In the era of publishing’s emergent global digital marketplace, many organizations are struggling with strategic questions about how to change their approach, planning, and execution around creating and managing their metadata. In the traditional publishing world, a significant portion of the metadata created and stored was on an “as-needed” basis — often bubbling up from a single department and incurring a technology debt due to the lack of planning for the longer term. These older, now substandard practices often led to longer development cycles and releases, as organizations were forced to slog through metadata cleansing challenges and siloed views of their company’s assets. These necessarily inconsistent efforts, in turn, led to customer experiences that were inconsistent across product lines. Further, these ad hoc approaches entailed a lack of reproducibility in content analytics, such that publishers simply could not tell which pieces of their content were achieving the greatest readership or immediate impact.

As a 21st century publisher, this is not what you want.

Committing to transition to a more planful strategy around Metadata Management can be daunting, as it involves significant changes around management accountability for the initiative and around its ongoing governance. A further — but equally critical — step entails alignment with the organization’s existing technology stack. While each organization’s challenges will vary, below I’ll highlight just a few of the most common challenges that face publishers when they commit to the project of seriously leveraging their metadata assets.

Misalignment of Long-Term Business Goals with Technical Execution and Roadmap

When technological expertise, business acumen, and the application of best practices come together, the resulting synergy can create a combined value far in excess of their individual parts. The benefits of merging technology-backed and business-driven roadmaps are varied and clear; they include increased ROI, more predictable release schedules, operational efficiencies, and maximization of both data resources and product capabilities. This far-off nirvana, however, is not easily achieved. Traditionally, core areas of Metadata Management are often thought of as cost centers rather than as profit centers (that is, as “a costly nuisance” or (worse) “overhead”). Misalignments can result, such as one technical team having a goal “to dramatically reduce all data storage costs related to metadata” while the business-facing team is tasked with “championing the exploitation of long-term metadata assets.” Reducing the inefficiencies and tension between business and technical work touching on metadata strategy, and specifically its costs and valuation, is one of the key areas a company must examine when looking into business realignment.

Lack of Organizational Metadata Governance Leading to Inconsistent, Siloed Metadata

It is common within a publishing company – indeed within any business organization – that various departments or teams operate in silos or fiefdoms, each pursuing its individual goals and requirements when making decisions about ingesting, managing, or storing metadata. Without organizational Data Governance, it is very difficult — and it may be impossible! — to ensure discoverability across all channels in an efficient way and to ensure decisions about metadata are made with all factors considered at an organizational level rather than at the level of the interests and goals of any one team. A lack of Metadata Governance manifests itself in lost opportunities and conflicting interpretations of company reporting as well as an overall lack of efficiency around making proper, informed, and long-standing decisions about the business. To put it simply: the organization and its customers will suffer from not knowing what data they have, what its value is, how the data may be accessed, or even what metrics matter. Basic bottom-line stuff. By contrast, a company with a well-established Data Governance approach — one that considers all aspects of combining and leveraging a company’s metadata assets — will reap benefits such as reduced project costs, shorter time-to-market, and increased overall product quality.

Metadata Treated as Static Inventory Without Semantic Enrichment to Aid Discoverability

The “users” of metadata are rapidly shifting to encompass both humans and machines. As the volume of metadata being produced grows exponentially, the ability to support discovery and to categorize and enrich content metadata will act as a differentiator and empower research. Creating semantically enriched metadata has to, as its goal, drive users to the meaning of content, not simply the typical identifiers and values associated with a citation. Alternatively, when core metadata is not squeezed further in this manner, huge opportunities in functionality, machine-assisted research, and overall customer experience will be missed. Thus, the creation and usage of semantically enriched metadata should be part and parcel of a larger product strategy, and its ready availability and utility should be thought of as a core business asset and product feature.

Above I have described only three high-level examples of common challenges faced by organizations trying to develop better processes and policies around how they treat and value their metadata. Metadata strategy and execution is not a one-size-fits-all equation, however. Each organization’s individual challenges, products, technologies, and goals must be factored into its overarching metadata strategy. Wondering how to get started? Here are four simple steps:

  1. Seek and ensure leadership support and alignment.
  2. Develop a metadata strategy with dedicated focus and consultation.
  3. Invest resources to ensure best practices for ongoing Data Governance are followed.
  4. Create an execution plan that aligns business and technology roadmaps.

Check out Part One of the Metadata Blog Series here.

Author: David Schott

David Schott is the Senior Manager of Data Engineering at Copyright Clearance Center and has been working with bibliographic metadata for over 15 years. He has held roles related to building data systems supporting transformation, normalization and large-scale data augmentation. During his career, David has also led many business efforts in analyzing how emerging publishing industry trends manifest in technical workflows, data formats and bibliographic standards.
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