How Skills Ontology is revolutionizing talent management?

It’s no longer up for debate, our economic environment is constantly changing. Professional Services Organizations are facing challenges that are evolving as well. Technological advances continue to run amok in an increasingly competitive field, with ever more demanding customers. This difficult context requires organizations to continuously reinvent themselves. Among their challenges, the issue of good resource management is at the top of the list. As we have already mentioned, skills are shared today like a currency. Valuable, evolving and specialized, it represents the very wealth of service companies. In fact, it is crucial to use it, optimize it, exploit it and sell it wisely. And this is the whole purpose of the skills ontology. This innovation developed by Whoz deserves a spotlight.

Understanding, organizing and leveraging skills: this key issue

When it comes to skills, it’s natural to talk about the challenges facing service companies. By selling intellectual services, these organizations have no choice but to rely on the expertise available in their talent ecosystem. This knowledge base remains their main lever of differentiation and added value. Understanding, managing and leveraging this knowledge is fundamental to meeting customer needs. Competence guarantees the quality of the services provided, and therefore customer satisfaction and employee commitment.

Except that, as we know, the management of these skills is complex and often not very formalized. The days when managers could process and assign them with Excel spreadsheets are over. Technology has taken over by offering powerful solutions. Competency ontology is one of these game-changing innovations. The objective of such technology is to formalize and structure competencies to better manage and value them.

The starting point of this approach is an observation: responding to customer demand is becoming complex. They expect more precise answers, closer relations between the different families of skills. And above all, categories of expertise that are always in line with the evolution of work and new professions. Relying on basic knowledge is no longer enough. Competency ontology is one of the most effective and sustainable ways to move in this direction.

Skills Ontology: What is it?

Let’s go into the basis of the competency ontology, or rather what it is not. In a very basic way, most companies have systems that put forward a database of skills. A knowledge base that is illustrated as a list of terms with associated definitions. A minimum level of knowledge then follows. Managers have at their disposal a series of rigid expertises that do not connect to others.  

The ontology goes far beyond a simple database or taxonomy of skills. Much more flexible and dynamic, this approach proposes an intelligent mesh between generalist skills, technical skills, etc. This concept is illustrated by a formal and structured representation of the skills required for a given job. 

The idea is to base the ontology on a classification of expertise, built on the relationship between skills. For example, “methodology” is one of the many ways of doing project management, which is itself a parent skill of “agile methodology”.

How did Whoz develop its skills ontology?

To fully understand the benefits of a competency ontology, it is necessary to take a leap to the product side. And since it is always easier to talk about what we know, we will focus our reflection on the ontology developed by Whoz. 

By making more complex what a skill was in Whoz and in particular by having a more precise hierarchy, we could then better answer to projects of new functionality for Whoz

When Whoz was in its infancy more than seven years ago, the team began building its skills repository using statistical analysis. These were based on experiences and job postings to extract skills and group them into different categories. In 2019, Whoz came to the conclusion that this method was not sufficient. Indeed, it was becoming difficult to collect all the relevant skills. As for the categorization, it was not precise enough.  

The Data team then had an idea: to make the skills more complex, in particular by having a more precise hierarchy. In fact, Whoz could then respond more efficiently to different projects. 

After the first entry on May 25, 2020, the database was thus developed and enriched. From there, the team began to make skill, a more complex object than just a word attached to a category. By creating a hierarchy of skills, the idea is to associate one skill with another. A sort of deep mesh with precise and pointed connections between the different type of skills, whether they are technical, generalist, rare, etc. 

For example, if a manager is looking for the skill “website development”, the technology will submit related skills such as HTML, CSS or Javascript. And going even further, Javascript will involve other levels of expertise such as Typescript, NPM, node.js, etc.

The skills ontology developed by Whoz currently has 11 hierarchical levels, although it is possible to go even further according to customer needs.

How is the skills ontology an opportunity for Professional Services Organizations?

By making a static database more complex, we simplify the management of an organization’s competencies. The ontology makes it possible to offer a single database for an entire ecosystem, and even beyond. As mentioned above, service companies are faced with major challenges to sustain their growth. Competencies are now their main differentiation lever on the market. They must be able to classify them efficiently and group them in a coherent way. 

Thanks to the competency ontology, organizations improve their understanding of the expertise required for a given mission, as well as that which they possess. They can then better define the roles and responsibilities of each mission, and therefore better adapt the profiles of their talents according to the required skills. 

Today, the terms of competencies are infinite. Managers cannot understand and think about all the possible skills for a mission. AI thinks for them by identifying, from a CV for example, the skills that a talent has. In a more active way, this same manager can consult the skills corresponding to his search, and even display related ones. 

In fact, organizations can better identify the current skills of their talents as well as their potential gaps. It then becomes easier to offer them personalized training to develop certain expertise required for given missions. By extension, this clear visibility of resources tends to improve the quality of the services provided, and therefore customer satisfaction. 

In short, ontology fits perfectly into this competency-based organization approach. By putting the knowledge and expertise of their talents at their core, service companies improve the understanding of their resources, better respond to their customers’ needs, strengthen their reputation and sustain their growth.

Ce n’est plus à débattre, notre environnement économique est en constante évolution. Les sociétés de services sont confrontées à des défis qui év