Content Agility Bolsters Automation and Innovation in Business Workflow

Call it data, information, assets or knowledge; content is the string of characters, digital 0s and 1s, that support us in how we work, collaborate, learn, communicate and make decisions.  Content can drive a better customer experience, improve worker productivity or transform a business.

The term “agile” has been applied to “agile development” and “hyper-agile cloud architectures.” Now it’s time to consider a context of “agile content” that fuels business automation and innovation by breaking down rigid documents into more nimble and reusable micro-content.

IDC defines content agility as the ability to employ content in any type of format (structured or unstructured text documents, images, video, audio, social streams, etc.) aided by artificial intelligence to influence and optimize the creation, ingestion, accessibility, transformation, analysis and utilization of that content. An example may be an “intelligent customer account opening” process, which could be modernized as an interactive, interview-based experience where components of the supplied answers are used to feed and customize different aspects of the customer onboarding experience.

There are two main tenets underpinning agile content. The first is fluidity — content should be malleable for reuse in various contexts, adapted to various screens and locations, and aggregated for analysis or insight. The second precept is that content is managed as atomic data blocks (micro-content) that can be assembled or processed at an elemental level. Examples include:

• Assembling a new purchasing agreement from a list of micro-content options from a library populated with successful articles, sections, subsections and enumerated clauses used in past agreements.

• Charging a subscriber fractions of a penny (micro-payments and micro-content work hand-in-hand) to view a webpage without advertisements, where the page content is driven by content block permissions and metadata.

• Inserting patient visit details (doctor name, timestamp of appointment, action taken) as a new encrypted block on a patient’s single medical record blockchain, viewable by multiple authorized entities and providing an immutable audit trail to a complete patient medical history that spans years and different medical providers.

From guided interviews replacing traditional forms capture, to adaptive assembly of common documents like contracts or invoices, adopting an agile content approach is possible today.Click To Tweet

As consumers, we are already partaking in agile content activities. We ask Alexa a question using short, context-dependent phrases and expect back an immediate and accurate answer the first time. The query, “Who sings this song?” requires real-time audio capture, natural language processing and access to a database of lyrics, titles and musicians. Why can it not be the same for business questions?  It is likely because the knowledge base needed to support it is not available yet. The question, “Who owns this account?” asked to Cortana or messaged via Slack would require context of what an “account” is and the role of the inquirer. Cortana could identify the voice as a known marketing user and deduce she wants to know which salesperson in Salesforce.com was last assigned to the ACME company. Difficult, but not impossible to derive.

Embracing micro-content and an agile content methodology for business agility

When it comes to business agility, IDC found that 23% of organizations looking to disrupt their traditional content-centric workflows will embrace an agile methodology to enable continuous, predictable delivery of content management improvements and analytics-based optimization. Additionally, 53.6% of IDC survey respondents expect to invest in artificial intelligence to provide insights into content usage, personalize the user experience for maximum relevancy and augment decision making within content-driven business processes.

It’s time to redefine the “document” in terms of micro-content. To get to this stage, however, content must be broken down from whole PDF documents, scanned images or large publications into bite-sized chunks. Organizations are comfortable creating metadata around the content, but it is usually applied to the whole asset and not detailed to the specific page, concept or image the descriptor is referencing. Adjusting to a micro-content strategy can bring agility and efficiency in the creation, management and publication of many types of content. For example, machine learning and natural language processing can assist in automated granular metadata assignment. Additional benefits arise when you bring content management to the cloud with the advent of new agile cloud content apps.

For example, say a particular content management vendor supports the creation and storage of componentized content via an XML schema. What this means is that a medical trade journal publisher can curate current events — for instance, a measles outbreak — and then tag and store the symptom and treatment data separate from the casualty rates, regions impacted and other details of the virus. As treatments change based on new findings, only the treatment-specific content block needs to be updated and republished. Editors benefit from not having to lock the entire “document” and can publish their updated content block independent of others who may be editing the measles topic in parallel. Additionally, doctors benefit from using their mobile device to request and receive the latest measles treatment without the need to speed-read through numerous pages of immaterial background.

Becoming an information-driven organization

Content agility is an important factor to becoming an information-driven organization. To facilitate this digital transformation, organizations should consider these key tactics:

• Create a micro-content strategy to capture, tag and publish micro-content blocks assisted by a unified taxonomy accessible by the entire organization.

• Develop and promote an organizational culture that treats information as a key asset to be continually updated and shared.

• Use machine learning to assist in the auto-categorization, auto-tagging and extraction of value from data sources into a shared repository.

There are numerous examples of micro-content making its way into modernized business processes. From guided interviews replacing traditional forms capture, to adaptive assembly of common documents like contracts or invoices, adopting an agile content approach is possible today. Add in new machine learning automation and there will be a massive change in the way content is managed and decisions are made in the future.