Master Data, enterprise architecture and digital transformation begin with a conceptual view of the enterprise
In the online world, a great deal of misunderstanding has developed regarding the term “taxonomy.” Originally used to describe biological classifications, the term has been used in the fields of library science, economics, education, technology, and information management.
Taxonomy is broadly understood as a way to classify the world into concepts and physical things. The world is comprised of categories and hierarchies with all physical and biological systems being comprised of subsystems. Similarly, information systems are comprised of hierarchies and systems built on subsystems.
An Evolving Definition
When taxonomy was first applied to the online world, agencies and developers considered the navigational structure to be a taxonomy – a method to organize the information resources of a web site or an intranet so that users could click through from one resource to another and easily understand the knowledge structure represented on the site or intranet. This initial definition became an oversimplification as taxonomy began to be considered more than navigation. The classification definition of taxonomy (as opposed to the navigation definition) included data structures – the terminology used to tag content. The “term store” in Microsoft SharePoint became the container for organizing principles at this opposite end of the spectrum.
Classification versus Navigation
Neither of these views – navigational structures at one end and classification terminology at the other – considers the processes and systems that lie between the two extremes. These processes and systems have names, but they are not navigation and are not terms applied to content. This may seem trivial in concept but is nuanced and complex in practice. Organizations continue to have challenges around finding and using information, not because the technologies are inadequate or because people don’t know how to make information useable, but because the landscape of information and the ecosystem of technologies is a living, changing, evolving thing. Moreover, when systems, processes, terminology and data structures are called different things by different people or the same names are used to describe different things, it becomes more difficult to make sense of that changing ecosystem.
As the information environment changes, systems need to be updated, switched out, reconfigured, and integrated on an ongoing basis. Change is continual, and the organization is challenged with upkeep and understanding of an increasingly complex array of applications, tools, structures, processes and mechanisms.
One way to deal with complexity is a foundation of consistency. In some programs this is called Master Data, in others, Enterprise Architecture, in still others, data standards, data quality, data curation, metadata management, information architecture, and our favorite, taxonomy initiatives. In any case, the goal is to develop consistency in the way that information of all kinds is classified.
Taxonomy and Business Concepts
Why call this taxonomy? Perhaps because our definition begins at the conceptual level. Taxonomy begins with a view of the enterprise from the perspective of business users and business objectives. It defines the things that are most important to the business related to people, products, services, customers, processes and the value-creating mechanisms at the heart of the enterprise.
Taxonomy does not start with data or data structures. It does not start with systems or applications. It begins with concepts by asking “what are all of the things that you interact with on a day-to-day basis?” “What are all of the processes that you engage with, applications you interact with, and people you speak to, both internally and externally?” “How do those people, processes and technologies interact?”
The result is a map of concepts and how those concepts are manipulated, transformed, interacted with and organized to produce the value of the enterprise. It encompasses the intellectual capital of the organization and the value networks that consist largely of information flows.
The Domain Model
The mapping process output is the “domain model” – the master diagram of everything that defines the enterprise. Sometimes this is referred to as an ontology, but regardless of what it is called, the domain model is a way of defining the fundamental building blocks of knowledge and process. Those building blocks represent the things that are then captured and manipulated through thousands of processes and interactions across hundreds of thousands to hundreds of millions of transactions with the marketplace.
The conceptual building blocks get translated into design elements – including the data structures, application designs, search systems, and information processes that comprise the business. By starting at the highest conceptual level, common understanding of terminology and concepts can be woven into every process and every system. In contrast, starting at the level of data structures misses important conceptual elements and misses how those conceptual elements come together.
Digital Transformation Requires Common Understanding
Although no organization can start with a completely clean sheet in looking at its domain model, all digital transformations should begin with this point of view. As processes are transformed to serve customers in new ways and as more products and services are virtualized and digitized, the foundational data structures need to be consistent, data processes need to be governed, and organizations need to be in agreement about the meaning of terminology and have common taxonomies that define all aspects of the business. Digital transformations are both data transformations and process transformations. Those transformations need to start with common definitions and understanding at all levels of the organization.
A classic error made when organizations embark on enterprise taxonomy programs is to try to get agreement on a single set of navigational structures. That will never work. There is no single way to look at all information. “We’ve tried that – it doesn’t work” should really be “We’ve tried to do that incorrectly – of course it didn’t’ work.” Multiple navigational structures can be derived from consistent classification structures. Consistent organizing principles, definitions, naming conventions, and data standards can be applied to various types of systems, various levels of granularity, and various contexts.
Enterprise Architecture and Enterprise Taxonomies
Enterprise architecture, enterprise data standards, enterprise data quality and enterprise governance begin with enterprise taxonomies. Unfortunately, many taxonomy consultants, information architects, digital agencies, and system integrators do not have a global view of knowledge and information that begins with the conceptual view of structured and unstructured data. It is easier to dive into the weeds of a system deployment, functional specifications, or application development. Many organizations do not have the patience or vision to begin with this abstract perspective. The result of such a vision does not always have a short-term impact on the bottom line and tangible immediate ROI that is the driver for most project decisions and resource allocations.
The transformations that are occurring of business and technology are unprecedented. We are at an inflection point in human history, and seeing the possibilities requires seeing the organization as a series of information flows that need to be optimized. Products and services are increasingly software- and information-based. Customer interactions are increasingly digital.
Optimized Customer Experience Requires Optimized Information Flows
The goal of digital transformation is to more effectively serve customers. However, when systems are stitched together through piecemeal integrations with one-off architectures and siloed interests, the information flows that comprise the customer experience cannot be optimized and therefore neither can the customer experience.
The era of big data, analytics, cognitive computing, semantic technology and machine learning requires a holistic approach to integrating structured and unstructured data, content, information, and knowledge and allowing for endless combinations of digital services and systems. Evolution and adaptation of the enterprise is based on the digital DNA of the business. That DNA is built on a foundation of consistent, curated, defined and – at some level – organized information. Taxonomy is essential to digital transformations and understanding the landscape of the business foundational to taxonomy development. The new master data starts with taxonomy.