In a poll we conducted during our webinar on “How Ontologies Drive Digital Transformation,” only 16% of the participants had developed ontologies that were functioning in a production environment, and 20% were at the pilot stage. The largest group (40%) had a good understanding of ontologies but was not using them, and 24% had no experience at all with ontologies. So despite their value to organizations, ontologies are not yet seeing widespread use. This reality presents opportunities for companies to gain a competitive edge by leveraging their data in a way that many companies are not. 

Finding ontology skills

One of the barriers to launching an initiative to develop an enterprise ontology may be concern about how to staff such an initiative. In fact, some of the steps involved in ontology development are likely to be at least somewhat familiar, because they involve the basics of organizing information and creating taxonomies. Ontologies are created by defining relationships among entities in different taxonomies, and most companies have some sort of taxonomy, such as a list of clients or products organized by category. There may be people in your company who care already involved in data governance who can help make it happen.

Even if just one person begins to look at holistically at the organizing principles in the company, audits existing systems and metadata structures, and assesses the quality and consistency of data, those actions can get an ontology project started. It is important to take a comprehensive view initially to look at the company and define its key elements. Then a team can be set up with multiple stakeholders to discuss the digital assets of the company that each of them owns, to develop a broader view. Once the assets are evaluated enterprise-wide, and metadata structures identified, it will be evident that a lot of harmonization needs to take place. There will be uplift from that alone.

If everyone owns it, no one does

The foundational work is critical, because relationships cannot be developed among different taxonomies unless the data is properly tagged. Data hygiene, content hygiene, and information architecture are the basis for both taxonomies and ontologies. However, even if it is a team effort, one person should own the ontology. If everyone owns it, nobody owns it. A committee may not do a good job of enforcing the rules consistently. 

There is a lot of talk in this field about cognitive engineers, AI experts, and data scientists. When one company wanted to deploy a virtual engineer and could not find content engineers they had to grow their own. They had knowledge architects, content architects, and user experience people. This combination was effective. Developing an ontology was not something completely new, but an extension of what they had been doing. You can look at a team and see who understands the processes, the business objects, the users, and the sources of information in the technology stack. These are the people you need. Ontology management tools can be used to document the relationships that are established. In some cases, a master data management (MDM) system can sometimes provide a starting point for documenting the ontology.

Finding value in the first projects

The next step is to build an ontological representation and show value to the company. Target a measurable process and then show an impact on the process in order to maintain executive level interest and funding. If you don’t have a practical application, then developing an ontology is just an intellectual exercise and it is difficult to maintain interest. You might start with the introduction of a new product and relating it to key customer groups, for example, and then perform some analytics to see if conversion improves.

Although you may begin with a single ontology project, it is important to view ontology as a program. It needs ongoing care and maintenance. There are times when an immediate need arises because something is on fire at that moment, such as a marketing initiative for a new group of products that affects short term needs of customers and an ad hoc review is needed. There is also a place for scheduled reviews, in which a group of taxonomies are reviewed to see if the market is still reflected in that taxonomy or it needs updating. This in turn will affect the relationships in the ontology. There may have been “editorial drift” in which people modified a taxonomy without due process. What is done upstream impacts what can happen downstream.

Nothing about this is easy (or sexy) but it needs to be done if your initiatives are going to make headway.  Our team of information science experts can help.  Give us a shout if you'd like to talk.

For more information on ontologies, see Seth Earley’s new book, The AI-Powered Enterprise:  Harness the Power of Ontologies to Make Your Business Smarter, Faster and More Profitable.