Master Data Management and Enterprise Taxonomies - A Common Vision

Building shared understanding and a common vision is part of the process. 

One of our enterprise customers is a large retail organization that is wrestling with how to gain alignment across the organization around common language and terminology.   This issue is at the core of enterprise taxonomy programs. Arriving at a common understanding of terminology, and using technology effectively to leverage it pose many challenges. The taxonomy project is running in parallel with a Master Data Management (MDM) initiative.  MDM provides a consistent data set for enterprises, essential for processes requiring information sharing and analysis.

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Gaining synergy from having these two projects proceed in tandem makes sense, because MDM and taxonomy projects share many common goals.  They both seek to have consistent information about customers, products, and content across enterprise processes.  Getting clarity of meaning and consistent definitions are prerequisites of MDM and the chief aim of taxonomy initiatives. 

Show progress with quick-wins

In the case of each of these kinds of programs, it is easy to get bogged down in the details and lose sight of business value and long-term outcomes. Yet keeping the big picture in mind--while providing short term wins to show steady progress-will help ensure business stakeholder buy-in and maintain energy, enthusiasm, and focus over the long time horizon that is needed for success.  Examples of short- term wins include:

  • Establishing common business term glossaries and vocabularies (just getting agreement across different groups can be a key accomplishment)
  • Retagging a subset of high value content in customer facing or internal systems to improve findability 
  • Automating a small set of dashboards through a tool like SharePoint to illustrate potential integration capabilities when metadata and terminology are mapped across systems

Many of these types of projects are considered as standalone – developing them within the context of an enterprise taxonomy and MDM roadmap will allow much greater long term synergies while providing short term wins. Each of these is relatively low effort and can show the power of enterprise taxonomies extrapolated to the rest of the enterprise.

The benefit from enterprise taxonomy is the cumulative benefit from all the systems that it supports.  Taxonomy is a foundational component of MDM, and MDM is a foundation to many other systems and processes.  Quantifying the benefit of one without the other is like quantifying the benefit of a chart of accounts without an accounting system.  One is of little value without the other.

Why start with taxonomy?

The driver for all organizations is the desire to overcome inefficiency in dealing with information – especially when legacy systems have been in place for years.  Systems upon systems are integrated, modified, added on to, and adapted in order to develop new capabilities.  Because these systems have different developers, code bases, and architectures, concepts are represented in different ways.

The result is a complex, brittle environment that requires immense resources just to maintain – with no ability to transform how the business interacts with customers. Enterprises are reaching the tipping point in needing to start fresh with new technology. However, new technology requires a foundational set of organizing principles – a new taxonomy, a new semantic architecture, a new ontology.

We start with taxonomy because taxonomy represents a hierarchy of business concepts.  Those concepts can then be translated into all of the tools and technologies that allow the business to do its work.  Starting with the business concepts means that the process originates with the people who need the information in order to do their jobs, not with technologists who may not have a full view of the enterprise strategy.

Let’s say that we are developing a new product information management system.  We can start with metadata schemas and data architecture – a very technology-centric approach.  Or we can start with the person that the system aims to serve. To understand the customer, we should ask a lot of questions, including:

  • Who are the customers?  How do we describe them? 
  • What do they need?  How can we serve them? 
  • What categories of products are customers purchasing? 
  • What do they need to make their purchase? 
  • How would they shop for a particular type of product?  Compare products?  Research them? 
  • What attributes would they want to search on?  .

Answering these questions leads to development of the concepts that can then lead to technical design details that are driven by real user needs. 

Why engage stakeholders from across the business in your MDM initiative?

Another outcome of the process, and a necessary step in developing an enterprise view of content and information, is that diverse stakeholder groups gain a shared understanding of the complexity and landscape of enterprise information flows.  Most enterprises are so complex that few business users understand information flows throughout the enterprise at more than a conceptual level. 

One can argue that people don’t need to understand more than their part. That may be true on an operational level – but a great deal can be achieved by raising the level of understanding for key process owners.  By having stakeholders participate in domain modeling sessions, the collective understanding of how terminology is shared and reused can be significantly improved, leading to new insights and identification of areas for improvement in processes and information quality.  This is an incredibly valuable exercise because it starts the process of building mindshare and common vision. 

The problems of information redundancy, ambiguity of meaning, inconsistency of terminology, and conflicting representations become crystal clear to participants in such exercises, and cause people to leave nodding their heads in agreement about what needed to be done.   This clarity provides more energy and enthusiasm for the process, and helps people stay on task as the project unfolds. Further, it reveals areas of opportunity for quick wins and high impact business application of taxonomy and MDM.

Many organizations have tried and failed to develop enterprise taxonomies. The problem is that they may not have been ready for the process, may not have had the correct resources, or may have been less mature in their approach. In some cases, the business wanted the benefit of an enterprise taxonomy but did not know how to structure ways for the stakeholders to interact, so it never really happened in a productive way. One of the most common pitfalls is to expect people to do this in their spare time without real guidance or the right expertise.  People are expected to figure it out or attend a conference, read a book, download some white papers. and do it. This approach typically produces a result commensurate with the level of attention and experience, and ends up not meeting the organization’s needs.     

These days, getting MDM and consistent business taxonomies right is essential to staying competitive and achieving the level of agility needed in the digital marketplace and to support digital transformation. 

Business and technical stakeholders need to share the same vision and understanding and focus on business outcomes. If they can do so, they will serve customers efficiently and effectively across devices, channels, and formats, and will provide customers with product and service information when they want it, where they want it, and how they want it.

To learn more about our approach to launching an MDM program read: Launching a Master Data Management Program: Eight Key Steps in the Journey

Meet the Author
Seth Earley

Seth Earley is the Founder & CEO of Earley Information Science and the author of the award winning book The AI-Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster, and More Profitable. An expert with 20+ years experience in Knowledge Strategy, Data and Information Architecture, Search-based Applications and Information Findability solutions. He has worked with a diverse roster of Fortune 1000 companies helping them to achieve higher levels of operating performance.