By Cruce Saunders
Purpose: This paper analyzes the challenges confronted by existing content teams and proposes a future-state framework for orchestrating enterprise content services with a content intelligence program that spans disciplines and organizational silos. [A] proposes an organizational model to support content intelligence, that incorporates distinct Content Strategy, Content Engineering, and Content Operations practices within an overall Content Services Organization (CSO). To achieve an effective return on assets as part of an overall content strategy, enterprise content teams should build a unified management approach under a coherent Content Operating Model (COM).
Method: Content engineers at [A], the content intelligence service, evaluated publishing team structures and workflows across large-scale enterprise publishers, including in-depth investigations at seven of the largest global companies.
The approaches advocated in this article are a result of the [A] findings and resulting recommendations from these in-depth analyses.
Results: New practices are necessary across the enterprise, established within a continuum between Content Strategy, Content Engineering and Content Operations. A collaborative strategy and set of standards must be organized across authoring groups.
Conclusion: Directed by a new Global Content Operating Model (GCOM), a Content Services Organization (CSO), powered by the triumvirate of Content Strategy, Content Engineering and Content Operations, provides a balanced and effective path for large-scale publishing organizations to embrace the intelligence revolution.
Keywords: content strategy, content engineering, content operations, omnichannel publishing, content models
Enterprise content teams should:
- Become unified under a common management approach – a content intelligence program
- Share clear goals, patterns, and standards
- Build a chartered, cross-functional CSO that incorporates Content Strategy, Content Engineering and Content Operations practices
To achieve coherence across content sets, we need:
- Active participation from multiple content-producing groups
- A content supply chain consisting of content authoring systems, systems of record, and shared schemas represented by a Master Content Model® and Master Semantic Model
- To support integrated, personalized customer experiences and modular, standards-based content objects
All content business value emerges from content that:
- Flows between producers, consumers, and robots
- Moves and transforms, empowering organizations and customers
- Becomes machinable and assembled into multiple renderings
We are standing in the midst of a significant revolution in the management of organizational knowledge and its expression as content. This revolution touches the publishing and engagement systems that handle content, the organizational structures and roles that produce and manage content, and every other part of the content ecosystem. Enterprise leaders face three mega shifts happening concurrently: a content revolution, a customer experience revolution, and an enterprise knowledge revolution.
Everything that relates to how we structure and communicate knowledge is changing, along with how that knowledge is consumed and used by humans and machines. For simplicity’s sake, let’s call this fundamental set of changes the “Intelligence Revolution.”
Working with any form of enterprise content, whether technical communications, marketing, learning, or any other purpose for which groups author content, most organizations use systems and methodologies that evolved organically over several decades. And, even on cusp of the year 2020, many teams still operate using 1990’s approaches to content. For example, critical source content may still be authored in an entirely unstructured form within Microsoft Word, manually being copied and pasted into a CMS within a WYSIWYG “page layout metaphor” then delivered into inflexible formats such as fixed ‘static’ HTML renderings or PDFs. Such static workflows were highly functional in the 1990s and 2000s but have become woefully inadequate today.
In addition to content inflexibility, enterprises also experience organizational inflexibility that make it difficult to accomplish the kinds of collaboration necessary to craft modular, reusable forms of content. Organizational roles, structures, and workflows have not kept up with the ever-changing demands on content.
Due to the exponential growth of, and demand for, volumes of relevant content, publishers now need smaller and smaller containers of content chunks structured and metadata-enriched for personalization and multifunctional use across customer surfaces.
The new content surfaces include, for example: personalized experiences by market or segment, voice conversational content experiences via assistants like Alexa, text-based chatbots, automated marketing and email pipelines, on-platform content for software and game companies, the Internet of Things (IoT), augmented reality (AR), and wearables.
So, teams have been compelled to innovate radically different approaches to build to all these new surfaces. Yet, content professionals face a stark dichotomy between resources and requirements. Content creators have been asked to produce more than ever before, faster than ever before, all the while fundamentally changing publishing practices and workflows. And yet, teams have not been given the executive support, fiat, or resources to succeed. And organizational structures themselves have not caught up to the reality of omnichannel customer experience needs.
This is a time of profound soul-searching for enterprise publishers as industry revisits how everything is done. For the past 15 years, even within technical communications alone, teams have needed to reinvent themselves multiple times (Stevens, 2018). Now, the industry again finds itself amid reinvention, as old systems bog down and traditional organizational charts prove themselves outdated. The new world order of content has yet to arrive, and this intermediary period has motivated many in the industry to introspection, experimentation, and renovation.
Leaders have only just, in the 2017 and 2018 timeframe, begun sponsoring various initiatives aimed at enabling contextually-rich content experiences to intelligently flow to an ever-expanding landscape of devices and consumers over the past two years, an observation based on investment patterns among [A] enterprise clients.
Generational shifts in customer behaviors and expectations may be a key factor driving the move toward new content-driven, cross-channel customer experiences. The first wave of fully “digital people” (starting with Gen Z born from mid 1990s to the early 2000s) continues to enter the workforce. Millennials will represent nearly 75% of the workforce by 2025 (Luchs, 2017). These customers interact natively across multiple devices and consumption contexts and demand maximum efficiency to accomplish transactions.
Shifting customer demands, the risks of unintentional misinformation, the rate of market change, new conversational formats for interaction, and the explosion of new channels and devices all contribute to a demand for speed and ability within content sets. Because all content value emerges from motion (content that flows between producers, humans, or robots), our organizations must now evolve to support content intelligence and flow.
The intelligence revolution inevitably is leading to structural changes within organizations, or at the least more committees. Everyone seems to see the need to re-engineer process and people workflows, in part, because the reality of the brokenness of today’s status quo has become painfully evident as teams struggle to just barely keep up.
This article reviews a few emerging system models for organizational design as well as new alliances across teams and proposes a continuum of practices that need to exist within a new Content Operating Model to embrace the intelligence revolution: Content Strategy, Content Engineering, and Content Operations.
An Omnichannel Content Explosion
Many people within content-producing departments feel they are “dog-paddling” on a wave of unfathomable and unconstrained content factor growth.
In [A] findings, echoed in a 2018 Forrester study sponsored by SDL, internally reported frustrations include (Forrester, 2018):
- Inability to keep up with the growing appetite for content
- Inability to keep up with support for new content formats/types
- Complex workflows and approval processes
- Lack of automation/mostly manual processes
- Content delivery that is poorly coordinated across teams or business units
- Inability to keep up with the growing volume and complexity of content delivery
- Lack of structure/definition around content translation
Due to the nature of productive content, which forever seeks new channels, there are thousands of variants of content renderings for every new surface and digital space that emerges. What used to be finite documents are now many versions of articles, campaign landings, search results, social promotions, emails, product information resources, promotions, offers, commerce stores, syndicated publishing consumers, support topics . . . and endless copies of each.
As illustrated in Figure 1, at least seven (7) factors of content dimension drive variation from destination to delivery.
Continuing to publish in the traditional manner turns intelligent, creative humans into copy-and-paste robots moving content from one format to another, one variant to another, one language to another, one channel or system of record to another, and from one part of the workflow to another. As Figure 1 shows, the sheer scale of manual touch points in common content management is frightening. We can easily become slaves to manually inserted content. Why is there so much manual transformation and insertion? The simple fact is that, today, many enterprises still have neither standard schemas nor shared tags or terms. Content often resides in product-based or divisional silos with entirely unique content management and practices.
Unnecessary manual and unwieldy steps, like copy/paste, not only deplete creative resources, they insert “static” content that will not update automatically when source files are modified. Publishers and content stakeholders from different divisions copy/paste, often from multiple versions of the same static source files. Many managers still attempt to control semantic terms in spreadsheets, rather than creating centralized systems of record for sharing these critical tagging standards.
An insidious amount of “toxic” static content can gradually creep through an overall treasury of content assets like fast-growing ivy on an old brick building; the ivy will gradually dissolve the mortar to the point that the building’s integrity becomes threatened. Fresh, updatable content assets keep an organization’s communication integrity intact and ensure the ability to weather the storms of change.
Human beings within publishing teams should be creative, intellectual, value-added, and problem-solving participants, not automatons. Therefore, workflows should embrace automation and machine-support wherever possible, so humans can focus on creative productivity. Overdependence on manual labor touchpoints across the many vectors of content versions can lead to the robot “nightmare” scenario illustrated in Figure 2.
The accelerated number of variants that can result from just five categories, for only one content type is shown in Figure 3. Naturally, this total number of variants could also be multiplied by the number of content types, to create an even more staggering total.
Symptoms of Content Organizational Dysfunction
Inside publishing-focused enterprise departments, which describes almost every major group making up a large geographically distributed organization, the organizational design around content has grown over time into a tangled mess of siloed content production efforts with little connection or facilitation.
Some of the symptoms of content organizational dysfunction include the following features:
- It is difficult or impossible to discover existing content.
- Content must be manually moved from place to place during a workflow.
- Every authoring group has a separate set of content structural schemas and none are related.
- Email or shared drives is the primary way content moves from person to person.
- There are lots of ad-hoc spreadsheets created to manage various taxonomies and none of them are connected.
- Content lives in multiple places, often repeated or duplicated, in many different versions.
- There is no agreement on standard vocabulary for terms or tags.
- Content is created for single “pages” or other representational states.
- Personalization efforts are stymied by a lack of modular content.
The more content producers, and the fewer standards employed, the more chaos and disorder reigns. It’s logical to draw the following hypothesis: If content producers are unsupported and unhappy within a dysfunctional system, content effectiveness and customer experiences will suffer. And without change, one day, the system will implode upon itself in the form of high turnover among staff and decreasing market relevance. If content fails to keep up with customers, customers fail to keep up with companies.
How to Survive the Content Tsunami?
We cannot avoid mass proliferation of content, but we can organize to manage it in a sustainable way. [A] proposes a new solution: Within the context of a new Content Operating Model (COM), form a chartered Content Services Organization (CSO) and empower it with durable leadership in the form of three major practices: Content Strategy, Content Engineering, and Content Operations.
Content Strategy must work with the Content Engineering and Content Operations practices. These are three major functional practices that must exist on a permanent, chartered basis to shape content at a sufficient speed and quality to become truly “intelligent.”
In 2011, Ann Rockley and Joe Gollner defined intelligent content as follows: “Intelligent content is structurally rich and semantically categorized and therefore automatically discoverable, reusable, reconfigurable, and adaptable” (Rockley & Gollner, 2011).
[A] further defines intelligent content as ([A], 2018b):
- Coherent – Orchestrated against a Master Content Model® unifying systems for content interoperability.
- Self-Aware – Connected with semantics, taxonomy, structure, and context.
- Quantum – Able to exist in multiple states and systems at one time, leveraging content assets for optimum reach and impact.
Creating a working coalition of content practices that reshape content can seem like a daunting goal, because it is. 80% of companies believe content supply chain challenges impede their ability to deliver on top business objectives (Forrester, 2018). The emergence of established Content Strategy functions and the widespread adoption of related roles across enterprises has helped to solve some of these challenges. Both Content Engineering and Content Operations are relatively new concepts to but have begun taking more shape.
Content is everywhere in an enterprise, because it is the basis for all customer experience. Content now originates from virtually every function within enterprises. To some degree, everyone is a member of the “customer experience team” as sales and marketing content, product documentation, support, and technical assets are reviewed and rated by potential customers throughout the whole customer lifecycle. Content shared between marketing, sales, technical communications, knowledge management, learning, localization, and others contribute to unifying pre- and post-sale customer experiences as customers choose where to start and where to go next within the content sets.
Given the complexity of enterprise content publishing, the practice of Content Strategy cannot solve today’s challenges alone. Content strategists need specialized counterparts and enablers to realize and sustain the goals of more strategic deployment of content assets, including the integration of engineering and operations functions.
In a dynamic landscape, content must move and be transformed to empower organizations and drive customer value. Engineered content assets can be used in many places at once: they may be related, discovered, and used to deliver value across multiple systems and platforms, when and where needed, at the fastest possible throughput.
In this article, readers will find a practical model created by [A] in collaboration with enterprise practitioners as a future state prescription to adapt organization structures for the Intelligence Revolution, rather than a description of methods commonly in use today. Reinventing the organizational structure to support the next-generation of enterprise content and knowledge management will not be easy. We anticipate by making the changes outlined herein, we change the fundamental flows of information within an organization and influence all the creative acts surrounding crafting customer experiences.
And yet, as challenging as changing fundamental publishing process and supply chains is, enterprises expect content problems to only get dramatically worse without significant changes (Forrester, 2018), demonstrating that the costs of complacency are more perilous than steady progress towards a new Content Operating Model. The practices of Content Strategy, Content Engineering and Content Operations are defined below along with an approach on how they should work together within a Content Services Organization.
What Is Content Strategy?
One useful definition of Content Strategy comes from the article, “Rahel Bailie Provides a Content Strategy Primer”:
Content Strategy deals with the planning aspects of managing content throughout its lifecycle, and includes aligning content to business goals, analysis, and modeling. (Balilie, 2009)
[A] defines Content Strategy as an essential planning activity that identifies:
- What content an organization must acquire, manage, and leverage.
- What content experiences it must enable to meet its business goals.
Content Strategy organizes the vision for customer experience and establishes the business justification for investments to be made in improving how content is handled, defining the metrics that will be used to measure progress against the plan.
What Is Content Engineering?
Content Engineering is the application of engineering discipline to the design, acquisition, management, delivery, and use of content and the content technologies deployed to support the full content lifecycle (Gollner, 2014).
In the spirit of engineering, Content Engineering leverages authoritative patterns, frameworks and standards to organize, substantiate, and economize its efforts.
Content engineers organize the shape, structure, and application of content ([A], 2018). Engineering content overcomes content supply chain friction, thereby increasing the velocity of content through authoring, management, and publishing parts of the lifecycle. Content engineers make possible content personalization, targeting, reuse, and distribution across many channels and devices. They bridge the divide between content strategists and producers and the developers and content managers who publish and distribute content. But rather than simply wedging themselves between these players, content engineers help define and facilitate the content structure during the entire Content Strategy, production, and distribution cycle from beginning to end.
Content engineers make sure that correct practices, platforms, and technologies are in place to take the Content Strategy from plan to technically realized reality as a resource to development teams. In short, content engineers hold the keys that unlock both the gates that separate very talented and often isolated members of a content marketing team as well as the full potential of what the team can accomplish.
Content Engineering is so important because it emerges at the intersection of strategy, operations, and implementation. It bridges strategy, technology, operational logistics, development, and omnichannel delivery.
What Is Content Operations?
[A] defines Content Operations as the organization function that performs the day-to-day business of acquiring, managing, and leveraging content. It is a management activity within the Content Services Organization that monitors, evaluates, and guides the content lifecycle, and the resulting content experience. Content Operations takes the goals and requirements set by Content Strategy, and the content model and processes developed by Content Engineering and makes them real in terms of how the organization operates.
Content Operations executes against strategy and manages all content production workflows that take place when applying content structural and semantic standards, including the Master Content Model® ([A], 2018) and centralized semantic annotation, terminology, and tagging standards.
Content Operations collaborates directly with Content Strategy and Content Engineering, facilitating application of the Content Operating Model across authoring, localization, content management, and related teams. The Operations team directly empowers and facilitates distributed authoring processes in active production. It is the daily work of the Operations team that aligns systems and standards with active process, making possible the convergence and reuse of structured content types across various content domains.
Think of Content Operations as the glue or binding between the plan for content, the workflows and standards, the content management systems, and the daily management cycles that happen within publishing groups across the whole organization.
The goals of Content Operations:
- Oversee production content workflows and facilitate process best practices, standards, and optimization across various authoring groups in an enterprise ecosystem.
- Manage all the content transformation and enrichment workflows, those parts of the content lifecycle not directly related to the subject matter authoring itself.
- Increase developer and author efficiency by off-loading tasks that don’t require direct developer or author attention.
- Facilitate the education and adoption of standards, systems, and the enterprise content lifecycle.
- Provide stakeholder advocacy within CMS/CCMS/CEM/CSP/DAM and other content and semantic technology implementations and ongoing management, in collaboration with IT.
- Collaborate with technical DevOps, especially where systems developed in-house drive customer experiences as much as the content does.
- Increase content flow and effectiveness via consulting and facilitating with internal content committees, communities of practice, and governance or oversight groups, along with tight coordination with Content Strategy and Content Engineering stakeholders. See Figure 5.
How Do We Differentiate Content Strategy, Content Engineering, and Content Operations?
Content Strategy provides the who, what, when and why of content, while Content Engineering provides the how and Content Operations provides the where.
Each of these three practices has a guiding role that parallels stakeholders within corporate executive ranks:
|Content Strategy is the CEO of Content.||This practice sets the vision.|
|Content Engineering is the CTO of Content.||This practice builds the delivery.|
|Content Operations is the COO of Content.||This practice empowers action.|
Content Engineering Is Key to the Content Orchestration Triumvirate
A new bridge between stakeholders and developers must exist during planning and execution. Enter Content Engineering. The content engineer helps orchestrate the complex tools (musical instruments) and content (sheet music) to achieve a harmonious result (music played in key).
Content and data assets need to be empowered to move seamlessly across organizational silos, Web services, search tools, CRM, CRP, and CEM platforms. Content must be like electricity, moving and transforming to power organizations.
The practice of Content Engineering gives organizations increased strategic alignment and impact across publishing, and improves the overall effectiveness of the spend on assets that can be multipurposed across usage scenarios. Engineered content assets can be used in many places at once, related, discovered, and used to deliver value at the fastest possible throughput. But, for many organizations today, content is more like a rock: chiseled and placed in some wall like a brick, never to be moved.
Together, content strategists and engineers should be tireless advocates for the transformation of documents into reusable, structured content components connected by common semantics. In other words, these practices work in concert towards intelligence across all content domains.
The Orchestration Layer
Organizations need a new Content Operating Model (COM). The practices we have discussed need to be included in a full, holistic picture that includes a Master Content Model® and a master semantic model ([A], 2018a). The standardized structural model is an orchestration layer for content schemas. The semantic model is an orchestration layer for taxonomies and vocabularies. The Content Services Organization is an orchestration layer for the applications of standards and workflow among diverse, far-flung authoring groups.
These standards, in concert with other orchestration artifacts and process, are maintained by the tripartite functions of Strategy, Engineering, and Operations along with a an overall content leadership function.
Together, these form what [A] calls the Content Services Organization (CSO), ideally positioned as a centralized orchestration function across the entirety of the integrated enterprise. The CSO itself, defined and chartered formally within the Content Operating Model (COM), and charged with enacting the COM, forms a multidisciplinary epicenter for standards orchestration. The CSO is the primary internal organization responsible for implementation, and maintaining the ongoing rhythms, of the Content Operating Model and the core principles of content intelligence.
A chartered orchestration function provides a centralized environment for enacting global patterns across content and metadata sets that impact broad business value, including, but not limited to:
- Industry Standards
- Search Engine Optimization (SEO)
Each of these functions benefits from integration into content models, semantic models, and standards for customer experience. Each needs to both provide and inherit shared patterns, and each needs orchestration to drive efficiency and effectiveness. Valuing content as a broker of customer experiences requires cross-functional management, and operational models that puts controls in place for the movement, efficiency, effectiveness, and measurement of valuable content assets.
The primary content services leader, a Head of Content, that leads the CSO, can report to a CMO, a head of Customer Experience, COO, or even to the CEO. The key is that the cross-functional content organization must have efficient executive sponsorship and be empowered and funded to live up to its broad mandate to unify the Content Operating Model, and therefore the customer experience, across the enterprise holistically. Senior mandate and fiat figures in as a key success factor to a CSO successfully carrying out its mission. A CSO can exist in a subsidiary group, or within a business function if an enterprise-wide mandate cannot be accomplished. However, functionally-isolated CSOs will only succeed to the extent of their mandate and empowerment as an orchestration function.
There is clear business justification for investing in a COM and CSO as an internal content standards orchestration regime. Tangible profits and customer wallet share benefits can be derived from omnichannel delivery, dynamic personalization of content, and facilitating scalable operations (van Dijk, 2017). Greater customer traction can be derived from moving content to a consumption-based model that enables content fragments to be compiled. More automated assembly of content appropriate to different locales improves localization for international markets.
A Convergence Between Marketing and Technical Communications
Although progress has been made in terms of working together with shared, structured content, Techcomm and Marcomm need to work together to achieve a more unified, productive approach to omnichannel customer experience challenges. Historically, Marcomm has been primarily interested in presentation, while Techcomm has been more focused on in-depth content and structure. Both disciplines have had very different cultures in pre- and post-sales communities. Organizations may begin Customer Experience (CX) alignment around shared content structure and semantic standards as a way to stitch together content systems and processes.
How Context Should Influence Content
Context is critical for content-based Customer Experience (CX). With awareness of context, content can conform itself for fluid delivery to meet customers within their unique contextual frames.
Customer Experience Management (CEM) technologies, the growing big data lake or Customer Data Platform (CDP), Account-Based Marketing (ABM), and other contributors toward personalization have been transforming omnichannel marketing for a decade – but content has not caught up yet. We now know that the future of content experiences hinges on intelligent, contextual and predictive approaches to delivering personally-engaging and relevant content. We also know we have more data than ever available to us to craft these experiences.
The Content Services Organization (CSO) must exist to build and prepare content forms for use within all of these customer experience systems, so the content itself can keep up with the contextual user data to actually become available for the realtime assembly of experiences. Without content structured and available to machine processes, personalization efforts fail outright.
We need an enterprise “content pool” to match our enterprise “data pool” (Porter, 2012).
Current Models: How Old Bridges Can Collapse
As discussed, many content creators in Techcomm, Marcomm, or other teams within the enterprise are working with systems and solutions that may have been formed or started well over a decade ago. The compelling need to exchange content and data between Techcomm and Marcomm for relevance is a relatively recent development.
Many technical content creators are working with a content management system (CMS) or component content management system (CCMS) based on DITA designed primarily for technical documentation. The Darwin Information Typing Architecture or Document Information Typing Architecture (DITA) is an open XML standard data model for authoring and publishing. Since DITA components can be rearranged and easily reused, it is very beneficial in Techcomm. In contrast, most marketing content creators are working with some sort of customer experience manager (CEM) to make output more up-to-date and relevant. Usually, DITA does not interact cleanly with marketing-oriented CMS and CEM platforms, nor do the publishing models natively align. The COM and CSO solves this gap by assigning accountability for portability and interoperability to a business-driven group outside IT, tied closely with the strategic needs of the business. The CSO uses content in a Master Content Model® to reconcile DITA with other metadata and markup standards such as schema.org, Open Graph Protocol, and industry-specific XML standards.
Unfortunately, during the planning stage of many existing systems, there was no Content Engineering staff to help ensure that communications between the strategy, design, and content stakeholders and the developers would work together in the CMS configuration(s). As a result, specifications from content strategists often did not include the “how” piece: how to structure content, how taxonomies work together, and how to tie all of the components together with contextual customer data.
Intelligent Content Requires Redefined Teamwork
The unification of Content Strategy, Content Engineering, and Content Operations helps bridge a critical gap in communications that exists in most organizations. This new vision of teamwork ensures the “how” factor is communicated from Content Strategy to developers. But, of course, there are other practices needed for large-scale publishers. Highlighting some of these are:
- Knowledge Graph Architecture and Ontology Management
- Information Architecture and User Experience Design
- Data Science and Analytics
Teamwork across many kinds of disciplines also underscores the need for consistent architectural patterns including a Master Content Model® ([A], 2018) and semantic model to ensure a broad-based organization working across skill areas can orchestrate omnichannel content experiences from authoring through delivery today, while preparing for ever-more sophisticated content knowledge graphs that will become the basis for dynamically-assembled customer experiences in the future.
How hard is it to add Content Engineering into a team structure?
Adding Content Engineering into the content lifecycle is not an onerous process. Even at the team level, content owners can add Content Engineering disciplines into the lifecycle without major changes in the staff and organization, by assigning a single contributor at first, or training and upleveling a content structural specialist.
New Organizational Models Can Improve Communications
With the vast portion of our workflow landscape changing beneath our feet, new lines of communications between teams are essential. As content practitioners, we have been dealing with content structure for years. Content as a Service (CaaS) focuses on managing structured content into feeds that other applications and properties can consume. Now, as we move toward CaaS within publishing organizations, the need to normalize content and move content services across a global enterprise requires structural thinking at all stages of the content lifecycle. The time has come for us to imagine and create new organization structure to enable the increasing flow of content between groups.
Inevitably, some organizational restructuring will have to take place for all of the goals we have outlined to become successful. Nearly every touchpoint of customer experience and customer communications has changed dramatically since the advent of portable, smart devices.
The Semantic Foundry has recently posted a thoughtful analysis on system models for organizational design (Exploring System Models for Organizational Design, 2018). Ten system models are highlighted, each with pros and cons. There are many advantages to choosing a model as a starting point based on the context and strategy of an organization.
The author (“Semantic Foundry,” 2018) postulates that these models can spur productive conversations when organization thought around redesign includes systems, capabilities, process, people and culture. Taking the initial focus away from an existing org chart and focusing on capabilities and outcomes can lead to effective cross team collaboration.
[A] finds the Holonic Enterprise Model a useful starting point, wherein the core practices are represented within each authoring group. (See Figure 7.)
In this article, Semantic Foundry writes that the strengths of the Holonic Enterprise model are “flexible organization architecture combining best features of top-down enterprises and bottom-up subsystems loosely coupled through networks and alliances, allowing greater adaptability to a changing environment” (2018).
On the “down side,” this model needs a strong mission or purpose to keep various subsystems aligned with the enterprise. There is a potential for high coordination and orchestration costs associated with alignment. Decision-rights and authority must be specifically spelled out.
We like the representation of various roles within teams, all connected functionally and by specialized area. A holonic model, for example, might have dedicated product or regional content authoring teams living alongside a strategic practitioner (content strategist), structural and semantic practitioner (content engineer), and a content operations practitioner, who in turn coordinate with the leaders and standards-oversight groups within the Content Services Organization (CSO).
Managing Content in a Fractal Enterprise
Throughout our organizations, content expresses itself in many forms, all of them related. Topic-based content (for example, content describing facets of a particular product) has permutations and modified renditions as versions crop up across marketing, support, and other departments. Enterprise content therefore might be seen as ‘fractal’, faceted endlessly by various usages, a concept [A] Master Architect Joe Gollner has been advocating and educating on for almost 20 years, exploring how integrated content management and intelligent content are also connected to a fractal enterprise (Gollner, 1999, 2016a, 2016b). If we are to ever create coherence, common standards become essential to ensure connections, consistency, and integrated asset use and discovery.
The goal of a Content Services Organization should be to orchestrate consistency across fractal uses of content. This requires a healthy degree of balance, exerting influence on authoring and the entire content supply chain, without requiring every single fractal of content to pass through a centralized governance regime (an impossible task when permutations become infinite).
In any workflow model, there must be an appropriate balance between facilitating content from “the edge” (content creators who are nearest the customer) and content and editorial cycles from the “center” (content producers in centralized shared resource groups). An extreme or overly-constrained governance of content from a central authority can constrict content creation and lead to resentment and resistance from all content stakeholders, ultimately threatening the governance regime. Therein, lies the story of many gutted and abandoned governance efforts.
A balanced solution has reasonable authority to maintain and facilitate content structure and semantics standards utilized by shared content authoring tools, systems of record, and templates — to move content throughout multiple publishing lifecycles with a minimum of friction. The Content Services Organization ensures all the various content-producing groups remain in harmony with agreed-upon foundational standards, established at the “center” of Content Strategy, while listening to and adapting the structural and semantic standards regularly based on the needs from “the edge.”
Established standards should be based on an overarching architectural framework that helps to unify people, process, and tools. At [A], we call this the Content Intelligence Framework ([A], 2019). Regardless of the architecture approach chosen or defined internally, Content Services Organizations need a documented framework to steer and manage by, otherwise risking creating more confusion than coherence.
The Content Services Organization then evolves beyond just being the repository of enterprise-wide standards but also enables cross-functional collaboration, facilitates shared schemas and taxonomies, and works with IT and vendors to make sure system schemas encompass standards, strategy, software, and integrated systems. All of these functions housed within the framework work in unison under the oversight of the Content Services Organization and inform the entire organization’s operating rhythms. With the CSO facilitating, content producers, marketers, and product groups have plenty of room for variation and nimble improvisation as needed to assemble new content experiences from the agreed-upon ingredients, and business function owners can be assured that all content assets are able to conform to set criteria, laying a foundation for sustainable content intelligence.
This “fractal approach” to the organizational Content Operating Model also provides the benefit of allowing vast, distributed teams to be meaningfully engaged and recognized for their vital role crafting customer experiences. Authoring groups become empowered and supported by the Content Services Organization, not stifled by a centralized governance function that gets in the way of publishing.
A New Framework for Collaboration Across Multiple Roles
In order to deliver the right content to the right user at the right time, we must eventually develop an organizational structure which embraces the continuum between strategy and engineering practices and its related sub-disciplines. Figure 8 represents an organizational commitment toward content intelligence that actively involves participation from all content-producing groups within the enterprise.
The Interactions Between Content Strategy, Content Engineering, Content Operations, And Content Leadership
The diagram in Figure 9 has been adapted and extended from “New Thinking: Brain Traffic’s Content Strategy Quad” by Kristina Halvorson, proposed in new form here by [A].
Each practice overlaps others, necessitating close collaborative work across primary and secondary responsibilities. It is this overlap which enables each area to successfully contribute to shared business outcomes and influence the entire enterprise coherently. Keep in mind that as a team, the Content Services Organization will function best when all functions have inputs from others. For example, Analytics requires inputs from Strategy and Engineering, even if management of analytics regimes and daily administration is overseen by Leadership. And Strategy will provide key inputs to Quality standards, even though Operations maintains Quality services overall.
Within the Content Services Organization Capabilities Model, here is a review of core roles:
Content Strategy orchestrates the customer experience and editorial approach. It also works on overall process and the guiding structural standards, in collaboration with engineering. Content Strategy designs and curates the targeted content interactions. What content is resonating with our customers? What is our segmentation strategy? Which content maps to which part of the customer journey and market conversations? What do we need to publish to meet market needs?
Content Engineering encompasses process and structure governed jointly with Content Strategy to enable the original plan for publication. Engineering ensures the ‘how’ of content delivery is possible with integrated, consistent schemas across content technology systems (planning, authoring, management, publishing) and as low friction as possible through all stages of the content lifecycle. Working on the systems and standards needed to frictionlessly author structured omnipurpose content, tagged and annotated with controlled semantics, and available through the content supply chain to delivery endpoints that produce customer experiences across channels.
Content Operations is a management activity that deploys, operates, monitors, and evaluates the content lifecycle and supporting content ecosystem as they are used to realize and optimize the content experience. Content Operations administers analytics programs and reporting, quality assurance, and alignment between the content set’s semantics and structure standards and the actual content in production. Being the stakeholder who pulls so much together, Content Operations is uniquely positioned to oversee the quality and analytics across the entire content lifecycle, and ensure all workflow processes (including localization, accessibility, SEO, legal) perform their functions smoothly in concert with the content production teams.
Content Leadership oversees the business value drivers, the people strategy and organization within the CSO, the return on investment strategy and measures, and manages the standards and process around supporting analytics and data analysis functions. Leadership facilitates the relationships of the CSO with the overall enterprise executive environment, ensuring funding, authority, and resource availability for the CSO. Content Leadership also helps aligns business objectives with editorial strategy, ensures the business strategy is represented in structural standards, and works with Content Operations on consistent management of the overall content intelligence program.
Each of these roles depicted in Figure 9 should own the orchestration of the functions, but not necessarily be the exclusive partners involved. For example, the CSO team should work with people outside of the CSO, such as SEO specialists from marketing, to inform the effectiveness of initiatives. Members of the CSO participate broadly to connect and enable multiple groups within an organization. The CSO is an orchestration organization, and the center of gravity for content across the enterprise.
We have analyzed the challenges confronting existing content teams, and have proposed a future-state framework involving a Content Services Organization (CSO) that orchestrates standards and principles by which the various aspects of the content supply chain can be adapted into coherent interoperable forms, for cross-disciplinary collaboration involving Content Strategy, Content Engineering, and Content Operations practices.
Enterprise content teams must come together under a unified organization design and Content Operating Model (COM) with clear, shared goals to achieve an effective return on assets as part of an overall Content Strategy. In order to deliver the right content to the right user at the right time, we must develop an organizational structure that represents an organizational commitment toward content intelligence that involves participation from multiple content-producing groups within the enterprise.
The promises of true artificial intelligence (AI), chatbots and other conversational interfaces, augmented and virtual reality (AR and VR) environments, personalization, and so much more within our evolving content-driven world, simply require orchestration to bring to life. Although the challenges seem daunting as we seek new structures to birth these next-generation customer experiences, many organizations already have motivated teams ready to make changes in the face of the revolution, knowing that it is only through the fire of transformation that a new, more stable order can emerge.
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About the Author
Founder and principal at [A], the content intelligence service (simplea.com), and author of Content Engineering for a Multi-Channel World, Cruce Saunders has spent more than 20 years focused on content technology and has directed hundreds of digital and content engineering engagements along with the strong team at [A] including some of the industry’s most recognized leaders and practitioners. Cruce and the [A] team work with the largest and most complex enterprise content publishers on Earth, including Fortune 50 enterprises, governments, and other large institutions, crafting the next generation of content supply chains and customer experiences. Cruce regularly keynotes on omnichannel customer experience, content intelligence, AI, personalization, and intelligence transformation. For STC, Cruce has produced multiple articles published in Intercom. He also hosts a podcast, Towards a Smarter World, where he connects with leaders impacting global intelligence. Follow him on twitter at @mrcruce.
Manuscript received 20 July 2018, revised 04 March 2018; accepted 12 March 2019.