How organizations manage their data directly impacts their success or failure. The correlation between data analytics and intelligence to competitive advantage and growth has led to heavy investments in those technologies throughout the last decade. So, if you consider that content is the consumable form of data, then it follows that the era of big data has now given way to the era of big content.
Employees, customers, partners, investors, and regulators – all internal and external stakeholders – are clamoring for content to stay employed, educated, entertained, and connected. And all these content consumers are more empowered than ever before, meaning organizations must harness not just the power of their data but also that of their content assets to meet information demands. This data-content continuum exists because of the inherent challenges and opportunities both data and content management share and because content is the form of data closest to your customers and other key audiences.
Like data, content is getting the attention it deserves as organizations recognize it as a valuable business asset and a competitive differentiator with a critical role in business success. It must be managed effectively and optimized for the greatest possible return. Importantly, to support a digital-first era in which audiences access data from various devices, organizations know the content they produce must reach their target audience in the right format, at the right time, and in the right place for ultimate consumption. What’s more, content must be measured, and stakeholders informed as to the success or otherwise of the content, with the capability to improve it over time.
Additionally, content management in highly regulated industries, like pharma, financial services, and government, comes with even more complexity. Each piece of content must meet legal and regulatory standards, which can cause friction with those across the organization making time to market and personalized customer experience priorities over meeting compliance requirements.
Modernizing Content Lifecycle Management
The enterprise is getting a reality check as more and more complexities emerge in modernizing and future-proofing their content ecosystems. For example, even within a single content group, such as documents, a company might juggle many types of documents – contracts, business reports, standard operating procedures (SOPs), and technical manuals, to name just a few. As the number of authors, reviewers, regulations, content types, file types, consumers, and consumer devices increases, so too does the complexity of your content production process. These span the entire content lifecycle – from creation to consumption. What’s more, these organizations don’t know if the content created works for them, in terms of resonating with the desired audiences, complying with industry regulations, or turning prospects into customers. In short, these organizations don’t know their content ROI.
Think about how investments in data infrastructure transformed data management and governance. Now imagine how content infrastructure investments could transform end-to-end content lifecycle management to accelerate time to market, reduce costs, and increase the effectiveness of your content strategy.
Your organization will struggle to keep up with customer content demands if your processes and software still reflect the traditional content workflow model in which content is manually adapted for each of the many different print and digital channels. With content automation, your organization can save time and money plus keep your subject matter experts (SMEs) focused on what they do best.
A modern content lifecycle management infrastructure is built on technologies that unify content creation, automation, and intelligence to power content creation, collaboration, assembly, publishing, and analysis. Think of modern content lifecycle management’s value this way: It’s modular, so content components can be created, updated easily, and reused at a moment’s notice; it’s rich with metadata to make content components compliance-controlled and easy to search and assemble in whatever format resonates best with your audience; and it’s omnichannel, so you can create a piece of content once and publish it across all print and digital channels as needed. Modernizing your content operations in this way gives you the power to use the same content in an email, a product data sheet, and a website with complete accuracy and consistency.
Relevant content reaches the right people in the right format via the right channels in line with unique corporate and industry requirements. And by connecting all the stages – from concept to execution – you can confidently tackle today’s content challenges and be prepared to support new requirements tomorrow. Further, modern content lifecycle management has baked-in intelligence through dashboards and reports so you know if your content is really working. Open collaboration and direct feedback to content authors and designers further improves an organization’s content operations, as they work together to improve content quality and performance.
And, because your content is componentized and stored as XML, AI and machine learning algorithms can be applied to all the stages of the content lifecycle to automate and improve content.
See the Value of Your Content Through Automation
Enterprise content publishing continues to evolve, fueled by digital transformation that demands business rules, processes, and solutions for a digital-first strategy (and in many cases, a mobile-first strategy) and supporting ecosystem. Content automation bridges this transition and will help you successfully inform, engage, and build trust among internal and external stakeholders.
Enterprises that produce a large volume of content in a variety of formats – print, web, mobile, and more – inevitably confront complexity and cost, as well as compliance. A point solution is good at addressing one activity in the content lifecycle but can be problematic for companies with medium- to high-complexity authoring processes. An example of this is the creation of a bank’s standard operating procedure (SOP), which requires strict corporate and governmental regulations, plus policies and procedures from audit, risk, and legal experts.
A point solution doesn’t have all the capabilities to manage authoring and review processes. This results in several challenges, including missteps in internal workflows, error-prone review processes, tool, and template inconsistencies, and added strain on IT teams to help implement, maintain, and troubleshoot the one-off, disconnected applications. A centralized content automation platform supports multiple departments across the enterprise. It resides on a common IT infrastructure, ideally SaaS-based, which makes it simple to deploy, maintain and update. It also integrates with core data sets, third-party apps, and input sources via APIs to extend collaboration and efficiency across the organization’s wider ecosystem.
Realizing greater value from both your data and content requires sound strategy and enabling technology. Much of what you know from implementing processes and systems to manage your data assets also applies to managing content assets. Similarly, the right tools exist to help you modernize content lifecycle management so your organization can further achieve digital transformation plus improve customer satisfaction, regulatory compliance, and revenue growth. That’s the real crux of the data-content continuum.