Steven Forth is a Co-Founder of TeamFit. See his Skill Profile.


In 2018, we saw increased emphasis on skill and competency management as a central aspect of the talent management puzzle. There were important product announcements from leading vendors including Docebo and Degreed. At the same time, many of the world’s top consulting companies did research and published on emerging skill requirements across many industries.

The learning management system (LMS) Docebo calls its new skill module the Perform Module. It “allows employees and managers within a company to evaluate skills, manage roles, and assign specific learning content to people that have skill gaps in specific roles.” I like the name of this module, Perform. After all, it is skills and skill management that hold the key to performance, not learning per se. Skill management systems will be central to organizational performance in a way that learning is not.

The hot thing in learning and development is learning experience platforms (LXPs), at least according to Josh Bersin. The leading example is Degreed in part because Degreed takes skills seriously. They go so far as to assert that “Learning doesn’t drive results. Skills do.” Degreed is also unusual in that it provides a solution for individuals and organizations (much like TeamFit does). It allows people to go through a process to certify their skills. I have done this myself, and was awarded a Level 7 certificate in Pricing Strategy (which is one of my passions).

Another compelling part of the Degreed approach is data ownership. Degreed and TeamFit agree that individuals should own their own skill records and be able to carry these with them over their careers. For more on this important theme see (Ownership of data in a collaborative age).

McKinsey has been doing a lot of good work identifying skill trends across many industries. At TeamFit, we have leveraged this into our work for a major mining company on the skill requirements for the future of mining. McKinsey has also been focussed on the impact of AIs, robots and automation on the future of work. The foundational research was done in 2017 and McKinsey continues to elaborate on this theme (see The Digital Future of Work: What Skills Will Be Needed).

Deloitte gathers many of its insights in this area under “Human Capital Trends.” There are a number of important insights in their 2018 report and taking the 2019 survey is thought provoking. An important theme is the ‘network of teams’ operating model.

TeamFit is designed to look at how the skills of different individuals combine to represent those of a team and we have done a lot of research into the role complementary and connecting skills play in building effective teams. Deloitte also has a concept, the extended talent network. This refers to the skills of the business partners, former employees (I once worked at Monitor Group, which is now part of Deloitte), consultant, thought leaders and advisors that you can leverage to get work done. A good skill management platform needs to provide scalable access to this extended network.

What does this mean for talent management leaders in 2019? How will skill and talent management evolve and what impact will this have on organizational performance? Here are some ideas to explore in 2019.

  1. Put skills and competencies at the centre of your talent management work
  2. Pay more attention to internal mobility over external recruiting
  3. Think in terms of data ownership, not data privacy
  4. Expect to use multiple competency models

Put skills and competencies at the centre of your talent management work

Skills connect learning to performance. When organized into a competency model (more on these below) skills become the hub of your learning, performance management, career development, outsourcing and talent acquisition.

You can build your skill model two ways: top down, in the form of a competency model that you design, or bottom up, letting people identify the skills they use and suggest skills to each other. You can also do both and let the TeamFit platform find the connections.

Pay more attention to internal mobility over external recruiting

The past five years have seen a lot of noise and excitement around recruiting and talent acquisition platforms. For most companies though, the key to transformation and new capabilities lies inside the organization and not outside. They have many people with the potential skills to move into new roles and to take on new challenges. Failing to give people these opportunities puts organizations at the risk of losing their best people.

Back in October, we participated in a session put on by Orange Silicon Valley (part of the French Telecom Orange’s innovation platform) where there was a discussion on internal mobility (in addition to TeamFit there was representation from Degreed, LinkedIn and Udemy) followed by a design thinking session on when and how to enable internal mobility. You can read more about this design thinking session here.

Think in terms of data ownership and not data privacy

2018 was the year of data privacy. In Europe, the General Data Privacy Standards came into play, provoking a reaction in the centre of the share all data world, California. The new California data privacy law will come into effect in 2020 baring new legislation on data privacy at a Federal level (which does not appear likely at this time).

At the same time, the HiQ vs. LinkedIn law suit is winding its way through the courts. If you have not been following this, you should be. It has many implications for data privacy in the enterprise as well. The case asks important questions around what one can and cannot do with publicly available data.

Human resources leaders should all be thinking about how they gather and use data about their employees. 2019 will see many discussions of people analytics and its combination with AI and deep learning. This debate tends to be held in terms of data privacy but another way to think about it is data ownership. Over the next decade, we expect many people to assert an ownership claim about data that has been collected about them. Social media, shopping and mobility will be the initial targets of this movement, but corporate data, especially HR data, will not be far behind. If you collect learning and performance data about your team, expect people to demand that you share it with them and provide them with a way to carry it with them when they leave your company. This will be of great benefit to you over time, as the people you hire and your extended talent network will bring data with them that your analytical systems can leverage. Respect ownership and not just privacy.

Expect to use multiple competency models

One thing that surprised us in 2018 was the realization that many companies use not just one, or two but dozens of different competency models. On reflection, this is not so surprising. Different parts of the business will need different models and models need to evolve. One company that we work with has a set of Marketing Competencies, a set of Brand Competencies and is building competency models for Digital Marketing and Customer Centricity. These all apply to the same group of people. Think of the competency models as different lens into the skills needed for a particular area of performance. Perhaps organizations need more and more varied competency models, models that can evolve with use, rather than monolithic views that can only be updated with great effort. In 2019, you should be building expertise on how to rapidly create, deploy and evolve competency models. This will help you think more clearly about how all of the work you do in human resources, learning and development and talent management comes together to drive performance.

What are your goals for skills, competencies and talent management generally in 2019. Let us know at