitions and usage scenarios. In general, the term refers to using a platform to solve a business problem by creating a solution out of modular, pre-made components, avoiding much of the traditional coding, increasing developer productivity and reducing the time it takes to create a software application. Gartner even has a Magic Quadrant dedicated to low-code platforms.
We often hear clients use the term “low-code” in contexts where there is no developer involved at all—such as automating a process using a toolkit designed for the non-programmer. This new “Citizen Developer” has access to capabilities that extend far beyond making macros and forms to automate simple tasks like data collection; in some cases, a business user can create a solution and render it as a mobile application, ready for use by a team.
In Office 365 this capability has existed for years, but only recently became more focused, as indicated by some updates and rebranding. For example, Flow, an Office 365 application that enables the creation of—you guessed it—workflows, has been enhanced and renamed Power Automate. Power Automate’s capabilities are impressive but seem paltry compared to the similarly-named but much more extensive PowerApps that is also part of the Office 365 suite.
Many of our clients overlook these tools when embarking upon their Office 365 journey, focusing on the bigger problems of application configuration and content migration, and rightfully so. But I believe that these tools—with the right guidance, governance and training—could be a useful way to quickly deliver solutions to your business customers, while avoiding the traditional methodologies of solution development. I’m also cool with empowering users with the ability to solve their own problems when it makes sense, and when the risk is low. But that’s a topic for a separate article!
Tapping once again into the field experience from the experts at M-Files and Nuxeo, they both agree that in the coming years, low-code tooling will become mainstream in Office 365 as well as all the major content services platforms. Greg Milliken from M-Files predicts that as enterprises make the move to external content services platforms, most will need to port dozens of content applications that they have built over the last 20 years, while continuing to build new solutions to address emerging content-driven business needs (which, to Chris McLaughlin’s point, will almost certainly involve AI and machine learning) .
Regardless, time to market will be critical as always, and the strongest content management vendors will borrow a page from the low-code playbook, bringing to market new visual design tools to enable customers to quickly configure and deploy new content applications.
Predictions are fun, and help us level-set, self-check, and can inform or validate the direction you’re taking your organization in the future. The work you are doing today can benefit, too. By learning from what others are doing, you can be more innovative in the solutions you create for your customers – creating more flexible solutions that will become even better when trends like AI and low-code interfaces become more mainstream.